Podcasts about Oracle Database

Yahoo Finance reported that Oracle beat expectations on total revenue in its fiscal fourth quarter while cloud sales missed analyst estimates. Oracle's cloud portfolio includes Oracle Cloud Infrastructure for compute and AI workloads and cloud applications such as Fusion and NetSuite. Supply limits on GPUs, new data center capacity, and multi-cloud security and compliance reviews are slowing deployments and revenue recognition. Oracle is pursuing multi-cloud strategies with integrations that place Oracle Database near Azure and Google Cloud while expanding AI-ready infrastructure. Founders should expect longer validation cycles, cloud-agnostic requirements, and co-selling motions to move enterprise deals. Key metrics to watch include remaining performance obligations, any disclosed growth splits, and capital expenditures tied to new regions and AI capacity.Learn more on this news by visiting us at: https://greyjournal.net/news/ Hosted on Acast. See acast.com/privacy for more information.

Have you ever wondered where all your digital memories, work projects, or favorite photos actually live in the cloud? In this episode, Lois Houston and Nikita Abraham discuss cloud storage. They explore how data is carefully organized, the different ways it can be stored—whether right next to the server or across the network—and what keeps it safe and easy to find.   Cloud Tech Jumpstart: https://mylearn.oracle.com/ou/course/cloud-tech-jumpstart/152992 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Radhika Banka, and the OU Studio Team for helping us create this episode. ------------------------------------------------------   Episode Transcript:    00:00 Hi there! We're hitting rewind for the next few weeks and bringing back some of our most popular episodes. So, sit back and enjoy these highlights from our archive. 00:12 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:38 Nikita: Welcome to the Oracle University Podcast! I'm Nikita Abraham, Team Lead of Editorial Services with Oracle University, and with me is Lois Houston, Director of Innovation Programs. Lois: Hey there! Last week, we spoke about the differences between traditional and cloud data centers, and covered components like CPU, RAM, and operating systems. If you haven't listened to the episode yet, I'd suggest going back and listening to it before you dive into this one.  Nikita: Joining us again is Orlando Gentil, Principal OCI Instructor at Oracle University, and we're going to ask him about another fundamental concept: storage. 01:16 Lois: That's right, Niki. Hi Orlando! Thanks for being with us again today. You introduced cloud data centers last week, but tell us, how is data stored and accessed in these centers?  Orlando: At a fundamental level, storage is where your data resides persistently. Data stored on a storage device is accessed by the CPU and, for specialized tasks, the GPU. The RAM acts as a high-speed intermediary, temporarily holding data that the CPU and the GPU are actively working on. This cyclical flow ensures that applications can effectively retrieve, process, and store information, forming the backbone for our computing operations in the data center. 02:05 Nikita: But how is data organized and controlled on disks? Orlando: To effectively store and manage data on physical disks, a structured approach is required, which is defined by file systems and permissions. The process began with disks. These are the raw physical storage devices. Before data can be written to them, disks are typically divided into partitions. A partition is a logical division of a physical disk that acts as if it were a separated physical disk. This allows you to organize your storage space and even install multiple operating systems on a single drive. Once partitions are created, they are formatted with a file system. 02:53 Nikita: Ok, sorry but I have to stop you there. Can you explain what a file system is? And how is data organized using a file system?  Orlando: The file system is the method and the data structure that an operating system uses to organize and manage files on storage devices. It dictates how data is named, is stored, retrieved, and managed on the disk, essentially providing the roadmap for data. Common file systems include NTFS for Windows and ext4 or XFS for Linux. Within this file system, data is organized hierarchically into directories, also known as folders. These containers help to logically group related files, which are the individual units of data, whether they are documents, images, videos, or applications. Finally, overseeing this entire organization are permissions.  03:55 Lois: And what are permissions? Orlando: Permissions define who can access a specific files and directories and what actions they are allowed to perform-- for example, read, write, or execute. This access control, often managed by user, group, and other permissions, is fundamental for security, data integrity, and multi-user environments within a data center.  04:21 Lois: Ok, now that we have a good understanding of how data is organized logically, can we talk about how data is stored locally within a server?   Orlando: Local storage refers to storage devices directly attached to a server or computer. The three common types are Hard Disk Drive. These are traditional storage devices using spinning platters to store data. They offer large capacity at a lower cost per gigabyte, making them suitable for bulk data storage when high performance isn't the top priority. Unlike hard disks, solid state drives use flash memory to store data, similar to USB drives but on a larger scale. They provide significantly faster read and write speeds, better durability, and lower power consumption than hard disks, making them ideal for operating systems, applications, and frequently accessed data. Non-Volatile Memory Express is a communication interface specifically designed for solid state that connects directly to the PCI Express bus. NVME offers even faster performance than traditional SATA-based solid state drives by reducing latency and increasing bandwidth, making it the top choice for demanding workloads that require extreme speed, such as high-performance databases and AI applications. Each type serves different performance and cost requirements within a data center. While local storage is essential for immediate access, data center also heavily rely on storage that isn't directly attached to a single server.  06:11 Lois: I'm guessing you're hinting at remote storage. Can you tell us more about that, Orlando? Orlando: Remote storage refers to data storage solutions that are not physically connected to the server or client accessing them. Instead, they are accessed over the network. This setup allows multiple clients or servers to share access to the same storage resources, centralizing data management and improving data availability. This architecture is fundamental to cloud computing, enabling vast pools of shared storage that can be dynamically provisioned to various users and applications. 06:48 Lois: Let's talk about the common forms of remote storage. Can you run us through them? Orlando: One of the most common and accessible forms of remote storage is Network Attached Storage or NAS. NAS is a dedicated file storage device connected to a network that allows multiple users and client devices to retrieve data from a centralized disk capacity. It's essentially a server dedicated to serving files. A client connects to the NAS over the network. And the NAS then provides access to files and folders. NAS devices are ideal for scenarios requiring shared file access, such as document collaboration, centralized backups, or serving media files, making them very popular in both home and enterprise environments. While NAS provides file-level access over a network, some applications, especially those requiring high performance and direct block level access to storage, need a different approach.  07:50 Nikita: And what might this approach be?  Orlando: Internet Small Computer System Interface, which provides block-level storage over an IP network. iSCSI or Internet Small Computer System Interface is a standard that allows the iSCSI protocol traditionally used for local storage to be sent over IP networks. Essentially, it enables servers to access storage devices as if they were directly attached even though they are located remotely on the network.  This means it can leverage standard ethernet infrastructure, making it a cost-effective solution for creating high performance, centralized storage accessible over an existing network. It's particularly useful for server virtualization and database environments where block-level access is preferred. While iSCSI provides block-level access over standard IP, for environments demanding even higher performance, lower latency, and greater dedicated throughput, a specialized network is often deployed.  08:59 Nikita: And what's this specialized network called? Orlando: Storage Area Network or SAN. A Storage Area Network or SAN is a high-speed network specifically designed to provide block-level access to consolidated shared storage. Unlike NAS, which provides file level access, a SAN presents a storage volumes to servers as if they were local disks, allowing for very high performance for applications like databases and virtualized environments. While iSCSI SANs use ethernet, many high-performance SANs utilize fiber channel for even faster and more reliable data transfer, making them a cornerstone of enterprise data centers where performance and availability are paramount. 09:56 Do you want to master Oracle Database on AWS? Check out the Oracle Database@AWS course, where you'll learn provisioning, migration, security, and high availability. Validate your new skills with a certification and stand out in the multicloud space. Visit mylearn.com to learn more!  10:23 Nikita: Welcome back! Orlando, are there any other popular storage paradigms we should know about? Orlando: Beyond file level and block level storage, cloud environments have popularized another flexible and highly scalable storage paradigm, object storage.  Object storage is a modern approach to storing data, treating each piece of data as a distinct, self-contained unit called an object. Unlike file systems that organize data in a hierarchy or block storage that breaks data into fixed size blocks, object storage manages data as flat, unstructured objects. Each object is stored with unique identifiers and rich metadata, making it highly scalable and flexible for massive amounts of data. This service handles the complexity of storage, providing access to vast repositories of data. Object storage is ideal for use cases like cloud-native applications, big data analytics, content distribution, and large-scale backups thanks to its immense scalability, durability, and cost effectiveness. While object storage is excellent for frequently accessed data in rapidly growing data sets, sometimes data needs to be retained for very long periods but is accessed infrequently. For these scenarios, a specialized low-cost storage tier, known as archive storage, comes into play. 11:59 Lois: And what's that exactly? Orlando: Archive storage is specifically designed for long-term backup and retention of data that you rarely, if ever, access. This includes critical information, like old records, compliance data that needs to be kept for regulatory reasons, or disaster recovery backups. The key characteristics of archive storage are extremely low cost per gigabyte, achieved by optimizing for infrequent access rather than speed. Historically, tape backup systems were the common solution for archiving, where data from a data center is moved to tape. In modern cloud environments, this has evolved into cloud backup solutions. Cloud-based archiving leverages high-cost, effective during cloud storage tiers that are purpose built for long term retention, providing a scalable and often more reliable alternative to physical tapes. 13:01 Lois: Thank you, Orlando, for taking the time to talk to us about the hardware and software layers of cloud data centers. This information will surely help our listeners to make informed decisions about cloud infrastructure to meet their workload needs in terms of performance, scalability, cost, and management.  Nikita: That's right, Lois. And if you want to learn more about what we discussed today, head over to mylearn.oracle.com and search for the Cloud Tech Jumpstart course.  Lois: In our next episode, we'll take a look at more of the fundamental concepts within modern cloud environments, such as Hypervisors, Virtualization, and more. I can't wait to learn more about it. Until then, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 13:44 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

Hosts Lois Houston and Nikita Abraham are joined by Brent Dayley, Senior Principal APEX and Apps Dev Instructor, to explore the latest vector AI supporting features in Oracle Exadata and GoldenGate 23ai. The conversation begins with an overview of Exadata's capabilities and then shifts to how GoldenGate is powering distributed AI, real-time data streaming, and analytics with advanced microservices architecture. Brent highlights recent GoldenGate enhancements, including distributed vector support, robust monitoring, OCI IAM integration, and support for next-generation AI workloads via real-time vector hubs.   Oracle AI Vector Search Deep Dive: https://mylearn.oracle.com/ou/course/oracle-ai-vector-search-deep-dive/144706/ Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, and the OU Studio Team for helping us create this episode.   Please note, this episode was recorded before Oracle AI Database 26ai replaced Oracle Database 23ai. However, all concepts and features discussed remain fully relevant to the latest release.   -------------------------------------------------------   Episode Transcript:   00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Lois: Hello and welcome to another episode of the Oracle University Podcast! I'm Lois Houston, Director of Communications and Adoption Programs with Customer Success Services, and with me is Nikita Abraham, Team Lead of Editorial Services with Oracle University.  Nikita: Hi everyone! Thanks for joining us! In our previous episode of this series, we took a deep dive into Oracle AI Vector Search and Retrieval Augmented Generation, or RAG, showing how unstructured data can be transformed into embeddings to power smarter, more context-aware AI with Oracle Database 23ai. Lois: That's right, Niki. We also explored how the OCI Generative AI service can be used with both Python and PL/SQL, and how AI Vector Search enables relevant information retrieval for large language model prompts. 01:21 Nikita: Today, we're focusing on the latest supporting features for Oracle AI Vector Search. Joining us once again is Brent Dayley, Senior Principal APEX and Apps Dev Instructor. Welcome back, Brent! To kick things off, could you outline what's new in Exadata with the 24ai release, particularly for AI storage? Brent: So Exadata has ushered in a new era of AI capabilities with 24ai release. Key features of Exadata system software 24ai include AI Smart Scan, Exadata RDMA Memory, known as XRMEM, Exadata Smart Flash Cache, and on-storage processing.  In-Memory Columnar Speed JSON Queries, Transparent Cross-Tier Scans, and caching enhancements, including Columnar Smart Scan at Memory Speed, Exadata Cache Observability, and Automatic KEEP Object Load into Exadata Flash Cache.  Now, Exadata system software 24ai is a significant release. It ushers in a new era of AI capabilities for Oracle Database users.  Now there have been some infrastructure improvements, including the ability to increase the number of virtual machines on X10M and Secure Boot for KVM Virtual Machines.  We have also improved and enhanced high availability and network resilience, including improved RoCE Network Resilience and enhanced RoCE Network Discovery. There have been some enhancements for monitoring and management, including AWR and SQL Monitor Enhancements and JSON API for Management Server.  Additionally, security enhancement. SNMP Security. Now, Exadata system software 24ai is supported on Exadata database machines and storage expansion racks from X6 and newer.  03:40 Lois: Those are some fantastic advancements for Exadata users. Now, let's pivot to distributed AI. Brent, can you walk us through how GoldenGate enables distributed AI? Brent: Let's take a look at some common GoldenGate use cases as a refresher. The first use case is multi-active, high availability, and cross-region deployments, spanning on-premises and cloud environments.  Another use case includes data offloading and data hub creation in order to support multiple downstream applications. Real-time data stores for Downstream Marts and Analytics. Micro and mini services architecture and an audit history of transactions.  Other use cases include migrations and upgrades of databases, including OCI-hosted databases. Another use case would be creating analytic data feeds for various applications, including SaaS and on-premises apps. And finally, stream analytics using application and transaction events captured by GoldenGate Stream Analytics.  05:03 Nikita: We know GoldenGate has long been a staple for enterprise data integration. So Brent, what makes GoldenGate the best choice today, and how has its architecture evolved? Brent: It offers DIY Stream Analytics. GoldenGate does remain the top choice for Enterprise Standard, real-time data streaming. It supports Oracle and third-party databases, vector sources, messaging systems, and NoSQL databases.  OCI offers a fully managed pipeline builder for Stream Analytics. This pipeline leverages various OCI services, such as OCI Streaming for real-time event ingestion, OCI Dataflow for stream processing, OCI Big Data for data storage and processing, and OCI Stream Analytics for real-time event processing and analysis.  GoldenGate microservices, available since 2017 in Oracle GoldenGate 12.3, is used in over 4,000 deployments in OCI. Benefits of GoldenGate microservices include the ability to employ the same trusted Extract and Replicat processes as the classic architecture.  Provides flexible and secure remote administration through a user-friendly web interface or CLI. Deployable on-premises in OCI as a service and in third-party cloud environments. Simplified patching and upgrading process.  Now the GoldenGate architecture evolution. First, classic architecture that was deprecated in version 19c and desupported in 23ai. Microservices Architecture introduced in version 12.3 and is the recommended architecture. A migration utility is available to upgrade from classic to microservices architecture.  07:12 Are you ready to create and manage AI Agents in Fusion Applications? Check out the Oracle AI Agent Studio for Fusion Applications courses! Start with the Foundations course to build, customize, and deploy AI Agents, and then advance to the Developer Professional certification. Explore hands-on labs and real-world case studies. Visit mylearn.oracle.com for all the details.  07:39 Nikita: Welcome back! It sounds like the latest GoldenGate updates offer new features and integrations. Could you share more about these enhancements? Brent: There are many new features and enhancements in GoldenGate, along with microservices, including a redesigned GUI for enhanced usability. Integration with StatsD and Telegraf for monitoring and metrics. OCI IAM integration for secure access control.  JSON Relational Duality for flexible data handling. Next-generation AI with distributed vector support. PDB Extract Capture for efficient data extraction from Oracle Pluggable Databases. DDL notification on Target Tables for schema evolution management.  Support for non-Oracle and Big Data technologies. Online DDL and EBR enhancement for improved performance. Data Streams Pub-Sub for asynchronous data dissemination. Async API support for standardized event communication. High-availability clusters for increased resilience. Trail Files Management for efficient data storage. And support for new features in 23ai database.  It also includes integrated diagnostics for improved troubleshooting of IE and IR processes. And 30 or more OS and database certifications for wider platform support. @Dbfunction Mapping for custom data transformations. And lastly, GoldenGate free recipes for pre-built solutions and best practices.  New in GoldenGate, distributed AI processing with vector replication.  09:37 Lois: And what type of use cases does this enable? Brent: Migrating vectors into Oracle Vector Database. Replicating and consolidating vector changes. Implementing multi-cloud, multi-active Oracle vector databases. Streaming text and vector changes to search engines.  Key considerations include that embedding models must be consistent across all vector stores for effective similarity searches.  10:09 Lois: Now, many organizations wonder if they can use generative AI with their own business data. Brent, how do enterprises typically approach this? Brent: Organizations are using generative AI typically like this.  Building LLMs from scratch. Training models on proprietary data for specific tasks. Fine-tuning LLMs, adapting pre-trained models to a specific domain using private data. And prompt engineering with retrieval augmented generation or RAG. Augmenting prompts with relevant information retrieved from a knowledge base to improve the accuracy and relevance of LLM responses.  Now it's possible to create a real-time vector hub for GenAI. This hub can ingest real-time data from various sources, including Oracle and third-party relational databases, vector databases, third-party messaging systems, and NoSQL databases, business updates, documents, events, and alerts.  11:11 Nikita: And how does the vector hub work?  Brent: DML and DDL changes, vector changes, and prompt or chat history are used to enrich prompts. And embedding model generates embeddings from the text data.  Similarity search is performed on these embeddings to retrieve relevant information from the vector hub. The retrieved information is used to augment the prompt, leading to more accurate and trustworthy answers from the LLM. Now, the benefits of real-time data and generative AI include the ability to ensure answers are based on fresh business data. And helps reduce hallucinations in generative AI responses.  Actionable AI and machine learning from streaming pipelines allows data from ERP and SaaS applications, databases, event messaging systems, and NoSQL databases to be ingested into streaming pipelines. This data can then be used for AI and machine learning model training, similarity searches, machine learning tasks, external AI, and machine learning integrations, alerts, and data product creation.  12:25 Lois: So if you had to summarize, Brent, why does GoldenGate 23ai stand out for artificial intelligence workloads? Brent: Well, first up, it improves data quality for AI model training and fine-tuning. And secondly, it enhances retrieval augmented generation by providing real-time access to relevant business data, leading to more accurate and trustworthy generative AI responses.  Nikita: Thank you, Brent, for sharing your insights and detailing these exciting new features across Oracle's AI stack. If you'd like to dive deeper into these topics, don't forget to visit mylearn.oracle.com and look for Oracle AI Vector Search Deep Dive course. Until next time, this is Nikita Abraham… Lois: And Lois Houston, signing off! 13:16 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.  

In this episode, learn how to migrate on-premises Oracle Database workloads to Oracle AI Database@Azure, where Oracle database services run on Oracle Exadata infrastructure located inside Azure datacenters. Then see how, once your database is in place, you can modernize faster by connecting Oracle data to Microsoft Fabric for analytics and building AI experiences with Foundry, Copilot Studio—using familiar Azure tools. Chapters 00:00 - Introduction 00:58 - What is Oracle AI Database@Azure 05:33 - Azure Portal experience 11:30 - Microsoft integrations (Fabric, Foundry) 14:00 - Agentic experience 15:54 - Wrap up & close Recommended resources Learn Docs Azure Product Page Connect Scott Hanselman | Twitter/X: @SHanselman Oracle AI Database@Azure | LinkedIn: linkedin.com/groups/14707004 Azure Friday | Twitter/X: @AzureFriday Azure | Twitter/X: @Azure

In this episode, learn how to migrate on-premises Oracle Database workloads to Oracle AI Database@Azure, where Oracle database services run on Oracle Exadata infrastructure located inside Azure datacenters. Then see how, once your database is in place, you can modernize faster by connecting Oracle data to Microsoft Fabric for analytics and building AI experiences with Foundry, Copilot Studio—using familiar Azure tools. Chapters 00:00 - Introduction 00:58 - What is Oracle AI Database@Azure 05:33 - Azure Portal experience 11:30 - Microsoft integrations (Fabric, Foundry) 14:00 - Agentic experience 15:54 - Wrap up & close Recommended resources Learn Docs Azure Product Page Connect Scott Hanselman | Twitter/X: @SHanselman Oracle AI Database@Azure | LinkedIn: linkedin.com/groups/14707004 Azure Friday | Twitter/X: @AzureFriday Azure | Twitter/X: @Azure

In this episode of the Oracle University Podcast, hosts Lois Houston and Nikita Abraham are joined by Brent Dayley, Senior Principal APEX & Apps Dev Instructor. Together, they explore how to implement Retrieval Augmented Generation (RAG) using Oracle AI Vector Search and OCI Generative AI. Brent walks listeners through the similarities and differences between building RAG workflows with Python and PL/SQL, offering practical insights into embedding creation, semantic search, and prompt engineering within Oracle's technology stack.   Oracle AI Vector Search Deep Dive: https://mylearn.oracle.com/ou/course/oracle-ai-vector-search-deep-dive/144706/ Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Kris-Ann Nansen, and the OU Studio Team for helping us create this episode.   Please note, this episode was recorded before Oracle AI Database 26ai replaced Oracle Database 23ai. However, all concepts and features discussed remain fully relevant to the latest release.   --------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Lois: Hello and welcome to another episode of the Oracle University Podcast! I'm Lois Houston, Director of Communications and Adoption Programs with Customer Success Services, and with me is Nikita Abraham, Team Lead for Editorial Services with Oracle University.  Nikita: Hi everyone! If you joined us last week, you'll remember we explored AI Vector Search and how Retrieval Augmented Generation, or RAG, empowers large language models by surfacing relevant business content for smarter, more context-aware answers. Lois: That's right, Niki. We also looked at how unstructured data gets transformed into embeddings, how these vectors power semantic search, and how Oracle Database 23ai is uniquely designed to support these advanced AI workflows. Nikita: Today, we're building on that foundation with an exciting double feature. We'll start with an introduction to OCI Generative AI Service and how you can use it with Python, and then dive into Retrieval Augmented Generation with Oracle AI Vector Search and the OCI Gen AI service using PL/SQL. 01:32 Lois: And to walk us through these topics, we're delighted to welcome back Brent Dayley, Senior Principal APEX & Apps Dev Instructor. Brent, it's great to have you. So, tell us, how does the OCI Generative AI service use Oracle AI Vector Search? Brent: So OCI Generative AI service allows us to take user questions and augment those using external data from outside of the large language model that allows us to return augmented content.  We would leverage Oracle AI Vector Search in order to retrieve contextually relevant information. And we would create prompts that have some sort of a meaning to help guide the user to input the appropriate types of questions. And this allows us to retrieve the data using a large language model.  02:27 Nikita: What are the typical steps for implementing a RAG workflow using the OCI Generative AI service in Python? Brent: We would load the document. Transform the document to text. And then split the text into chunks.  So if you're talking about maybe a PDF that contains chapters, we might split the different chapters into individual chunks. We would then set up Oracle AI Vector Search and insert the embedding vectors. We would build the prompt to query the document. And then we would invoke the chain.  So first, you would load the text sources from a file. Open a terminal window and connect to your compute instance. And launch ipython to allow interactive work.  Ipython allows you to insert a series of steps in order to put different commands in different steps. You might load the source file called FAQs. Next, you would load the FAQ chunks into the Vector Database. You would create a connection and connect to your database. And then create the table. And then you would vectorize the text chunks and then encode the text chunks. And then insert the chunks and vectors into the database.  Next, you would vectorize the question. Define the SQL script ordering the results by the calculated score. Define the question. Write the retrieval code. And then execute the code. Finally, you would print the results. Then we would create the large language model prompt and call the AI generative LLM. Ensure that our prompt does not exceed the maximum context length of the model. And then define the prompt content.  We would then initialize the OCI client and then make the call.  04:47 Here's some exciting news! Oracle University has training to help your teams unlock Redwood—the next-gen design system for Fusion Cloud Applications. Learn how Redwood improves your user experience and discover how to personalize your Fusion investment using Visual Builder Studio. Whatever your role, visit mylearn.oracle.com and check out these courses today!  05:12 Nikita: Thanks, Brent. That gives us a nice overview of how Python can be leveraged with OCI Generative AI. Now, how would you compare working with Python for building RAG applications to using PL/SQL? Can you walk us through the high-level process for building a RAG solution in this environment? Brent: First, we would want to load the document. Next, we would transform the document into plain text. After that, we would take that text and split it into meaningful chunks. Next, we would go ahead and set up Oracle AI Vector Search and insert the embedding vectors. We would then build the prompt so that we can query the document. And then we would invoke all of those previous steps as our chain.  06:04 Lois: OK, and can we take a closer look at each of these steps?  Brent: Step 1, text extraction and preparation. So, let's imagine we have some sort of document that we want to use as the augmented information. We would load that document. Next, we would transform the document to text. And we have a function in the DBMS Vector Chain Package called util to text. And this is used to extract plain text from the loaded documents.  Next, we would want to split the text into meaningful chunks. The DBMS Vector Chain Package has another function called util two chunks, that allows us to divide the extracted text into smaller, more manageable pieces, which we call chunks.  07:02 Nikita: Once we have our text chunks ready, what's the next step to make our data searchable and useful for the large language model? Brent: Step number 2, we would want to go ahead and use embedding models in order to create our vectors. We would load multiple ONNX models into the database. And the reason we would do this is because models with a greater number of dimensions usually produce higher quality vector embeddings.  So you might want to load multiple different ONNX models into the database so that you can generate embeddings from each of the models, and then compare those vector embeddings using those different models. You would create vector embeddings using PL/SQL packages.  07:55 Lois: After embeddings are created, how does the solution find the most relevant content in response to a user's question? Brent: Step 3, we would then go and do a similarity search so that we can return a response. We would select the text chunks that have the relevant information for the input user question based on vector search. This allows for integrating with Oracle's Gen AI Large Language Model Service to generate responses. The process ensures that the large language model generates contextually appropriate and relevant answers for those users' queries.  Now, step 4 is to build the prompt, and I want to stress the importance of large language model prompt engineering. What this will do is to carefully craft input queries or instructions so that we can get more accurate and desirable outputs from the large language model.  This allows developers to guide the LLM's behavior and tailor its responses to specific requirements. This is what we call LLM Prompt Engineering. And it allows us, as I was saying, to craft input queries or instructions so that we can create more accurate and desirable outputs.  Next, we would use an example interactive RAG application that uses the Streamlit framework in order to create a user-friendly interface. This interface will allow us to upload documents, pose the question, and receive relevant answers generated by the underlying RAG pipeline within the database.  In the final step, we will have an input prompt that asks us to ask a question about the PDF. We will then type in some sort of a question relative to the PDF content. And then we would retrieve the return data based on the input question.  10:11 Nikita: Brent, thank you for walking us through both the Python and PL/SQL approaches for building RAG solutions with Oracle Generative AI. If you'd like to dive deeper into these topics, don't forget to visit mylearn.oracle.com and look for the Oracle AI Vector Search Deep Dive course. Until next time, this is Nikita Abraham… Lois: And Lois Houston, signing off! 10:33 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

This week on Azure Friday, Scott Hanselman talks with Jonathon Frost about AI-enhanced migration from Oracle to PostgreSQL using the VS Code PostgreSQL extension. See how developers can automate schema conversion, transform application code, and validate results using an intelligent, agent-driven workflow. Chapters 00:00 - Introduction 00:36 - Model Hyperparameter Tuning, Agent Orchestration, and Determinism 02:25 - Architectural Overview of AI-enhanced Schema Migration 04:28 - How it is Built on the VS Code Extension for PostgreSQL 04:56 - Self-correction of AI-enhanced Migration 05:59 - Migration Demo 06:33 - Connect to Oracle Database 07:23 - Connect to PostgreSQL Database 07:50 - Connect to Azure OpenAI Endpoint 08:45 - Run Migration 09:37 - Review Completed Migration Report 11:07 - Visualize Schema of PostgreSQL Database 12:17 - Side-by-side File Diff 13:30 - Where to get the Extension and Learn More Recommended resources Learn Docs VS Code Extension Marketplace Page Azure Product Page Blog Connect Scott Hanselman | Twitter/X: @SHanselman Jonathon Frost | LinkedIn: linkedin.com/in/jjfrost Azure Database for PostgreSQL | LinkedIn: linkedin.com/company/azure-database-for-postgresql Azure Friday | Twitter/X: @AzureFriday Azure | Twitter/X: @Azure

This week on Azure Friday, Scott Hanselman talks with Jonathon Frost about AI-enhanced migration from Oracle to PostgreSQL using the VS Code PostgreSQL extension. See how developers can automate schema conversion, transform application code, and validate results using an intelligent, agent-driven workflow. Chapters 00:00 - Introduction 00:36 - Model Hyperparameter Tuning, Agent Orchestration, and Determinism 02:25 - Architectural Overview of AI-enhanced Schema Migration 04:28 - How it is Built on the VS Code Extension for PostgreSQL 04:56 - Self-correction of AI-enhanced Migration 05:59 - Migration Demo 06:33 - Connect to Oracle Database 07:23 - Connect to PostgreSQL Database 07:50 - Connect to Azure OpenAI Endpoint 08:45 - Run Migration 09:37 - Review Completed Migration Report 11:07 - Visualize Schema of PostgreSQL Database 12:17 - Side-by-side File Diff 13:30 - Where to get the Extension and Learn More Recommended resources Learn Docs VS Code Extension Marketplace Page Azure Product Page Blog Connect Scott Hanselman | Twitter/X: @SHanselman Jonathon Frost | LinkedIn: linkedin.com/in/jjfrost Azure Database for PostgreSQL | LinkedIn: linkedin.com/company/azure-database-for-postgresql Azure Friday | Twitter/X: @AzureFriday Azure | Twitter/X: @Azure

Join hosts Lois Houston and Nikita Abraham as they explore one of the most exciting innovations in enterprise AI: Retrieval Augmented Generation (RAG) powered by Oracle AI Vector Search. In this episode, Senior Principal APEX & Apps Dev Instructor Brent Dayley walks through the fundamentals of RAG, explaining how it combines Oracle Database 23ai, vector embeddings, and large language models to deliver accurate, context-rich answers from both business and unstructured data. Discover the typical RAG workflow, practical setup steps on Oracle Cloud Infrastructure, and how to work with embedding models for real-world applications.   Oracle AI Vector Search Deep Dive: https://mylearn.oracle.com/ou/course/oracle-ai-vector-search-deep-dive/144706/ Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Kris-Ann Nansen, and the OU Studio Team for helping us create this episode.   Please note, this episode was recorded before Oracle AI Database 26ai replaced Oracle Database 23ai. However, all concepts and features discussed remain fully relevant to the latest release.   ----------------------------------------------   Episode Transcript 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Nikita: Welcome to the Oracle University Podcast! I'm Nikita Abraham, Team Lead: Editorial Services with Oracle University, and joining me is Lois Houston, Director of Communications and Adoption Programs with Customer Success Services. Lois: Hi everyone! If you've been with us this season, you'll know we've already covered a lot about Oracle AI Vector Search. In Episode 1, we introduced the core concepts—how vectors let you search by meaning, not just keywords, and how embedding models translate your unstructured data into a searchable format inside Oracle Database 23ai.  Nikita: Then, in Episode 2, we took a deeper dive into how these vectors are actually stored and managed. We explored the different types of vector indexes, similarity metrics, and best practices for designing and optimizing your database for semantic search.  Lois: Right. Today, we're shifting gears into one of the most exciting real-world applications: Retrieval Augmented Generation, or RAG. You'll learn how RAG combines the power of Oracle AI Vector Search with large language models to answer natural language questions using both business and unstructured data.  01:39 Nikita: We'll walk through the workflow, highlight why Oracle Database is uniquely suited for RAG, and give you the essential steps to get started. Back again is Senior Principal APEX & Apps Dev Instructor Brent Dayley. Hi Brent! Could you explain what RAG is, and why it's important for working with AI and large language models? Brent: Well, RAG stands for Retrieval Augmented Generation. And this is a technique that allows us to enhance the capabilities of large language models, also known as LLMs, and this provides them with relevant context from external knowledge sources. This will allow the LLMs to generate more accurate, informative, and context-aware responses. Real world applications include answering questions, chatbot development, content summarization, and knowledge discovery.  02:35 Lois: Brent, what makes Oracle Database 23ai a good platform for implementing RAG workflows? Brent: Now, there are some key advantages of using Oracle Database 23ai as a RAG platform. These include native functionality, allowing built-in tools and packages specifically designed for RAG pipeline development.  Also, if you are a PL/SQL developer, then this will allow you to develop within a familiar and robust database environment. Also, Oracle has a plethora of security and performance tools. And this ensures enhanced security and optimized performance.  03:18 Nikita: What does a typical RAG workflow look like in Oracle Database 23ai? What are the main steps involved? Brent: Now, the primary workflow steps are going to be to generate vector embeddings from your unstructured data. You do this using vector embedding models. And you can generate those embeddings either inside or outside of the database.  Next, you need to store the vector embeddings, the unstructured data, and the relational business data, and you can store all of that in the Oracle Database. You might want to also create vector indexes that can allow you to run similarity searches over huge vector spaces with really good performance.  Finally, you need to query data with similarity searches. You can use Oracle AI Vector Search native SQL operations to combine similarity with relational searches to retrieve relevant data. And optionally, you can generate a prompt and send it to a large language model for full RAG inference.  04:30 Lois: Can you give us an example of how this workflow operates in practice? Brent: A user's natural language question is encoded as a vector and sent to AI Vector Search. Next, AI vector search finds private content, such as documents, that are stored in the database, and those will match the user's question. The content is then sent to Oracle's GenAI service to help answer the user's question. And then GenAI uses the content plus general knowledge to provide an informed answer back to the user.  05:14 Nikita: What does the overall user experience look like when interacting with RAG? How does Oracle ensure the answers are both accurate and up to date? Brent: In this case, we have a chatbot. This is the interface that we usually use to enable dialogue with the large language model. Now, in order to improve the quality of the answers, we want to search your private business data, and that allows us to pass the most relevant facts back to the LLM.  Next, we want to format the similarity search results as a prompt and context for the large language model. Now, this will allow us to use up to date facts as input to LLMs. And that will minimize the probability of the LLM hallucinating. And those high-quality responses are then returned back to the chatbot.  06:12 Lois: Brent, what does the setup process look like for getting RAG up and running with Oracle AI Vector Search on OCI? Can you take us through the main steps? Brent: First, you will log into OCI. Provide your cloud account name and click Next. There are also interfaces for signing in using a traditional cloud account. And if you're not an Oracle Cloud customer yet, you can also sign up using this page.  Next, after signing in, you will create a compute instance. And you will use Oracle Infrastructure Cloud Console in order to do this. And you will wind up with the user called OPC. You'll notice that you're using SSH in order to connect to your compute instance, and you're running a script in order to set up the Oracle Database.  After that, you will set up the Python environment, again using SSH to connect as an OPC user to your compute instance.  07:22 Do you want to optimize your implementation strategies? Check out the Oracle Fusion Cloud Applications Process Essentials training and certifications for insight into key processes and efficiencies across every phase of your Fusion Cloud Apps journey. Learn more at mylearn.oracle.com.  07:43 Nikita: Welcome back! So far, we've seen how Oracle AI Vector Search powers RAG, letting you surface relevant business knowledge for large language models and enhance their answers. At the heart of all this is the process of transforming unstructured data, like text or documents, into mathematical representations called embeddings.  Lois: Those embeddings are what make meaningful, semantic search possible. But have you wondered how those embeddings actually get created, or what goes on behind the scenes when you choose an embedding model?  Nikita: Up next, we'll take a closer look at embedding models themselves: what they are, how to use them inside Oracle Database 23ai, and how you can experiment with different models to get the results that best fit your business needs.  Lois: We'll walk through importing models, generating embeddings, and even how you can swap out embedding models to compare results. But before we get into the nitty-gritty details, let's quickly recap embedding models, since we've mentioned them in our previous episodes.  08:47 Nikita: Brent, for listeners who might need a refresher, can you explain what embedding models are and why they're so central to AI Vector Search?  Brent: AI Vector Search is based on similarity properties. You can search data by semantic similarity rather than by the actual values. Vector embeddings are created by embedding models to represent the unstructured data. So we have input data.  What we'll want to do is to use an embedding model to generate vector embeddings. And then the vector embeddings would be stored inside of a vector column in a table. We would then compare those vectors to each other using vector distance function.  And we would get the relevant content back based on the number of returns that we describe. For instance, maybe we want to bring back the five closest pieces of data compared to the input data.  There is a new function that allows you to generate vector embeddings that is called the vector embedding function. It allows you to generate vectors within the database.  10:08 Lois: Can you walk us through the practical steps for using embedding models with Oracle AI Vector Search? Brent: In order to create and set up a table, we might use the Python program called create_schema.py. And that will allow us to create a table.  We would ensure that the table was successfully created with the data. As an example, I would create a table called MY_DATA. Next, we would use a sentence transformers embedding model in order to vectorize the table. We can use the Python program, vectorize_table_SentenceTransformers.py. We would then query the MY_DATA table in the Oracle Database to verify that the data has been updated.  And then we would use sentence transformers in order to perform the similarity search. The Python program is called similarity_search_SentenceTransformers.py And what that would do is create the table and then perform a similarity search using the sentence transformers. Now what if you decide that you want to maybe change embedding models? Maybe you want to compare the results by using one particular model as compared to a different model.  So you can change the embedding model. And in order to do that, you would change the embedding model in both of the programs and re-vectorize the table using the vectorize_table_SentenceTransformers.py program. You would then use the new model with different words, possibly, and then compare and review the results, and then choose which one gets you back the data that you're looking for that is most similar.  12:02 Nikita: Well, that's a wrap on this episode. A big thank you, Brent, for sharing your expertise with us.  Lois: If you want to learn more about the topics we discussed today, visit to mylearn.oracle.com and search for the Oracle AI Vector Search Deep Dive course. Until next time, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 12:25 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

Go deeper into Oracle AI Vector Search as hosts Lois Houston and Nikita Abraham, along with Senior Principal APEX & Apps Dev Instructor Brent Dayley, break down how vector indexes, memory requirements, and similarity metrics make fast, powerful semantic search possible in Oracle Database 23ai. Learn about the different types of vector indexes, the VECTOR data type, and how exact and approximate similarity searches work, including best practices for vector management and search performance.   Oracle AI Vector Search Fundamentals:  https://mylearn.oracle.com/ou/course/oracle-ai-vector-search-fundamentals/140188/ Oracle University Learning Community:  https://education.oracle.com/ou-community LinkedIn:  https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Kris-Ann Nansen, and the OU Studio Team for helping us create this episode.   *Please note, this episode was recorded before Oracle AI Database 26ai replaced Oracle Database 23ai. However, all concepts and features discussed remain fully relevant to the latest release.   ----------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Nikita: Welcome to the Oracle University Podcast! I'm Nikita Abraham, Team Lead: Editorial Services with Oracle University, and joining me is Lois Houston, Director of Communications and Adoption Programs with Customer Success Services. Lois: Hi everyone! Thanks for joining us again as we continue our exploration into the exciting world of Oracle AI Vector Search. In today's episode, we're taking you inside the technology powering vector search in Oracle Database 23ai. We'll break down core concepts like vector indices, how vectors are stored and managed, and how you can use similarity metrics to unlock new possibilities with your data.  01:09 Nikita: We'll also dig into best practices for handling vectors, everything from memory requirements and table creation to the nuts and bolts of running both exact and approximate similarity searches. Back with us today is Senior Principal APEX & Apps Dev Instructor Brent Dayley. Hi Brent! What exactly are vector indexes? Brent: Now, vector indexes are specialized indexing data structures that can make your queries more efficient against your vectors. They use techniques such as clustering, and partitioning, and neighbor graphs. Now, they greatly reduce the search space, which means that your queries happen quicker. They're also extremely efficient. They do require that you enable the vector pool in the SGA.  02:06 Lois: And are there different types of vector indices supported? Brent: So, Oracle AI Vector Search supports two types of indexes, in-memory neighbor graph vector index. HNSW is the only type of in-memory neighbor graph vector index that is supported. These are very efficient indexes for vector approximate similarity search. HNSW graphs are structured using principles from small world networks along with layered hierarchical organization.  And neighbor partition vector index. Neighbor partition vector index, inverted file flat index, is the only type of neighbor partition index supported. It is a partition-based index which balances high search quality with reasonable speed.  In order for you to be able to use vector indexes, you do need to enable the vector pool area. And in order to do that, what you need to do is set the vector memory size parameter.  You can set it at the container database level. And the PDB inherits it from the CDB. Now bear in mind that the database does have to be balanced when you set the vector pool.  Other considerations, vector indexes are stored in this pool, and vector metadata is also stored here. You do need to restart the database. So large vector indexes do need lots of RAM, and RAM constrains the vector index size. You should use IVF indexes when there is not enough RAM. IVF index is used both the buffer cache as well as disk.  04:05 Lois: Now, memory is definitely a key consideration, right? Can you share more about the memory requirements and considerations for working with vectors? Brent: So to remind you, a vector is a numerical representation of text, images, audio, or video that encodes the features or semantic meaning of the data, instead of the actual contents, such as the words or pixels of an image. So the vector is a list of numerical values known as dimensions with a specified format.  Now, Oracle does support the int8 format, the float32 format, and the float64 format. Depending on the format depends on the number of bytes. For instance, int8 is one byte, float32 is four bytes.  04:56 Nikita: And how do you calculate the size of a vector? Brent: Now, that's going to depend upon the embedding model that you use to create those embeddings. Oracle AI Vector Search supports vectors with up to 65,535 dimensions. As a reminder, vectors are stored in tables and table data is stored on disk.  05:19 Nikita: Let's talk about working with vectors in tables. Can you walk us through how Oracle Database 23ai supports creating tables with vector columns? Brent: Now, Oracle Database 23ai does have a new VECTOR data type. The new data type was created in order to support vector search.  The definition can include the number of dimensions and can include the format. Bear in mind that either one of those are optional when you define your column. The possible dimension formats are Int, float 32, and float 64. Float 32 and float 64 are IEEE standards, and Oracle Database will automatically cast the value if needed.  Let's take a look at some of the declaration examples. Now, if we just do a vector type, then the vectors can have any arbitrary number of dimensions and formats. If we describe the vector type as vector * , *, then that means that vectors can have an arbitrary number of dimensions and formats. Vector and vector * , * are equivalent. Vector with the number of dimensions specified, followed by a comma, and then an asterisk, is equivalent to vector number of dimensions.  Vectors must all have the specified number of dimensions, or an error will be thrown. Every vector will have its dimension stored without format modification. And if we do vector asterisk common dimension element format, what that means is that vectors can have an arbitrary number of dimensions, but their format will be up-converted or down-converted to the specified dimension element format, either INT8, float 32, or float 64.  07:25 Lois: Are there any operations or configurations that are prohibited with the VECTOR data type? Brent: You cannot define vector columns in or as external tables, index-organized tables, neither as the primary key nor as non-key columns, in clusters or cluster tables, global temporary tables, subpartitioning key, primary key, foreign key, or unique constraint.  Additionally, you cannot define vector columns in or as check constraints, default value, modify column, manually segment space manage tablespaces. Only the SYS user can create vectors as basic files in manually segment space manage tablespaces. For continuous query notification queries, or for non-vector indexes such as B-tree, bitmap, reverse key, text, or spatial indexes. Also, bear in mind that Oracle does not support distinct, count distinct, order by, group by, join condition, or comparison operators such as less than, greater than, or equal to with vector columns.  08:46 Have you already nailed the basics of AI? Then it's time to level up. Explore advanced AI with our OCI AI Professional courses and certifications covering Data Science, Generative AI, and AI Vector Search. Are you ready to take the next step? Head over to mylearn.oracle.com and learn more! 09:12 Nikita: Welcome back!! Now, let's shift gears and discuss vector search itself. How does one create a vector "on the fly" for testing or learning purposes? Brent: Now, the vector constructor is a function that allows us to create vectors without having to store those in a column in a table. These are useful for learning purposes. You use these usually with a smaller number of dimensions. Bear in mind that most embedding models can contain thousands of different dimensions. You get to specify the vector values, and they usually represent two-dimensional like xy coordinates. The dimensions are optional, and the format is optional as well.  10:01 Lois: Once we have vectors, how do we compare them or measure how "close" they are to each other? Brent: Now vector distance uses the function VECTOR_DISTANCE as the main function. This allows you to calculate distances between two vectors and therefore takes two vectors as parameters. Optionally, you can specify a metric. If you do not specify a metric, then the default metric, COSINE, would be used.  You can optionally use other shorthand functions, too. These include L1 distance, L2 distance, cosine distance, and inner product. All of these functions also take two vectors as input and return the distance between them. Now the VECTOR_DISTANCE function can be used to perform a similarity search. And bear in mind these caveats. If a similarity search query does not specify a distance metric, then the default cosine metric will be used for both exact and approximate searches.  If a similarity search does specify a distance metric in the VECTOR_DISTANCE function, then an exact search with that distance metric is used if it conflicts with the distance metric specified in a vector index. If the two distance metrics are the same, then this will be used for both exact as well as approximate searches.  11:44 Nikita: Can you break down the distance metrics we use in Oracle AI Vector Search? Brent: We have Euclidean and Euclidean squared distances. We have cosine similarity, dot product similarity, Manhattan distance, and Hamming similarity. Now let's take a closer look at the first of these metrics, Euclidean and Euclidean squared distances. This gives us the straight-line distance between two vectors. It does use the Pythagorean theorem. And notice that it is sensitive to both the vector size as well as the direction.  With Euclidean distances, comparing squared distances is equivalent to comparing distances. So when ordering is more important than the distance values themselves, the squared Euclidean distance is very useful as it is faster to calculate than the Euclidean distance, which avoids the square root calculation.  12:54 Lois: Cosine similarity is a term I hear often. How does it work exactly? Brent: It is one of the most widely used similarity metrics, especially in natural language processing. The smaller the angle means they are more similar. While cosine distance measures how different two vectors are, cosine similarity measures how similar two vectors are.  13:20 Nikita: Dot product similarity comes up a lot, too. What's its role? Brent: Dot product similarity allows us to multiply the size of each vector by the cosine of their angle. The corresponding geometrical interpretation of this definition is equivalent to multiplying the size of one of the vectors by the size of the projection of the second vector onto the first one or vice versa. Larger means that they are more similar. Smaller means that they are less similar.  13:58 Lois: How does Manhattan distance differ from other metrics, and when is it used? Brent: This is useful for describing uniform grids. You can imagine yourself walking from point A to point B in a city such as Manhattan. Now, since there are buildings in the way, maybe we need to walk down one street and then turn and walk down the next street in order to get to our result. As you can imagine, this metric is most useful for vectors describing objects on a uniform grid such as city blocks, power grids, or perhaps a chessboard. Now these are faster than the Euclidean metric.  14:48 Nikita: And how is Hamming similarity different from the others? Brent: This describes where vector dimensions differ. They are binary vectors, and it tells us the number of bits that require change to match. It compares the position of each bit in the sequence. Now, these are usually used in order to detect network errors.  15:17 Nikita: Now that we've covered the foundations, how do we actually search for the "closest" vectors in our data? What's an exact similarity search? Brent: An exact similarity search allows you to calculate the query vector distance to all other vectors. This is also called a flat search or an exact search. This does give you the most accurate results. It gives you perfect search quality. However, you might have potentially long search times.  Now, this comparison is done using a particular distance metric. But what is important is the result set of your top closest vectors not the distance between them.  Let's take a look at one of the metrics. This one is Euclidean. The Euclidean similarity search retrieves the top k nearest vectors in your space relative to the Euclidean distance metric and a query vector.   Now let's take a look at Euclidean squared distance. In the case of Euclidean distances, comparing squared distances is equivalent to comparing distances. So when ordering is more important than the distance values themselves, the Euclidean squared distance is very useful, as it is faster to calculate than the Euclidean distance, avoiding the square-root calculation.  16:46 Lois: How does that compare to approximate searches, which are usually faster, using vector indices? Brent: Approximate similarity search is a type of vector search that uses vector indexes. In order to use vector indexes, you have to ensure that you have enabled the vector pool in the SGA. For a vector search to be useful, it needs to be fast and accurate.  These types of searches can be more efficient. However, the trade off is that they can be less accurate. Now, approximate searches use vector indexes, and there are many types of approximate searches that you can perform using vector indexes. Vector indexes can be less accurate, but they can consume less resources. Because 100% accuracy cannot be guaranteed by the heuristics, vector index searches use target accuracy.  Internally, the algorithms used for both the index creation and index search are doing their best to be as accurate as possible. You do have the option to influence those algorithms by specifying a target accuracy.  Let's take a look at vector indexes a little closer. We have two types of vector indexes. We have HNSW indexes, which stand for Hierarchical Navigable Small World index, and we have Inverted File Flat index, or IVF. 18:23 Nikita: And for more complex requirements, how does Oracle handle multi-vector similarity search? Brent: Multi-vector similarity search is usually used for multi-document search. The documents would be split into chunks. The chunks would be embedded individually into vectors. It does use the concept of groupings called partitions. A multi-vector search consists of retrieving the top K vector matches, using the partitions based on the document's characteristics.  The ability to score documents based on the similarity of their chunks to a query vector being searched is facilitated in SQL using the partitioned row-limiting clause.  Now, the partition row-limiting clause extension is a generic extension of the SQL language. It does not have to apply to just vector searches. Multi-vector search with the partitioning row limit clause does not use vector indexes. 19:32 Lois: We covered quite a lot today! Thanks for that, Brent! If you want to learn more about the topics we discussed today, go to mylearn.oracle.com and search for the Oracle AI Vector Search Fundamentals course. Until next time, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 19:52 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

Explore Oracle AI Vector Search and learn how to find data by meaning, not just keywords, using powerful vector embeddings within Oracle Database 23ai. In this episode, hosts Lois Houston and Nikita Abraham, along with Senior Principal APEX & Apps Dev Instructor Brent Dayley, break down how similarity search works, the new VECTOR data type, and practical steps for implementing secure, AI-powered search across both structured and unstructured data.   Oracle AI Vector Search Fundamentals: https://mylearn.oracle.com/ou/course/oracle-ai-vector-search-fundamentals/140188/ Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Kris-Ann Nansen, and the OU Studio Team for helping us create this episode.   ---------------------------------------------------- Episode Transcript:   00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Lois: Hello and welcome to the Oracle University Podcast! I'm Lois Houston, Director of Communications and Adoption Programs with Customer Success Services, and with me is Nikita Abraham, Team Lead: Editorial Services with Oracle University. Nikita: Hi everyone! Today, we're beginning a brand-new season, this time on Oracle AI Vector Search. Whether you're new to vector searches or you've already been experimenting with AI and data, this episode will help you understand why Oracle's approach is such a game-changer. Lois: To make sure we're all starting from the same place, here's a quick overview. Oracle AI Vector Search lets you go beyond traditional database searches. Not only can you find data based on specific attribute values or keywords, but you can also search by meaning, using the semantics of your data, which opens up a whole new world of possibilities. 01:20 Nikita: That's right, Lois. And guiding us through this episode is Senior Principal APEX & Apps Dev Instructor Brent Dayley. Hi Brent! What's unique about Oracle's approach to vector search? What are the big benefits? Brent: Now one of the biggest benefits of Oracle AI Vector Search is that semantic search on unstructured data can be combined with relational search on business data, all in one single system. This is very powerful, and also a lot more effective because you don't need to add a specialized vector database. And this eliminates the pain of data fragmentation between multiple systems.  It also supports Retrieval Augmented Generation, also known as RAG. Now this is a breakthrough generative AI technique that combines large language models and private business data. And this allows you to deliver responses to natural language questions. RAG provides higher accuracy and avoids having to expose private data by including it in the large language model training data.  02:41 Lois: OK, and can you explain what the new VECTOR data type is? Brent: So, this data type was introduced in Oracle Database 23ai. And it allows you to store vector embeddings alongside other business data.  Now, the vector data type allows a foundation to store vector embeddings. This allows you to store your business data in the database alongside your unstructured data, and allows you to use those in your queries. So it allows you to apply semantic queries on business data.  03:24 Lois: For many of our listeners, "vector embeddings" might be a new term. Can you explain what vector embeddings are? Brent: Vector embeddings are mathematical representations of data points. They assign mathematical representations based on meaning and context of your unstructured data.  You have to generate vector embeddings from your unstructured data either outside or within the Oracle Database. In order to get vector embeddings, you can either use ONNX embedding machine learning models or access third-party REST APIs.  Embeddings can be used to represent almost any type of data, including text, audio, or visual such as pictures. And they are used in proximity searches.  04:19 Nikita: Now, searching with these embeddings isn't about looking for exact matches like traditional search, right? This is more about meaning and similarity, even when the words or images differ? Brent, how does similarity search work in this context? Brent: So vector data is usually unevenly distributed and clustered. Vector data tends to be unevenly distributed and clustered into groups that are semantically related. Doing a similarity search based on a given query vector is equivalent to retrieving the k nearest vectors to your query vector in your vector space.  What this means is that basically you need to find an ordered list of vectors by ranking them, where the first row is the closest or most similar vector to the query vector. The second row in the list would be the second closest vector to the query vector, and so on, depending on your data set. What we need to do is to find the relative order of distances. And that's really what matters rather than the actual distance.  Now, similarity searches tend to get data from one or more clusters, depending on the value of the query vector and the fetch size. Approximate searches using vector indexes can limit the searches to specific clusters. Exact searches visit vectors across all clusters.  05:51 Lois: Let's talk about how we actually convert information into these vectors. There are models behind the scenes, right? Kind of like translators between words, images, and numbers. Brent, what embedding models does Oracle support, and how do they handle different data types? Brent: Vector embedding models allow you to assign meaning to what a word, or a sentence, or the pixels in an image, or perhaps audio. What that actually means? It allows you to quantify features or dimensions.  Most modern vector embeddings use a transformer model. Bear in mind that convolutional neural networks can also be used. Depending on the type of your data, you can use different pretrained open-source models to create vector embeddings. As an example, for textual data, sentence transformers can transform words, sentences, or paragraphs into vector embeddings.  For visual data, you can use residual network, also known as ResNet, to generate vector embeddings. You can also use visual spectrogram representation for audio data. And that allows us to use the audio data to fall back into the visual data case. Now, these can also be based on your own data set. Each model also determines the number of dimensions for your vectors.  As an example, Cohere's embedding model, embed English version 3.0, has 1,024 dimensions. Open AI's embedding model, text-embedding-3-large, has 3,072 dimensions.  07:45 Nikita: For organizations ready to put this into practice, there's the question of how to get the models up and running inside Oracle Database. Can you walk us through how these models are brought into Oracle Database? Brent: Although you can generate vector embeddings outside the Oracle Database using pre-trained open-source embeddings or your own embedding models, you also have the option of doing those within the Oracle Database. In order to use those within the Oracle Database, you need to use models that are compatible with the Open Neural Network Exchange Standard, or ONNX, also known as onn-ex.  Oracle Database implements an ONNX runtime directly within the database, and this is going to allow you to generate vector embeddings directly inside the Oracle Database using SQL.  08:41 AI is transforming every industry. So, it's no wonder that AI skills are the most sought-after by employers. If you're ready to dive into AI, check out the OCI AI Foundations training and certification that's available for free! It's the perfect starting point to build your AI knowledge. Head over to mylearn.oracle.com to kickstart your AI journey today! 09:06 Nikita: Welcome back! Let's make this practical. Imagine I'm setting this up for the first time. What are the big steps? Can you walk us through the end-to-end workflow using Oracle AI Vector Search? Brent: Generate vector embeddings from your data, either outside the database or within the database. Now, embeddings are a mathematical representation of what your data meaning is. So, what does this long sentence mean, for instance? What are the main keywords out of it? You can also generate embeddings not only on your typical string type of data, but you can also generate embeddings on other types of data, such as pictures or perhaps maybe audio wavelengths.  Maybe we want to convert text strings to embeddings or convert files into text. And then from text, maybe we can chunk that up into smaller chunks and then generate embeddings on those chunks. Maybe we want to convert files to embeddings, or maybe we want to use embeddings for end-to-end search.  Now you have to generate vector embeddings from your unstructured data, as we mentioned, either outside or within the Oracle Database. You can either use the ONNX embedding machine learning models or you can access third-party REST APIs.  You can import pretrained models in ONNX format for vector generation within the database. You can download pretrained embedding machine learning models, convert them into the ONNX format if they are not already in that format. Then you can import those models into the Oracle Database and generate vector embeddings from your data within the database.  Oracle also allows you to convert pre-trained models to the ONNX format using Oracle machine learning for Python. This enables the use of text transformers from different companies.  11:36 Nikita: Once those embeddings are generated, what's the next step?  Brent: Store vector embeddings. So you can create one or more columns of the vector data type in your standard relational data tables. You can also store those in secondary tables that are related to the primary tables using primary key foreign key relationships.  You can store vector embeddings on structured data and relational business data in the Oracle Database. You do store the resulting vector embeddings and associated unstructured data with your relational business data inside the Oracle Database.  12:17 Lois: And when do vector indexes come into play?  Brent: Now you may want to create vector indexes in the event that you have huge vector spaces. This is an optional step, but this is beneficial for running similarity searches over those huge vector spaces.  12:38 Nikita: Now, once all of that is in place, how do users perform similarity searches?  Brent: So once you have generated the vector embeddings and stored those vector embeddings and possibly created the vector indexes, you can then query your data with similarity searches. This allows for native SQL operations and allows you to combine similarity searches with relational searches in order to retrieve relevant data.  So let's take a look at the combined complete workflow. Step number one, generate the vector embeddings from your unstructured data. Step number two, store the vector embeddings. Step number three, create vector indexes. And step number four, combine similarity and keyword searches.  Now there is another optional step. You could generate a prompt and send it to a large language model for a full RAG inference. You can use the similarity search results to generate a prompt and send it to your generative large language model in order to complete your RAG pipeline.  14:07 Lois: Thanks for that detailed walk-through, Brent. To sum up, today we introduced Oracle AI Vector Search, discussed its core concepts, data types, embedding models, and the complete workflow you'll use to get real value out of your business data, securely and efficiently.  Nikita: If you want to learn more about the topics we discussed today, go to mylearn.oracle.com and search for the Oracle AI Vector Search Fundamentals course. And if you're feeling inspired to try this out for yourself, don't forget to check out the Oracle Database 23ai SQL Workshop for hands-on training. Until next time, this is Nikita Abraham… Lois: And Lois Houston, signing off! 14:49 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.  

Running Oracle Database@AWS is most effective when you have full visibility and control over your environment.   In this episode, hosts Lois Houston and Nikita Abraham are joined by Rashmi Panda, who explains how to monitor performance, track key metrics, and catch issues before they become problems. Later, Samvit Mishra shares key best practices for securing, optimizing, and maintaining a resilient Oracle Database@AWS deployment.   Oracle Database@AWS Architect Professional: https://mylearn.oracle.com/ou/course/oracle-databaseaws-architect-professional/155574 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ------------------------------------------------------ Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Nikita: Welcome to the Oracle University Podcast! I'm Nikita Abraham, Team Lead: Editorial Services with Oracle University, and with me is Lois Houston, Director of Communications and Adoption with Customer Success Services  Lois: Hello again! Last week's discussion was all about how Oracle Database@AWS stays secure and available. Today, we're joined by two experts from Oracle University. First, we'll hear from Rashmi Panda, Senior Principal Database Instructor, who will tell you how to monitor and log Oracle Database@AWS so your environment stays healthy and reliable. Nikita: And then we're bringing in Samvit Mishra, Senior Manager, CSS OU Cloud Delivery, who will break down the best practices that help you secure and strengthen your Oracle Database@AWS deployment. Let's start with you, Rashmi. Is there a service that allows you to monitor the different AWS resources in real time? Rashmi: Amazon CloudWatch is the cloud-native AWS monitoring service that can monitor the different AWS resources in real time. It allows you to collect the resource metrics and create customized dashboards, and even take action when certain criteria is met. Integration of Oracle Database@AWS with Amazon CloudWatch enables monitoring the metrics of the different database resources that are provisioned in Oracle Database@AWS. Amazon CloudWatch collects raw data and processes it to produce near real-time metrics data. Metrics collected for the resources are retained for 15 months. This facilitates analyzing the historical data to understand and compare the performance, trends, and utilization of the database service resources at different time intervals. You can set up alarms that continuously monitor the resource metrics for breach of user-defined thresholds and configure alert notification or take automated action in response to that metric threshold being reached. 02:19 Lois: What monitoring features stand out the most in Amazon CloudWatch? Rashmi: With Amazon CloudWatch, you can monitor Exadata VM Cluster, container database, and Autonomous database resources in Oracle Database@AWS. Oracle Database@AWS reports metrics data specific to the resource in AWS/ODB namespace of Amazon CloudWatch. Metrics can be collected only when the database resource is an available state in Oracle Database@AWS. Each of the resource types have their own metrics defined in AWS/ODB namespace, for which the metrics data get collected.  02:54 Nikita: Rashmi, can you take us through a few metrics? Rashmi: At Exadata database VM Cluster, there is CPU utilization, memory utilization, swap space storage file system utilization metric. Then there is load average on the server, what is the node status, and the number of allocated CPUs, et cetera. Then for container database, there is CPU utilization, storage utilization, block changes, parse count, execute count, user calls, which are important elements that can provide metrics data on database load. And for Autonomous Database metrics data include DB time, CPU utilization, logins, IOPS and IO throughput, RedoSize, parse, execute, transaction count, and few others. 03:32 Nikita: Once you've collected these metrics and analyzed database performance, what tools or services can you use to automate responses or handle specific events in your Oracle Database@AWS environment? Rashmi: Then there is Amazon EventBridge, which can monitor events from AWS services and respond automatically with certain actions that may be defined. You can monitor events from Oracle Database@AWS in EventBridge, which sends events data continuously to EventBridge at real time. Eventbridge forwards these events data to target AWS Lambda and Amazon Simple Notification Service to perform any actions on occurrence of certain events. Oracle Database@AWS events are structured messages that indicate changes in the life cycle of the database service resource. Eventbridge can filter events based on your defined rules, process them, and deliver to one or more targets. Event Bus is the router that receives the events, optionally transform them, and then delivers the events to the targets. Events from Oracle Database@AWS can be generated by two means: they can be generated from Oracle Database@AWS in AWS, and they can also be generated directly from OCI and received by EventBridge in AWS. You can monitor Exadata Database and Autonomous Database resource events. Ensure that the Exadata infrastructure status is an available state. You can configure how the events are handled for these resources. You can define rules in EventBridge to filter the events of interest and the target, who is going to receive and process those events. You can filter events based on a pattern depending on the event type, and apply this pattern using Amazon EventBridge put-rule API, with the default event bus to route only those matching events to targets. 05:13 Lois: And what about events that AWS itself generates? Rashmi: Events that are generated in AWS for the Oracle Database@AWS resources are delivered to the default event bus of your AWS account. These events that are generated in AWS for Oracle Database@AWS resources include lifecycle changes of the ODB network. The different network events are successful creation or failure of the creation of the ODB network, and successful deletion or failure in deletion of the ODB network. When you subscribe to Oracle Database@AWS, then an event bus with prefix aws.partner/odb is created in your AWS account. All events generated in OCI for the Oracle Database@AWS resources are then received in this event bus. When you are creating filter pattern using Amazon EventBridge put-rule API, you must set the event bus name to this event bus. Make sure you do not delete this event bus. Events generated in OCI and received into event bus are extensive. They include events of Oracle Exadata infrastructure, VM Cluster, container, and pluggable databases. 06:14 Lois: If you want to look back at what's happened in your environment, like who made the changes or accessed resources, what's the best AWS service for logging and auditing all that activity? Rashmi: Amazon CloudTrail is a logging service in AWS that records the different actions taken by a user or roles, or an AWS service. Oracle Database@AWS is integrated with Amazon Cloud Trail. This enables logging of all the different events on Oracle Database@AWS resources.  Amazon Cloud Trail captures all the API calls to Oracle Database@AWS as events. These API calls include calls from the Oracle Database@AWS console, and code calls to Oracle Database@AWS API operations. These log files are delivered to Amazon S3 bucket that you specify. These logs determine the identity of the caller who made the call request to Oracle Database@AWS, their IP from which the call originated, the time of the call, and some additional details.  CloudTrail event history stores immutable record of the past 90 days of management events in an AWS region. You can view, search, and download these records from CloudTrail Event History. You can access CloudTrail when you create an AWS account that automatically gives you the access to CloudTrail. Event history. If you would like to retain the logs for a longer period of time beyond 90 days, you can create CloudTrail trails or CloudTrail Lake event data store.  Management events in AWS provide information about management operations that are performed on the resources in your AWS account. Management operations are also called control plane operations. Thus, the control plane operations in Oracle Database@AWS are logged as management events in CloudTrail logs.  07:59 Are you a MyLearn subscriber? If so, you're automatically a member of the Oracle University Learning Community! Join millions of learners, attend exclusive live events, and connect directly with Oracle subject matter experts. Enjoy the latest news, join challenges, and share your ideas. Don't miss out! Become an active member today by visiting mylearn.oracle.com. 08:25 Nikita: Welcome back! Samvit, let's talk best practices. What should teams keep in mind when they're setting up and securing their Oracle Database@AWS environment?  Samvit: Use IAM roles and policies with least privilege to manage Oracle Database@AWS resources. This ensures only authorized users can provision or modify DB resources, reducing the risk of accidental or malicious changes.  Oracle Data Safe monitors database activity, user risk, and sensitive data, while AWS CloudTrail records all AWS API calls. Together, they give full visibility across the database and cloud layers. Autonomous Database supports Oracle Database Vault for enforcing separation of duties. Exadata Database Service can integrate with Audit Vault and Database Firewall to prevent privileged users from bypassing security controls. Enable multifactor authentication for AWS IAM users managing Oracle Database@AWS. This adds a strong second layer of protection against stolen credentials.  Always deploy your Oracle Database@AWS in private subnets without public IPs. Use AWS security groups and NACLs to strictly limit inbound and outbound traffic, allowing access only from trusted applications. Exadata Database Service supports integration with Oracle Vault for key lifecycle management. And in case of Autonomous Database, the transparent data encryption keys are automatically managed. But you can bring your own keys with OCI Vault. Key rotation ensures compliance and reduces risk of key compromise. Oracle Database@AWS enforces encrypted connections by default. Ensure clients connect with TLS 1.2 or 1.3 to protect data in transit from interception or tampering.  Use Oracle Data Safe's user assessment features to detect dormant users or excessive privileges. Disable unused accounts and rightsize permissions to reduce insider threats and security gap. Export database audit logs to Oracle Data Safe Audit Vault or AWS S3 with object lock for immutability. This prevents lock tampering and ensures audit evidence is preserved for compliance.  11:25 Lois: OK, that covers security. Do you have any tips for making sure your Oracle Database@AWS setup is reliable and resilient? Samvit: Start with clear recovery objectives. Define how much downtime and data loss each workload can tolerate. These targets drive your HADR architecture and backup strategy.  Implement business continuity measures to deliver maximum uptime for your databases. As a best practice, you must configure disaster recovery environment for your critical databases so that, in the event of any disaster affecting the primary database, applications can be immediately failed over to the DR environment, ensuring least application downtime and zero or minimal data loss. With Oracle Database@AWS, you can automate the creation and management of DR environment for your database services using different deployment capabilities. You can opt to configure either cross-availability zone DR in the same region or configure cross-region DR. Since cross-availability zone can only provide site failure protection, you must also configure a cross-region DR to protect against regional failure. A DR plan is only effective if tested. Regular failover and switchover drills validate that people, processes, and systems can recover as designed.  For Exadata Database, Autonomous Recovery Service provides automated backup validation, recovery guarantees, and protection against accidental data loss or corruption.  Oracle-managed backups are fully managed by OCI. When you create your Oracle Exadata Database, you can enable automatic backups by choosing Enable Automatic Backups in the OCI Console. When you do that, you can select Amazon S3 or OCI Object Storage or Autonomous Recovery Service as the backup destination. Don't just take backups. You also need to test them. Regularly restore backups into non-production environment to validate integrity and recovery time.  Plan beyond just the database. Map application and middleware dependencies to ensure end-to-end business resilience. A database failover is useless if dependent apps can't reconnect. 14:09 Nikita: Another area of interest is performance and cost. What practices help teams balance the two? Samvit: Autonomous Database automatically scales CPU and storage as workloads grow. This ensures performance during peaks while avoiding overprovisioning. So you should enable ADB auto-scaling.  Monitor CPU, memory, and IO metrics with AWS CloudWatch to rightsize your compute. Scale up or down based on actual utilization instead of static provisioning. Autonomous databases continuously evaluate and creates indexes automatically. This improves query performance without requiring manual tuning.  Use connection pooling in your applications to optimize database connections. Minimizing round-trip reduces latency and improves throughput. Apply AWS tags to database and related resources for cost allocation and chargeback. Tagging also helps with governance and cost visibility.  Choose between bring your own license and license-included models for Oracle Database@AWS. The right model depends on your existing license portfolio and cost strategy. Not all workloads need long backup retention. Adjust retention policies based on business needs to balance compliance with storage costs.  Exadata Database supports Oracle multitenant with pluggable databases. Consolidating databases reduces infrastructure footprint and licensing costs. Performance tuning isn't just technical. Align metrics with business KPIs. correlating DB performance to user experience and revenue impact helps prioritize optimizations.  16:20 Lois: Before we wrap up, Samvit, let's look at operational efficiency. What advice do you have for making day-to-day operations more efficient? Samvit: Use infrastructure as code tools like Terraform or AWS CloudFormation to automate provisioning. This ensures consistent, repeatable deployments with minimal manual errors.  For Autonomous Database, enable auto-start/stop to optimize costs by running databases only when needed. This is ideal for dev test or seasonal workloads. Exadata Database Service provides fleet maintenance to patch multiple systems consistently. This reduces downtime and simplifies lifecycle management.  Integrate AWS CloudWatch for performance monitoring and EventBridge for event-driven automation. This helps detect issues early and trigger automated workflows. Oracle Data Safe provides ready-to-use audit and compliance reports. Use these to streamline governance and reduce the effort of manual compliance tracking.  For Autonomous databases, Performance Hub simplifies monitoring while Exadata users benefit from AWR and ASH reports. Together, they give deep insights into performance trends. Automated tagging policies and change management workflows help maintain governance. They ensure resources are tracked properly and changes are auditable.  Monitor storage consumption and growth patterns using AWS CloudWatch and the ADB Console. Proactive tracking helps avoid capacity issues and unexpected costs. Send CloudTrail logs into EventBridge to trigger automated incident responses. This shortens response time and builds operational resilience.  18:36 Nikita: Samvit and Rashmi, thanks for spending time with us today. Your insights always help bring the bigger picture into focus. Lois: They definitely do. And if you'd like to go deeper into everything we covered, head over to mylearn.oracle.com and look up the Oracle Database@AWS Architect Professional course. Until next time, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 19:03 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

When your business runs on data, even a few seconds of downtime can hurt. That's why this episode focuses on what keeps Oracle Database@AWS running when real-world problems strike.   Hosts Lois Houston and Nikita Abraham are joined by Senior Principal Database Instructor Rashmi Panda, who takes us inside the systems that keep databases resilient through failures, maintenance, and growing workloads.   Oracle Database@AWS Architect Professional: https://mylearn.oracle.com/ou/course/oracle-databaseaws-architect-professional/155574 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. --------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Lois: Hello and welcome to the Oracle University Podcast! I'm Lois Houston, Director of Communications and Adoption with Customer Success Services, and with me is Nikita Abraham, Team Lead: Editorial Services with Oracle University. Nikita: Hi everyone! In our last episode, we explored the security and migration strengths of Oracle Database@AWS. Today, we're joined once again by Senior Principal Database Instructor Rashmi Panda to look at how the platform keeps your database available and resilient behind the scenes. 01:00 Lois: It's really great to have you with us, Rashmi. As many of you may know, keeping critical business applications running smoothly is essential for success. And that's why it's so important to have deployments that are highly resilient to unexpected failures, whether those failures are hardware-, software-, or network-related. With that in mind, Rashmi, could you tell us about the Oracle technologies that help keep the database available when those kinds of issues occur? Rashmi: Databases deployed in Oracle Database@AWS are built on Oracle's Foundational High Availability Architecture. Oracle Real Application Cluster or Oracle RAC is an Active-Active architecture where multiple database instances are concurrently running on separate servers, all accessing the same physical database stored in a shared storage to simultaneously process various application workloads. Even though each instance runs on a separate server, they collectively appear as a single unified database to the application. As the workload grows and demands additional computing capacity, then new nodes can be added to the cluster to spin up new database instances to support additional computing requirements. This enables you to scale out your database deployments without having to bring down your application and eliminates the need to replace existing servers with high-capacity ones, offering a more cost-effective solution. 02:19 Nikita: That's really interesting, Rashmi. It sounds like Oracle RAC offers both scalability and resilience for mission-critical applications. But of course, even the most robust systems require regular maintenance to keep them running at their best. So, how does planned maintenance affect performance?  Rashmi: Maintenance on databases can take a toll on your application uptime. Database maintenance activities typically include applying of database patches or performing updates. Along with the database updates, there may also be updates to the host operating system. These operations often demand significant downtime for the database, which consequently leads to slightly higher application downtime. Oracle Real Application Cluster provides rolling patching and rolling upgrades feature, enabling patching and upgrades in a rolling fashion without bringing down the entire cluster that significantly reduces the application downtime.  03:10 Lois: And what happens when there's a hardware failure? How does Oracle keep things running smoothly in that situation? Rashmi: In the event of an instance or a hardware failure, Oracle RAC ensures automatic service failover. This means that if one of the instance or node in the cluster goes down, the system transparently failovers the service to an available instance in the cluster, ensuring minimal disruption to your application. This feature enhances the overall availability and resilience of your database.  03:39 Lois: That sounds like a powerful way to handle unexpected issues. But for businesses that need even greater resilience and can't afford any downtime, are there other Oracle solutions designed to address those needs? Rashmi: Oracle Exadata is the maximum availability architecture database platform for Oracle databases. Core design principle of Oracle Exadata is built around redundancy, consisting of networking, power supplies, database, and storage servers and their components. This robust architecture ensures protection against the failure of any individual component, effectively guaranteeing continuous database availability. The scale out architecture of Oracle Exadata allows you to start your deployment with two database servers and three storage servers, having different number of CPU cores and different sizes and types of storage to meet the current business needs. 04:26 Lois: And if a business suddenly finds demand growing, how does the system handle that? Is it able to keep up with increased needs without disruptions? Rashmi: As the demand increases, the system can be easily expanded by adding more servers, ensuring that the performance and capacity grow with your business requirements. Exadata Database Service deployment in Oracle Database@AWS leverages this foundational technologies to provide high availability of database system. This is achieved by provisioning databases using Oracle Real Application Cluster, hosted on the redundant infrastructure provided by Oracle Exadata Infrastructure Platform. This deployment architecture provides the ability to scale compute and storage to growing resource demands without the need for downtime. You can scale up the number of enabled CPUs symmetrically in each node of the cluster when there is a need for higher processing power or you can scale out the infrastructure by adding more database and storage servers up to the Exadata Infrastructure model limit, which in itself is huge enough to support any large workloads. The Exadata Database Service running on Oracle RAC instances enables any maintenance on individual nodes or patching of the database to be performed with zero or negligible downtime. The rolling feature allows patching one instance at a time, while services seamlessly failover to the available instance, ensuring that the application experienced little to no disruption during maintenance. Oracle RAC, coupled with Oracle Exadata redundant infrastructure, protects the Database Service from any single point of failure. This fault-tolerant architecture features redundant networking and mirrored disk, enabling automatic failover in the event of a component failure. Additionally, if any node in the cluster fails, there is zero or negligible disruption to the dependent applications. 06:09 Nikita: That's really impressive, having such strong protection against failures and so little disruption, even during scaling and maintenance. But let's say a company wants those high-availability benefits in a fully managed environment, so they don't have to worry about maintaining the infrastructure themselves. Is there an option for that? Rashmi: Similar to Oracle Exadata Database Service, Oracle Autonomous Database Service on dedicated infrastructure in Oracle Database@AWS also offers the same feature, with the key difference being that it's a fully managed service. This means customers have zero responsibility for maintaining and managing the Database Service. This again, uses the same Oracle RAC technology and Oracle Exadata infrastructure to host the Database Service, where most of the activities of the database are fully automated, providing you a highly available database with extreme performance capability. It provides an elastic database deployment platform that can scale up storage and CPU online or can be enabled to autoscale storage and compute. Maintenance activities on the database like database updates are performed automatically without customer intervention and without the need of downtime, ensuring seamless operation of applications. 07:20 Lois: Can we shift gears a bit, Rashmi? Let's talk about protecting data and recovering from the unexpected. What Oracle technologies help guard against data loss and support disaster recovery for databases? Rashmi: Oracle Database Autonomous Recovery Service is a centralized backup management solution for Oracle Database services in Oracle Cloud Infrastructure. It automatically takes backup of your Oracle databases and securely stores them in the cloud. It ensures seamless data protection and rapid recovery for your database. It is a fully managed solution that eliminates the need for any manual database backup management, freeing you from associated overhead. It implements an incremental forever backup strategy, a highly efficient approach where only the changes since the last backup are identified and backed up. This approach drastically reduces the time and storage space needed for backup, as the size of the incremental changes is significantly lower than the full database backup. 08:17 Nikita: And what's the benefit of using this backup approach? Rashmi: The benefit of this approach is that your backups are completed faster, with much lesser compute and network resources, while still guaranteeing the full recoverability of your database in the event of a failure. You can achieve zero data loss with this backup service by enabling the real-time protection option, while minimizing the data loss by recovering data up to the last subsecond. It is highly recommended to enable this option for mission-critical databases that cannot tolerate any data loss, whether due to a ransomware attack or due to an unplanned outage. The protection policy can retain the protected database backups for a minimum of 14 days to a maximum of 95 days. The recovery service requires and enforces the backups are encrypted. These backups are compressed and encrypted during the backup process. The integrity of the backups is continuously validated without placing a burden on the production database. This ensures that the stored backup data is consistent and recoverable when needed. This protects against malicious user activity or any ransomware attack. With strict policy-based retention strategy, it prevents modification or deletion of backup data by malicious users. 09:30 Lois: Now, let's look at the next layer of protection. Rashmi, can you tell us about Oracle Active Data Guard? Rashmi: Oracle Active Data Guard provides highly available data protection and disaster recovery for Enterprise Oracle Databases. It creates and manages one or more transactionally consistent standby copies of production database, which is the active primary. The standby database is isolated from production environment located miles away in a distance data center, ensuring the standby remains protected and unaffected, even if the primary is impacted by a disaster. In the event of a disaster or data corruption occurring at the primary, the standby can take over the role as new primary, thus allowing business to continue its operations uninterrupted. It keeps the standby database in sync with the production database by continuously applying change logs from production. 10:25 Do you want to stay ahead in today's fast-paced world? Check out our New Features courses for Oracle Fusion Cloud Applications. Each quarter brings new updates and hands-on training to keep your skills sharp and your knowledge current. Head over to mylearn.oracle.com to dive into the latest advancements! 10:45 Nikita: Welcome back! Rashmi, how does Oracle Active Data Guard operate in practice? Rashmi: It uses the knowledge of Oracle Database block format to continuously validate physical blocks or logical intrablock corruption during redo transport and change apply. With automatic block repair feature, whenever any corrupt block is detected in the primary or the standby database, then it is automatically repaired by transferring a good copy of the block from other destination that holds it. This is handled transparently without any error being reported in the application. It enables you to upload the read-only workloads and backup operations to the standby database, reducing the load on the production database. You can achieve zero data loss at any distance by configuring a special synchronization mechanism known as parsing. File systems form the attack surface for ransomware. Since Active Data Guard replicates the data at the memory level, any ransomware attack on the primary database will never be replicated to the standby database. This allows for a safe failover to the standby without any data loss, and shielding the database from effects of the attack. You can enable automatic failover of the primary database to a chosen standby database without any manual intervention by configuring a Data Guard Broker. The Data Guard Broker continuously monitors the primary database and automatically performs a failover to the standby when the predefined failover conditions are met. Active Data Guard enables you to perform database maintenance or database software upgrades with almost zero or minimal downtime. 12:18 Lois: And how does disaster recovery work for Exadata Database Service in Oracle Database@AWS? Rashmi: Exadata Database Service, by design, are already protected against local failures by use of technologies like Oracle RAC and Oracle Exadata. Now, by deploying Exadata Database Service across multiple availability zones in an AWS region, it can ensure that your database services remain resilient to site failures. It leverages Oracle Active Data Guard to create standby in a separate availability zone such that if the primary availability zone is affected, then all application traffic can be routed to the database services in the secondary availability zone, restoring business continuity of the application back to normal. Through continuous validation of the data blocks at both the primary and the standby database, any potential corruption is detected and prevented. This ensures data integrity and protection across the entire database service. By leveraging zero data loss Autonomous Recovery Service, the database ensures that the backup remains secure and unaffected by ransomware. This enables rapid restoration of clean, uncompromised data in the event of an attack. Periodic patching and upgrades are performed online in a rolling fashion with little to no impact on the application uptime using a combination of Oracle RAC and Oracle Active Data Guard technologies. For all resource-intensive workloads like database backup or generating monthly reports, which are read-only in nature, they can be uploaded to the standby, reducing the load on the production database. In the cross-availability zone DR setup, you have the flexibility to configure Active Data Guard to use either the AWS network or the OCI network for keeping database redo logs to the standby database. Choosing which network to use for the traffic is entirely at the enterprise discretion. However, both are Oracle maximum availability–compliant and the setup is pretty simple. If the network traffic being used is OCI network or AWS network, then respective cloud provider is responsible for ensuring the reliability. You have to take into account the different charges that each cloud provider may have. And you can provision multiple standby databases using the console. Optionally, you may set up a broker manually to enable automatic failover capability. 14:30 Nikita: We just covered cross-availability-zone protection. But what if an entire AWS region goes down? Rashmi: This is where we can provide an additional level of protection by provisioning cross-region disaster recovery for your Exadata Database Service in Oracle Database@AWS.  This deployment protects your database against regional disasters. You can provision another DR environment in a different AWS region that supports Oracle Database@AWS. This deployment, together with the cross-availability zone deployment, complements your highly available and protected database service deployment in Oracle Database@AWS. Under the hood, it uses the same Oracle Database technologies that include Oracle Active Data Guard, OCI Autonomous Recovery Service, Oracle Exadata, Oracle RAC to provide the same capabilities as in case of cross-availability zone deployment. Here too, you have the flexibility to configure Oracle Active Data Guard to use either AWS network or OCI network for shipping database redo logs to the standby. And for the network traffic options, the feature remains the same, except a small difference with respect to chargeback. When using OCI Network for cross-region deployment, there is no charge for the first 10 TB of data transfer per month. Beyond that, standard OCI charges would apply. When using AWS network, you may refer to AWS charging sheet for the cross-region traffic. 15:49 Nikita: Thank you so much, Rashmi, for this insightful episode. Lois: Yes, thank you! And if you want to dive deeper into the topics we covered today, go to mylearn.oracle.com and search for the Oracle Database@AWS Architect Professional course. Until next time, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 16:13 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

In this episode, hosts Lois Houston and Nikita Abraham are joined by special guests Samvit Mishra and Rashmi Panda for an in-depth discussion on security and migration with Oracle Database@AWS. Samvit shares essential security best practices, compliance guidance, and data protection mechanisms to safeguard Oracle databases in AWS, while Rashmi walks through Oracle's powerful Zero-Downtime Migration (ZDM) tool, explaining how to achieve seamless, reliable migrations with minimal disruption.   Oracle Database@AWS Architect Professional: https://mylearn.oracle.com/ou/course/oracle-databaseaws-architect-professional/155574 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   -------------------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Nikita: Welcome to the Oracle University Podcast! I'm Nikita Abraham, Team Lead: Editorial Services with Oracle University, and with me is Lois Houston, Director of Communications and Adoption with Customer Success Services. Lois: Hello again! We're continuing our discussion on Oracle Database@AWS and in today's episode, we're going to talk about the aspects of security and migration with two special guests: Samvit Mishra and Rashmi Panda. Samvit is a Senior Manager and Rashmi is a Senior Principal Database Instructor.  00:59 Nikita: Hi Samvit and Rashmi! Samvit, let's begin with you. What are the recommended security best practices and data protection mechanisms for Oracle Database@AWS? Samvit: Instead of everyone using the root account, which has full access, we create individual users with AWS, IAM, Identity Center, or IAM service. And in addition, you must use multi-factor authentication. So basically, as an example, you need a password and a temporary code from virtual MFA app to log in to the console.  Always use SSL or TLS to communicate with AWS services. This ensures data in transit is encrypted. Without TLS, the sensitive information like credentials or database queries can be intercepted. AWS CloudTrail records every action taken in your AWS account-- who did what, when, and from where. This helps with audit, troubleshooting, and detecting suspicious activity. So you must set up API and user activity logging with AWS CloudTrail.  Use AWS encryption solutions along with all default security controls within AWS services. To store and manage keys by using transparent data encryption, which is enabled by default, Oracle Database@AWS uses OCI vaults. Currently, Oracle Database@AWS doesn't support the AWS Key Management Service. You should also use advanced managed security services such as Amazon Macie, which assists in discovering and securing sensitive data that is stored in Amazon S3.  03:08 Lois: And how does Oracle Database@AWS deliver strong security and compliance? Samvit: Oracle Database@AWS enforces transparent data encryption for all data at REST, ensuring stored information is always protected. Data in transit is secured using SSL and Native Network Encryption, providing end-to-end confidentiality. Oracle Database@AWS also uses OCI Vault for centralized and secure key management. This allows organizations to manage encryption keys with fine-grained control, rotation policies, and audit capabilities to ensure compliance with regulatory standards. At the database level, Oracle Database@AWS supports unified auditing and fine-grained auditing to track user activity and sensitive operations. At the resource level, AWS CloudTrail and OCI audit service provide comprehensive visibility into API calls and configuration changes. At the database level, security is enforced using database access control lists and Database Firewall to restrict unauthorized connections. At the VPC level, network ACLs and security groups provide layered network isolation and access control. Again, at the database level, Oracle Database@AWS enforces access controls to Database Vault, Virtual Private Database, and row-level security to prevent unauthorized access to sensitive data. And at a resource level, AWS IAM policies, groups, and roles manage user permissions with the fine-grained control. 05:27 Lois Samvit, what steps should users be taking to keep their databases secure? Samvit: Security is not a single feature but a layered approach covering user access, permissions, encryption, patching, and monitoring. The first step is controlling who can access your database and how they connect. At the user level, strong password policies ensure only authorized users can login. And at the network level, private subnets and network security group allow you to isolate database traffic and restrict access to trusted applications only. One of the most critical risks is accidental or unauthorized deletion of database resources. To mitigate this, grant delete permissions only to a minimal set of administrators. This reduces the risk of downtime caused by human error or malicious activity. Encryption ensures that even if the data is exposed, it cannot be read. By default, all databases in OCI are encrypted using transparent data encryption. For migrated databases, you must verify encryption is enabled and active. Best practice is to rotate the transparent data encryption master key every 90 days or less to maintain compliance and limit exposure in case of key compromise. Unpatched databases are one of the most common entry points for attackers. Always apply Oracle critical patch updates on schedule. This mitigates known vulnerabilities and ensures your environment remains protected against emerging threats. 07:33 Nikita: Beyond what users can do, are there any built-in features or tools from Oracle that really help with database security? Samvit: Beyond the basics, Oracle provides powerful database security tools. Features like data masking allow you to protect sensitive information in non-production environments. Auditing helps you monitor database activity and detect anomalies or unauthorized access. Oracle Data Safe is a managed service that takes database security to the next level. It can access your database configuration for weaknesses. It can also detect risky user accounts and privileges, identify and classify sensitive data. It can also implement controls such as masking to protect that data. And it can also continuously audit user activity to ensure compliance and accountability. Now, transparent data encryption enables you to encrypt sensitive data that you store in tables and tablespaces. It also enables you to encrypt database backups. After the data is encrypted, this data is transparently decrypted for authorized users or applications when they access that data. You can configure OCI Vault as a part of the transparent data encryption implementation. This enables you to centrally manage keystore in your enterprise. So OCI Vault gives centralized control over encryption keys, including key rotation and customer managed keys. 09:23 Lois: So obviously, lots of companies have to follow strict regulations. How does Oracle Database@AWS help customers with compliance?  Samvit: Oracle Database@AWS has achieved a broad and rigorous set of compliance certifications. The service supports SOC 1, SOC 2, and SOC 3, as well as HIPAA for health care data protection. If we talk about SOC 1, that basically covers internal controls for financial statements and reporting. SOC 2 covers internal controls for security, confidentiality, processing integrity, privacy, and availability. SOC 3 covers SOC 2 results tailored for a general audience. And HIPAA is a federal law that protects patients' health information and ensures its confidentiality, integrity, and availability. It also holds certifications and attestations such as CSA STAR, C5. Now C5 is a German government standard that verifies cloud providers meet strict security and compliance requirements. CSA STAR attestation is an independent third-party audit of cloud security controls. CSA STAR certification also validates a cloud provider's security posture against CSA's cloud controls matrix. And HDS is a French certification that ensures cloud providers meet stringent requirements for hosting and protecting health care data. Oracle Database@AWS also holds ISO and IEC standards. You can also see PCI DSS, which is basically for payment card security and HITRUST, which is for high assurance health care framework. So, these certifications ensure that Oracle Database@AWS not only adheres to best practices in security and privacy, but also provides customers with assurance that their workloads align with globally recognized compliance regimes. 11:47 Nikita: Thank you, Samvit. Now Rashmi, can you walk us through Oracle's migration solution that helps teams move to OCI Database Services? Rashmi: Oracle Zero-Downtime Migration is a robust and flexible end-to-end database migration solution that can completely automate and streamline the migration of Oracle databases. With bare minimum inputs from you, it can orchestrate and execute the entire migration task, virtually needing no manual effort from you. And the best part is you can use this tool for free to migrate your source Oracle databases to OCI Oracle Database Services faster and reliably, eliminating the chances of human errors. You can migrate individual databases or migrate an entire fleet of databases in parallel. 12:34 Nikita: Ok. For someone planning a migration with ZDM, are there any key points they should keep in mind?  Rashmi: When migrating using ZDM, your source databases may require minimal downtime up to 15 minutes or no downtime at all, depending upon the scenario. It is built with the principles of Oracle maximum availability architecture and leverages technologies like Oracle GoldenGate and Oracle Data Guard to achieve high availability and online migration workflow using Oracle migration methods like RMAN, Data Pump, and Database Links. Depending on the migration requirement, ZDM provides different migration method options. It can be logical or physical migration in an online or offline mode. Under the hood, it utilizes the different database migration technologies to perform the migration. 13:23 Lois: Can you give us an example of this? Rashmi: When you are migrating a mission critical production database, you can use the logical online migration method. And when you are migrating a development database, you can simply choose the physical offline migration method. As part of the migration job, you can perform database upgrades or convert your database to multitenant architecture. ZDM offers greater flexibility and automation in performing the database migration. You can customize workflow by adding pre or postrun scripts as part of the workflow. Run prechecks to check for possible failures that may arise during migration and fix them. Audit migration jobs activity and user actions. Control the execution like schedule a job pause, resume, if needed, suspend and resume the job, schedule the job or terminate a running job. You can even rerun a job from failure point and other such capabilities. 14:13 Lois: And what kind of migration scenarios does ZDM support? Rashmi: The minimum version of your source Oracle Database must be 11.2.0.4 and above. For lower versions, you will have to first upgrade to at least 11.2.0.4. You can migrate Oracle databases that may be of the Standard or Enterprise edition. ZDM supports migration of Oracle databases, which may be a single-instance, or RAC One Node, or RAC databases. It can migrate on Unix platforms like Linux, Oracle Solaris, and AIX. For Oracle databases on AIX and Oracle Solaris platform, ZDM uses logical migration method. But if the source platform is Linux, it can use both physical and logical migration method. You can use ZDM to migrate databases that may be on premises, or in third-party cloud, or even within Oracle Cloud Infrastructure. ZDM leverages Oracle technologies like RMAN datacom, Database Links, Data Guard, Oracle GoldenGate when choosing a specific migration workflow. 15:15 Are you ready to revolutionize the way you work? Discover a wide range of Oracle AI Database courses that help you master the latest AI-powered tools and boost your career prospects. Start learning today at mylearn.oracle.com. 15:35 Nikita: Welcome back! Rashmi, before someone starts using ZDM, is there any prep work they should do or things they need to set up first? Rashmi: Working with ZDM needs few simple configuration. Zero-downtime migration provides a command line interface to run your migration job. First, you have to download the ZDM binary, preferably download from my Oracle Support, where you can get the binary with the latest updates. Set up and configure the binary by following the instructions available at the same invoice node. The host in which ZDM is installed and configured is called the zero-downtime migration service host. The host has to be Oracle Linux version 7 or 8, or it can be RCL 8. Next is the orchestration step where connection to the source and target is configured and tested like SSH configuration with source and target, opening the ports in respective destinations, creation of dump destination, granting required database privileges. Prepare the response file with parameter values that define the workflow that ZDM should use during Oracle Database migration. You can also customize the migration workflow using the response file. You can plug in run scripts to be executed before or after a specific phase of the migration job. These customizations are called custom plugins with user actions. Your sources may be hosted on-premises or OCI-managed database services, or even third-party cloud. They may be Oracle Database Standard or Enterprise edition and on accelerator infrastructure or a standard compute. The target can be of the same type as the source. But additionally, ZDM supports migration to multicloud deployments on Oracle Database@Azure, Oracle Database@Google Cloud, and Oracle Database@AWS. You begin with a migration strategy where you list the different databases that can be migrated, classification of the databases, grouping them, performing three migration checks like dependencies, downtime requirement versions, and preparing the order migration, the target migration environment, et cetera. 17:27 Lois: What migration methods and technologies does ZDM rely on to complete the move? Rashmi: There are primarily two types of migration: physical or logical. Physical migration pertains to copy of the database OS blocks to the target database, whereas in logical migration, it involves copying of the logical elements of the database like metadata and data. Each of these migration methods can be executed when the database is online or offline. In online mode, migration is performed simultaneously while the changes are in progress in the source database. While in offline mode, all changes to the source database is frozen. For physical offline migration, it uses backup and restore technique, while with the physical online, it creates a physical standby using backup and restore, and then performing a switchover once the standby is in sync with the source database. For logical offline migration, it exports and imports database metadata and data into the target database, while in logical online migration, it is a combination of export and import operation, followed by apply of incremental updates from the source to the target database. The physical or logical offline migration method is used when the source database of the application can allow some downtime for the migration. The physical or logical online migration approach is ideal for scenarios where any downtime for the source database can badly affect critical applications. The only downtime that can be tolerated by the application is only during the application connection switchover to the migrated database. One other advantage is ZDM can migrate one or a fleet of Oracle databases by executing multiple jobs in parallel, where each job workflow can be customized to a specific database need. It can perform physical or logical migration of your Oracle databases.  And whether it should be performed online or offline depends on the downtime that can be approved by business. 19:13 Nikita: Samvit and Rashmi, thanks for joining us today. Lois: Yeah, it's been great to have you both. If you want to dive deeper into the topics we covered today, go to mylearn.oracle.com and search for the Oracle Database@AWS Architect Professional course. Until next time, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 19:35 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

If you've ever wondered how Oracle Database really works inside AWS, this episode will finally turn the lights on.   Join Senior Principal OCI Instructor Susan Jang as she explains the two database services available (Exadata Database Service and Autonomous Database), how Oracle and AWS share responsibilities behind the scenes, and which essential tasks still land on your plate after deployment.   You'll discover how automation, scaling, and security actually work, and which model best fits your needs, whether you want hands-off simplicity or deeper control.   Oracle Database@AWS Architect Professional: https://mylearn.oracle.com/ou/course/oracle-databaseaws-architect-professional/155574 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   ------------------------------------------------------------   Episode Transcript:   00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26   Lois: Hello and welcome to the Oracle University Podcast! I'm Lois Houston, Director of Communications and Adoption with Customer Success Services, and with me is Nikita Abraham, Team Lead: Editorial Services with Oracle University.  Nikita: Hi everyone! In our last episode, we began the discussion on Oracle Database@AWS. Today, we're diving deeper into the database services that are available in this environment. Susan Jang, our Senior Principal OCI Instructor, joins us once again.  00:56 Lois: Hi Susan! Thanks for being here today. In our last conversation, we compared Oracle Autonomous Database and Exadata Database Service. Can you elaborate on the fundamental differences between these two services?     Susan: Now, the primary difference is between the service is really the management model. The Autonomous is fully-managed by Oracle, while the Exadata provides flexibility for you to have the ability to customize your database environment while still having the infrastructure be managed by Oracle.   01:30 Nikita: When it comes to running Oracle Database@AWS, how do Oracle and AWS each chip in? Could you break down what each provider is responsible for in this setup?  Susan: Oracle Database@AWS is a collaboration between Oracle, as well as AWS. It allows the customer to deploy and run Oracle Database services, including the Oracle Autonomous Database and the Oracle Exadata Database Service directly in AWS data centers.   Oracle provides the ability of having the Oracle Exadata Database Service on a dedicated infrastructure. This service delivers full capabilities of Oracle Exadata Database on the Oracle Exadata hardware. It offers high performance and high security for demanding workloads. It has cloud automation, resource scaling, and performance optimization to simplify the management of the service.  Oracle Autonomous Database on the dedicated Exadata infrastructure provides a fully Autonomous Database on this dedicated infrastructure within AWS. It automates the database management tasks, including patching, backups, as well as tuning, and have built-in AI capabilities for developing AI-powered applications and interacting with data using natural language. The Oracle Database@AWS integrates those core database services with various AWS services for a comprehensive unified experience.  AWS provides the ability of having a cloud-based object storage, and that would be the Amazon S3. You also have the ability to have other services, such as the Amazon CloudWatch. It monitors the database metrics, as well as performance. You also have Amazon Bedrock. It provides a development environment for a generative AI application.   And last but not the least, amongst the many other services, you also have the SageMaker. This is a cloud-based platform for development of machine learning models, a wonderful integration with our AI application development needs.  03:54 Lois: How has the work involved in setting up and managing databases changed over time?  Susan: When we take a look at the evolution of how things have changed through the years in our systems, we realize that transfer responsibility has now been migrated more from customer or human interaction to services. As the database technology evolves from the traditional on-premise system to the Exadata engineered system, and finally to the Autonomous Database, certain services previously requiring significant manual intervention has become increasingly automated, as well as optimized.  04:34 Lois: How so?  Susan: When we take a look at the more traditional database environment, it requires manual configuration of hardware, operating system, as well as the software of the database, along with initial database creation. As we evolve into the Exadata environment, the Exadata Database, specifically the Exadata cloud service, simplifies provisioning through web-based wizard, making it faster and easier to deploy the Oracle Database in an optimized hardware.     But when we move it to an Autonomous environment, it automates the entire provisioning process, allowing users to rapidly deploy mission-critical databases without manual intervention, or DBA involvement. So as customers move toward Autonomous Database through Exadata, we have fewer components that the customer needs to manage in the database stack, which gives them more time to focus more on important parts of the business.  With the Exadata Database, it provides a co-management of backup, restore, patches and upgrade, monitoring, and tuning. And it allows the administrator the ability to customize the configuration to meet their very specific business needs. With Autonomous Database, it's now fully automated and it's a greater responsibility is shift toward the service. With Autonomous Database on dedicated infrastructure, it provides that fine-grained tuning more for Oracle to help you perform that task.  06:15 Nikita: If we narrow it down just to Oracle and AWS for a moment, which parts of the infrastructure or day-to-day ops are handled by each company behind the scenes?  Susan: When we take a look at Oracle Database@AWS, it operates under a shared responsibility model, dividing the service responsibilities between AWS, as well as Oracle, as well as you, the customer.   The AWS has the data center. Remember, this is where everything is running. The Oracle Database@AWS, the Oracle Database infrastructure may be managed by Oracle and run in OCI, but is physically located within the AWS regions, as well as the availability zones and the AWS data centers.  The AWS infrastructure, in this case, is AWS's responsibility to secure the environment, including the physical security of the data center, the network infrastructure, and the foundational services like the compute, the storage, and the networking, all within AWS.  The next thing of who's responsible for the shared responsibility, it's Oracle. And that would be the hardware. We provide the hardware. While the hardware may physically reside in the AWS data center, Oracle's Cloud Infrastructure operational team will be the one managing this infrastructure, including software patching, infrastructure update, and other operations through a connection to OCI. This means Oracle handles the provisioning, as well as the maintenance of any of the underlying Exadata infrastructure hardware.  When we take a look at the next thing that it manages, it is also responsible besides the infrastructure of the Exadata. It is also the ability to manage the hardware, the environment of that hardware through the database control plane. So Oracle manages the administration and the operational for the Oracle Database@AWS service, which resides in OCI. So this includes the capabilities for management, upgrade, and operational features.  08:37 Nikita: And what are the key things that still remain on the customer's plate?   Susan: If you are in an Exadata environment or in an Autonomous environment, it is you, the customer, who is responsible for most of the database administration operation, as well as managing the users and the privileges of the user to access the database. No one knows the database and who should be accessing the data better than you.  You will be responsible for securing the applications, the data of the database, which now allows you to define who has access to it, control the data encryption, and securing the application that interacts with the Oracle Database@AWS.  09:29 Lois: Susan, we've talked about both Autonomous Database and Exadata Database Service being available on Oracle Database@AWS, but what's different about how each works in this environment, and why might someone pick one over the other?  Susan: Both databases, even though they run on the same Exadata Cloud Infrastructure, both can be deployed on both public cloud, as well as the customer data center, which is Oracle Cloud@Customer.  The Autonomous Database is a fully managed, completely automated environment. And this provides a capability of having a fully Autonomous Database Service running on a dedicated Oracle Exadata Infrastructure within your AWS data center.  The Exadata is a service that is provided and managed by Oracle and is physically running in the AWS data center, but is designed for mission critical workload and includes RAC environment, Real Application Cluster, offering a high performance availability and full feature capability that is similar to other Exadata environment, such as those running in our customers' data center.  The primary difference is really between the two services. When you take a look at the Exadata, the customer only pays for the compute resources that is used. Autoscaling can be used for a variety or variable resources, the workload, to automatically scale to the compute resources up or down when required.  The Autonomous Database also has automatic optimization for data warehousing, transaction processing, as well as JSON workload. The Exadata service, the customer again, also pays for the compute resources that they allocate. But that's the key thing. The customer can initiate the scaling because it's very specific to the workload that is needed.  So when you take a look at the two database services, one gives the ability to let Oracle fully manage it, including the scaling capability. The other, the Exadata, provides you the capability of having the environment that it's running on the infrastructure be managed by Oracle that adds a database administrator. You may wish to have a little bit more granular control of how you want the database to not only be scaling, but how you wish to customize how the database will be running.  12:10 Nikita: Focusing on Autonomous Database for a moment, what should teams know about how it actually runs within AWS?   Susan: The Autonomous Database on the Oracle Database@AWS brings the power of the Oracle's self-managing, self-securing, and self-repairing database into your AWS environment.  It provides the capability of the database automatically, automates many of the traditional, complex, and time-consuming database management tasks, such as the provisioning of the database, the patching, the backing up, and the scaling, and the performance tuning, reducing the need for any manual intervention by the database administrator.  Running the Autonomous Database in your AWS region enables low latency access for your AWS applications and services that is deployed within AWS, thus improving performance and response time. With the Autonomous Database, it automates many of the traditional things that is now automatically done by Oracle. It also supports integration with various AWS services, such as the ability of the not in addition to AIM, but the cloud formation, the CloudWatch for monitoring and the S3 for the storage.  You can easily migrate existing Exadata workload, including those running on Oracle RAC to AWS with minimum or no change to any of your databases or applications. In addition, there's a really powerful capability and feature of the database is called zero ETL, and that's zero extract, transformation, and load.  It's an integration capability with services like your Amazon Redshift, enabling near real time analytics and machine learning on your transactional database that is stored within the Autonomous Database on in your AWS environment. So with the Autonomous Database, it checks off many of the boxes for automatic capability, securing, tuning, as well as scaling the database.  With the Autonomous Database in the Dedicated Exadata Infrastructure, the Exadata Cloud Infrastructure resource represents the physical system, which can be expanded with storage, as well as compute services, the compute host. This now provides the ability to have an isolated zone for the highest protection from other tenants. The data is stored on a dedicated server only for one customer. That would be you.  14:56 Lois: Could you explain the role of Autonomous VM? What are its primary benefits?  Susan: The virtual machine or as we refer to them as the cluster, includes the grid infrastructure and provides a private network isolation. This provides you the capability of having custom memory, core, and storage allocation.  The Oracle Grid Infrastructure includes the Oracle Clusterware, which manages the cluster, as well as the servers, and ensure that the database can failover to another server in case of any failure.  15:34 Be a part of something big by joining the Oracle University Learning Community! Connect with over 3 million members, including Oracle experts and fellow learners. Engage in topical forums, share your knowledge, and celebrate your achievements together. Discover the community today at mylearn.oracle.com.  15:55 Nikita: Welcome back! Susan, what is the Autonomous Container Database?  Susan: With the Autonomous Container Database, and you need that if you're going to create an Autonomous Database, you need to provision that within your Autonomous Exadata VM Cluster. It serves as a container to hold or to house one or more Autonomous Databases.  This allows multiple Autonomous Databases to coexist in the same infrastructure while still being logically separated. And this allows for the separation of databases based on their intended use. Think of a database for production. Think of a database for development. Think of a database for testing. You may have different database versions within the same infrastructure.  This isolation makes it easier for you to be able to meet your SLA, your Service Level Agreement, any long-term backups you may have, very specific encryption key needs to prevent issues from one database impacting another. So, the ability to have everything be isolated and secure is still grouping it in a manner that will meet your business needs.  17:08 Lois: Looking at Exadata Database Service specifically, what are some standout advantages for customers who deploy it on Oracle Database@AWS? Is there anything in particular they should get excited about in terms of performance or integration with AWS?  Susan: The Exadata Database Service is running on a dedicated Exadata Infrastructure that's deployed within your AWS data center. It delivers the same Exadata service experience in cloud control planes as the Oracle Cloud Infrastructure, allowing you to leverage existing skills and processing across your multi-cloud environment.  It addresses the data resiliency, or residency rather. And that's the scenario where many of our customers has the need. You have a need because of your security compliance to have the data local to you. By having the Exadata Database in your Oracle Database@AWS, it is running in your data center. So, this addresses that very important need, data residency, to have it close to you.  It also allows for seamless integration with other AWS services and applications. So now you have a capability of a hybrid cloud architecture leveraging the benefit of both Oracle Exadata and your AWS system. It has built-in high availability, the RAC application cluster, as well as Data Guard, a capability of addressing disaster recovery capability.  This also provides the ability for you to scale your compute, as well as your storage and your I/O resources independently. So as mentioned with Exadata, you have flexibility of how you want your database to be running individually. So just like the Autonomous, the Exadata Database checks off many of the boxes for running a mission-critical with high availability, highly redundant hardware and software features, along with extreme performance, scalability, and reliability.  This now allows you to run your AI environment, your online transaction processing, your analytic workload on any scale on the Exadata Infrastructure running in the Oracle Cloud. And in this case, running in your data center.  19:45 Nikita: If a business suddenly needs more capacity, how does scaling work with Exadata Database Service versus Autonomous Database on Oracle Database@AWS?   Susan: So with the Exadata scaling, you now can scale to meet expected demands so you know at certain point I will need more. I will then ask it to scale at that point when I will assign it-- and I'm using an example, I will assign it three computer cores all the time. But there may be demands. Think of your end of the quarter, end of the year processing that you may need more. So, you are enabling the compute cores to scale at the time you need it.  And what's cool is it will then, when it's no longer needed, it will then scale back down to the original three cores that you assign. So, you only pay for the enabled cores. But what's very cool about the Autonomous is that it is real-time scaling. So, with Autonomous, now you have the capability using Autonomous Database since it is self-tuning, self-monitoring, the Autonomous Database actually monitors the workload requirement and scales to match the workload demand.  Once the minimum level of the compute is defined and enabled, the automatic scaling is set. Autonomous Database will adjust to the consumption when it's needed, and it will scale back down when it's not. So though the Exadata is pretty cool, it will scale up and down on the workload demand.  This is with the Autonomous is even more powerful. It is real-time scaling based on that usage at that moment. Built-in automatic increase to meet the workload demands when it spikes and it automatically scales back when it's not needed.  A very powerful capability with all of our Oracle databases, the ability, even with traditional, to allow you to define what you may need with Exadata scaling for peak demands, as well as Autonomous scaling for real-time consumption and scaling when needed.  When you look at all of our options, one of the key things to bear in mind is a phrase that we use: performance scale as more servers are added. And what this is really saying is Oracle's automated scaling ability for the database, it basically has the ability to maintain or improve its performance under increased workload by automatically adding computational resources when needed.  This process is also known as horizontal scaling. It involves adding more servers, compute instances, to a cluster to share the processing load. And it has that capability automatically.  22:53 Nikita: There's so much more we can discuss about Oracle Database@AWS, but let's pause here for today! Thank you so much Susan for joining us.  Lois: Yeah, it's been really great to have you, Susan. If you want to dive deeper into the topics we covered today, go to mylearn.oracle.com and search for the Oracle Database@AWS Architect Professional course. Until next time, this is Lois Houston…  Nikita: And Nikita Abraham, signing off!  23:23 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

In this episode, hosts Lois Houston and Nikita Abraham take you inside how Oracle brings its industry-leading database technology directly to AWS customers.   Senior Principal OCI Instructor Susan Jang unpacks what the OCI child site is, how Exadata hardware is deployed inside AWS data centers, and how the ODB network enables secure, low-latency connections so your mission-critical workloads can run seamlessly alongside AWS services.   Susan also walks through the differences between Exadata Database Service and Autonomous Database, helping teams choose the right level of control and automation for their cloud databases.   Oracle Database@AWS Architect Professional: https://mylearn.oracle.com/ou/course/oracle-databaseaws-architect-professional/155574 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   -------------------------------------------------------------   Episode Transcript:   00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Nikita: Welcome to the Oracle University Podcast! I'm Nikita Abraham, Team Lead: Editorial Services with Oracle University, and with me is Lois Houston, Director of Communications and Adoption with Customer Success Services.  Lois: Hi there! Last week, we talked about multicloud and the partnerships Oracle has with Microsoft Azure, Google Cloud, and Amazon Web Services. If you missed that episode, do listen to it as it sets the foundation for today's discussion, which is going to be about Oracle Database@AWS.  00:59 Nikita: That's right. And we're joined by Susan Jang, a Senior Principal OCI Instructor. Susan, thanks for being here. To start us off, what is Oracle Database@AWS?  Susan: Oracle Database@AWS is a service that allows Oracle Exadata infrastructure that is managed by Oracle Cloud Infrastructure, or OCI, to run directly inside an AWS data center.   01:25 Lois: Susan, can you go through the key architecture components and networking relationships involved in this?    Susan: The AWS Cloud is the Amazon Web Service. It's a cloud computing platform. The AWS region is a distinct, isolated geographic location with multiple physically separated data center, also known as availability zone. The availability zone is really a physically isolated data center with its own independent power, cooling, and network connectivity.  When we speak of the AWS data center, it's a highly secured, specialized physical facility that houses the computing storage, the compute servers, the storage server, and the networking equipment. The VPC, the Virtual Private Cloud, is a logical, isolated virtual network.  The AWS ODB network is a private user-created network that connects the virtual private cloud network of Amazon resources with an Oracle Cloud Infrastructure Exadata system. This is all within an AWS data center. The AWS-ADB peering is really an established private network connection that's between the Oracle VPC, the Virtual Private Cloud, and the Oracle Database@AWS network. And that would be the ODB.  Within the AWS data center, you have something that you see called the child site. Now, an OCI child site is really a physical data center that is managed by Oracle within the AWS data center. It's a seamless extension of the Oracle Cloud Infrastructure. The site is hosting the Exadata infrastructure that's running the Oracle databases.  The Oracle Database@AWS service brings the power as well as the performance of an Oracle Exadata infrastructure that is managed by Oracle Cloud Infrastructure to run directly in an AWS data center.  03:57 Nikita: So essentially, Oracle Database@AWS lets you to run your mission-critical Oracle data load close to your AWS application, while keeping management simple. Susan, what advantages does Oracle Database@AWS bring to the table?  Susan: Oracle Database@AWS offers a powerful and flexible solution for running Oracle workloads natively within AWS. Oracle Database@AWS streamlines the process of moving your existing Oracle Database to AWS, making migration faster as well as easier.  You get direct, low latency connectivity between your application and Oracle databases, ensuring a high performance for your mission-critical workloads.   Billing, resource management, and operational tasks are unified, allowing you to manage everything through similar tools with reduce complexity. And finally, Oracle Database@AWS is designed to integrate smoothly with your AWS environments' workloads, making it so much easier to build, deploy, and scale your solutions.  05:15 Lois: You mentioned the OCI child site earlier. What part does it play in how Oracle Database@AWS works?   Susan: The OCI child site really gives you the capability to combine the physical proximity and resources of AWS with the logical management and the capability of Oracle Cloud Infrastructure. This integrated approach allows us to enable the ability for you to run and manage your Oracle databases seamlessly in your AWS environment while still leveraging the power of OCI, our Oracle Cloud Infrastructure.  06:03 Did you know that Oracle University offers free courses on Oracle Cloud Infrastructure for subscribers! Whether you're interested in multicloud, databases, networking, security, AI, or machine learning, there's something for everyone. So, what are you waiting for? Pick your topic and get started by visiting mylearn.oracle.com.   06:29 Nikita: Welcome back! Susan, I'm curious about the Exadata infrastructure inside AWS. What does that setup look like?  Susan: The Exadata Infrastructure consists of physical database, as well as storage servers. That is deployed-- the database and the storage servers are interconnected using a high-speed, low-latency network fiber, ensuring optimal performance and reliable data transfer.  Each of the database server runs one or more Virtual Machines, or VMs, as we refer to them, providing flexible compute resources for different workloads. You can create, as well as manage your virtual machine, your VM clusters in this infrastructure using various methods. Your AWS console, Command-Line Interface, CLI, or Application Program Interface, that's your API, giving you various options, several options for automating, as well as integrating your existing tools.  When you're creating your Exadata Infrastructure, there are a few things you need to define and set up. You need to define the total number of your database servers, the total number of your storage server, the model of your Exadata system, as well as the availability zone where all these resources will be deployed.  This architecture delivers a high-performance resiliency and flexible management capability for running your Oracle Database on AWS.  08:18 Lois: Susan, can you explain the network architecture for Oracle Database deployments on AWS?   Susan: The ODB network is an isolated network within the AWS that is designed specifically for Exadata deployments. It includes both the client, as well as the backup subnet, which are essential for securing and efficient database operations.  When you create your Exadata Infrastructure, you need to specify the ODB network as you need the connectivity. This network is mapped directly to the corresponding network in the OCI child site. This will enable seamless communication between AWS, as well as the Oracle Cloud Infrastructure.  The ODB network requires two separate CIDR ranges. And in addition, the client subnet is used for the Exadata VM cluster, providing connectivity for database operations. Well, you do also have another subnet. And that subnet is the backup subnet. And it's used to manage database backups of those VM cluster, ensuring not only data protection, but also data recovery.  Within your AWS region and availability zone, the ODB network contains these dedicated client, as well as backup subnet. It basically isolates the Exadata traffic for both the day-to-day access, and that would be for the client, as well as the backup operations, and that would be for the backup subnet. This network design supports secure, high performance, and connectivity in a reliable backup management of the Oracle Database deployments that is running on AWS.  10:23 Nikita: Since we're on the topic of networking, can you tell us about ODB peering within the Oracle Database architecture?  Susan: The ODB peering establishes a secure private connection between your AWS Virtual Private Cloud, your VPC, then the Oracle Database, the ODB network that contains your Exadata Infrastructure.  This connection makes it possible for application servers that's running in your VPC, such as your Amazon EC2 instances to access your Oracle databases that is being hosted on Exadata within your ODB network. You specify the ODB network when you set up your infrastructure, specifically the Exadata Infrastructure. This network includes dedicated client, as well as backup subnets for an efficient and secure connectivity.  If you wish to enable multiple VPCs to connect to the same ODB network and access the Oracle Database@AWS resources, you can leverage AWS Transit Gateways or even an AWS Cloud WAN for scalable and centralized connectivity.   The virtual private cloud contains your application server, and that's securely paired with the Oracle Database network, creating a seamless, high-performance path to your application to interact with your Oracle Database.  ODB peering simplifies the connectivity between the AWS application environments and the Oracle Exadata Infrastructure, thus supporting a flexible, high performance, and secure database access.  12:23 Lois: Now, before we close, can you compare two key databases that are available with Oracle Database@AWS: Oracle Exadata Database Service and Oracle Autonomous Database Service?  Susan: The Exadata Database Service offers a fully managed and dedicated infrastructure with operational monitoring that is handled by you, the customer. In contrast, the Autonomous Database is fully managed by Oracle, taking care of all the operational monitoring.  Exadata provides very high scalability though resources, such as disk and compute, must be sized manually. Where in the Autonomous Database, it offers high scalability through automatic elastic scaling. When we speak of performance, both service deliver strong results. Exadata offers ultra-low latency and Exadata-level performance, while the Autonomous Database delivers optimal performance with automation.  Both services provide high migration capability. Exadata offers full compatibility and the Autonomous Database includes a robust set of migration tools. When it comes to management, Exadata requires manual management and administration. And that's really in a way to provide you the ability to customize it in the manner you desire, making it meets your very specific business needs, especially your database needs.  In contrast, the Autonomous Database is fully managed by Oracle, including automated administration tasks, optimal self-tuning features to further reduce any management overhead. When we speak of the feature sets, the Exadata delivers a full suite of Oracle features, including the RAC application cluster, or the Real Application Cluster, RAC, whereas the Autonomous offers a complete feature set, but specifically that is designed for optimized Autonomous operations.  Finally, when we speak of integration, integration for both of this service integrates seamlessly with AWS service, such as your EC2, your network, the VPC, your policies, the Identity and Access Management, your IAM, the monitoring with your CloudWatch, and of course, your storage, your SC, ensuring a consistent experience within your AWS ecosystem.  15:21 Nikita: So, you could say that the Exadata Database Service is better for customers who want dedicated infrastructure with granular control, while the Autonomous Database is built for customers who want a fully automated experience. Thank you, Susan, for taking the time to talk to us about Oracle Database@AWS.  Lois: That's all we have for today. If you want to learn more about the topics we discussed, head over to mylearn.oracle.com and search for the Oracle Database@AWS Architect Professional course. In our next episode, we'll find out how to get started with the Oracle Database@AWS service. Until then, this is Lois Houston…  Nikita: And Nikita Abraham, signing off!  16:06 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

Multicloud is changing the way modern teams run their workloads: with real choice and real control.   In this episode, hosts Lois Houston and Nikita Abraham welcome Senior Principal OCI Instructor Sergio Castro, who explains how Oracle has partnered with Microsoft Azure, Google Cloud, and AWS to bring Oracle Database directly inside their data centers, unlocking sub-millisecond latency and new levels of flexibility.   They discuss how organizations can seamlessly migrate from on-premises or between clouds with minimal disruption, take advantage of best-in-class cloud services, and enhance business continuity.   Oracle Database@AWS Architect Professional: https://mylearn.oracle.com/ou/course/oracle-databaseaws-architect-professional/155574 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   ------------------------------------------------------------   Episode Transcript:   00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Lois: Hello and welcome to the Oracle University Podcast! I'm Lois Houston, Director of Communications and Adoption with Customer Success Services, and with me is Nikita Abraham, Team Lead: Editorial Services. Nikita: Hi everyone! We're kicking off a new season of the podcast today, this time on Oracle Database@AWS. But before we fully dive into that, we've got Sergio Castro with us to introduce multicloud and talk about some of its use cases. Sergio, who you may have heard on the podcast before, is a Senior Principal OCI Instructor with Oracle University.   01:02 Lois: Hi Sergio! Thanks for joining us today. We've spoken a lot about multicloud before, but we couldn't possibly discuss Oracle Database@AWS without another quick intro to multicloud. So, for anyone who doesn't already know, what is multicloud? And could you also talk about what Oracle is doing in this space?  Sergio: It is the use of several Cloud providers to deliver an IT service. Basically, a multi-cloud strategy allows organizations to distribute their workloads across multiple Cloud platforms and providers. This will help aiding the flexibility when picking the right tool for each job. Basically, by selecting the best Cloud Service, IT architects can take advantage of each provider's strengths, including custom hardware, software, and service capabilities. And Oracle is a pioneer in multi-cloud. We have partnerships with Azure, Google Cloud, AWS, and we've been doing multi-cloud since 2019, including Oracle Interconnect for Azure and Oracle Interconnect for Google Cloud. Our multi-cloud products is the Oracle Database Service at Azure, at Google Cloud, and at AWS. Here we have our database inside the data centers of these Cloud Service providers. And multi-cloud can be complemented by resources that you have on-premises, providing you with a hybrid Cloud model. And our public Cloud offerings are not limited to the commercial realm. Multi-cloud is beginning to be available also in the government realm. You can now find Oracle Interconnect for Azure in the US government realm. We also have government realm offerings in the UK and in the European Union. And of course, dedicated Cloud. If you're going to be involving on-premises, you can also have all the Oracle Cloud Infrastructure resources behind your firewall, behind your routers with dedicated Cloud. So the offers from Oracle Cloud Infrastructure are really exceptional. It offers you great flexibility and choice. And the choice is yours. You select the platform for your Oracle Cloud solutions.  03:39 Nikita: You've already mentioned a few of them, but could you talk about the various benefits of multicloud? Sergio: A solid multi-cloud approach enables organizations to leverage the unique strengths and offerings of various Cloud service providers. By not being limited to a single vendor's capabilities or policies, businesses can adapt quickly to changing environments, deploy workloads where they fit best, and rapidly integrate new solutions as market demands evolve.  Relying on a single Cloud vendor can make it challenging and costly to migrate workloads or switch providers if businesses needs change. Multi-cloud strategies mitigate this risk by distributing applications and data across multiple platforms, making technology transition smoother and giving organizations greater bargaining power.  Now, diminishing single points of failure at the Cloud service provider level is great, because distributing systems and data across multiple clouds can definitely reduce dependence on a single provider or region.  This increased geographic diversity improves resilience and provides a more robust backup and recovery option, helping to ensure business continuity in the event of a disaster or even an outage. With access to a range of pricing models and service levels from different providers, organizations can allocate workloads based on cost effectiveness.  This best fit approach encourages cost savings by enabling the selection of the most economical provider for each workload. And this facilitates continuous cost optimization efforts. For example, OCI provides significantly lower data egress charges, this in comparison to our competitors.  Multicloud management empowers organizations to place their workloads in the environments where they perform the best. By distributing workloads based on latency, processing power, or data proximity, businesses can realize performance improvements and achieve higher availability for their critical services.  Now regarding best of breed, each Cloud provider brings unique innovations and specialized services to the market. With a multi-cloud approach, organizations can tailor solutions to meet specific business needs.  Operating across multiple Cloud platforms means access to a wider array of data centers worldwide. This extended reach supports expansion into new markets, improves local performance for users, and helps satisfy data sovereignty requirements in diverse jurisdictions. And speaking about jurisdictions, this flexibility helps meet industry standards and regional data protection laws more effectively.  06:50 Nikita: You mentioned that Oracle's multicloud journey started in 2019 with Azure. What was that early phase like? Sergio: The Oracle Cloud Infrastructure multi-cloud offering started with the Oracle Interconnect for Microsoft Azure, where we connect FastConnect, our digital circuit, to the equivalent Express Route, the digital circuit of Microsoft Azure. Basically FastConnect, it is used typically for extending the OCI services into on-premises. In this case, it is extending these services into another Cloud Service provider, Microsoft Azure or various applications. 07:29 Lois: And then we moved on to Oracle Database Service for Azure, right?  Sergio: It's very similar to what we have right now, the Oracle Database Service at Azure, except that back then, the interface was on OCI. Basically on OCI, we had a console that resembled Azure, but all the services were still running on OCI. Now, the difference with Oracle Database Service at Azure is that we extended Oracle Cloud Infrastructure into the Azure data centers. So Oracle Database at Azure is a child site in the Microsoft Azure data centers. Basically we are placing our hardware in Azure data centers. And this gives us a very good latency, sub-one millisecond latency. 08:24 Lois: What about Oracle's multicloud services with Google and Amazon Web Services?  Sergio: Oracle Interconnect org and Oracle Database app are available for Google Cloud. We do have a service called Oracle Interconnect or Google Cloud, similar to the Azure one. And we also have the Oracle Database inside the Google Cloud data centers operating as a child site. And back in 2024 during Oracle Cloud World, we announced Oracle Database@AWS. This product is now available in two AWS regions. In a similar way, we have the Oracle Database inside the AWS data center with sub-one millisecond latency. We are currently in two data centers, but we have brought plans for being available in over 20 plan regions between Oracle Cloud and Amazon Web Services. 09:32 Nikita: Sergio, how do the capabilities of Oracle Database multicloud help enterprises modernize? Sergio: Oracle Database multi-cloud capabilities help enterprise modernize, adopting a Gen AI strategy, obviously, using the Oracle database to bring Oracle's powerful AI to business data. When you move to multi-cloud environments, you have a playground for you to test and run your workloads and then go into productions with your choice of services on the Oracle Exadata. And reducing risk, it's very easy to move to cloud and gain Oracle maximum availability architecture benefits. And by moving into a multi-cloud environment, you guarantee that you're going to be lowering your cost because you're going to be selecting the best of breed of the services that the Cloud Service provider can offer. Now, with the Oracle Database on multi-cloud environments, you're able to port your Oracle Database knowledge that you have from on-premises to a single cloud provider to a multi-cloud environment. It is the same solution, the same Oracle Database capabilities available everywhere-- on-premises, on your private cloud, on a single cloud provider, or on a multi-cloud environment. Having the same capabilities make it very easy to migrate from on-premises or to migrate from one cloud service provider to the other. Oracle Database multi-cloud solutions really offer the best of both worlds. So a choice of services directly from hyperscaler marketplace and the vendor's cloud portal. 11:21 Lois: And when you say "hyperscalers," who exactly are you referring to? Sergio: These hyperscalers, we're talking about OCI, we're talking about Azure, we're talking about Google cloud, we're talking about AWS. Having the Oracle Database inside the Cloud data centers, regardless of who the hyperscaler provider is, guarantees low latency from your application into your database. But Oracle Database is not the only product. We also offer Oracle Interconnect for Azure and GCP. So if you want to go beyond Oracle Database@Cloud Service provider, or if you're looking to going into a region where the service is not available yet, you can leverage the Oracle Interconnect for Azure or Google Cloud platform. Basically, this service interconnects the Cloud Service providers. We have a partnership and selected regions where we interconnect with either Azure or Google Cloud platform.  12:25 Are you working toward an Oracle Certification? Join one of our live certification prep events! Get insider tips from seasoned experts and connect with others on the same path. Visit mylearn.oracle.com and kick off your certification journey today! 12:45 Nikita: Welcome back! Sergio, could you tell us about some key Oracle Database multicloud use cases? Sergio: Move to cloud. Lift and shift from on-premises to Cloud. Lift and shift from one Cloud Service provider to the other, and consolidate your database on Exadata. This will guarantee all the tools that you need for building innovative applications, bringing artificial intelligence to your business data, on the Oracle powerful AI suite, and combine Database AI with hyperscaler services and frameworks. Remember, the best of breed from the Cloud Service provider of your choice. And this will allow you to reduce complexity and cost. Now according to knowledge is not the only thing. You can also lift and ship without refactoring your data, reducing migration times, complexity, and costs with the Oracle Database Exadata and maximum availability architecture. 13:47 Nikita: What are the key differentiators and benefits of moving Oracle Database workloads to the cloud? Sergio: Extreme performance. Accelerate your database workloads with scalability, scale infrastructure, and consumption, and extreme cost optimization. But that's not all. You also get extreme availability with the Oracle maximum availability architecture, extreme resiliency, making sure that you're always running with high availability and disaster recovery protection and extreme simplicity. So you can use all your Oracle Database and Exadata capabilities. Build innovative applications with Cloud-First capabilities. These are Cloud native capabilities that are going to enable you to innovate for all your applications. And having a unified multi-cloud environment reduce complexity and cost because you can leverage your Exadata infrastructure with share licenses, low administration with database lifecycle automation, and purchase through your hyperscaler marketplace. So you can only have one vendor running all billing, even if you're leveraging multi-cloud solutions. And you can leverage your Oracle investments with bring-your-own-license and earn up to 33% towards Oracle tech license. Reduce administration by up to 65% with the Autonomous self-driving database. Only pay consumption for actual usage with online scaling, Autonomous Database, elastic pools, and per second billing. And enjoy advanced features at no added cost, like using the built-in AI vector search. 15:31 Lois: Can you give us a real-world example of a company using Oracle Database@AWS? Sergio: Fidelity Investments rely on Oracle Database@AWS. They were one of the very first customers to leverage the best of both worlds, in this case, the offering from the AWS hyperscale applications and the Oracle Database Exadata Cloud service inside AWS. Specifically, Fidelity uses this integration to make it easier to move some of its database workloads to AWS, combining the reliability and security of AWS with the critical enterprise software provided by Oracle.  16:17 Lois: Thank you, Sergio, for joining us on the podcast! To learn more about what we discussed today, head over to mylearn.oracle.com and search for the Oracle Database@AWS Architect Professional course. Join us next week when we dive deep into what Oracle Database@AWS is all about. Until then, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 16:43 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

Join us for an inspiring conversation with private equity advisor Jeffrey Malcolm as he shares how Oracle AI certification has transformed his career, family, and approach to business. Discover the real-world impact and opportunities that come from upskilling with Oracle's leading AI training programs.   AI Foundations: https://mylearn.oracle.com/ou/learning-path/become-an-oci-ai-foundations-associate-2025/147781 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, Anna Hulkower, Kris-Ann Nansen, and the OU Studio Team for helping us create this episode.   ------------------------------------------------------------   Episode Transcript:   00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Lois: Welcome to the Oracle University Podcast. I'm your host, Lois Houston, and I'm joined today by Jeffrey Malcolm, Operating Adviser working in the private equity space, to talk about how Oracle AI certifications have impacted his professional and personal life. Hi Jeffrey, thank you so much for taking the time to chat with us today. Our conversation actually stems from a fascinating discussion we had at AI World, Oracle's annual user conference. There you shared your journey to becoming Oracle AI certified... How that process not only shifted your perspective on emerging technologies, but also influenced the way you work, interact with colleagues and clients, and even how you encourage continued learning in your own family. I'm really excited to dive deeper into your story and explore the value and real world benefits of certification in today's AI-driven landscape. 01:20 Jeffrey: Uh Lois, first of all, thank you for having me. Um, it was fantastic running into your teammates at AI World. It was amazing. You know, for for me, you know, as we go through this AI journey with my portfolio companies, I'm constantly looking at what are the new things out there? How can I get myself enabled? So, excited that we're having this conversation today. 01:42 Lois: That's great. So, let's start at the beginning. Before your certifications, what was your initial reaction when you heard about Oracle's OCI and AI certification programs? Were you immediately interested or was there hesitation? Jeffrey: I was skeptical. You know, I was skeptical about OCI capabilities as you guys didn't have much market penetration at the time. You know, in my technology career, I built several enterprise applications on AWS, Azure, and GCP. However, OCI Cloud was new and my wife Kay Malcolm, who you know, kept raving at home over and over about OCI, that the cloud was faster, it was more secure and cost friendly. All of which this thing that I'm hearing are appealing to me as a CIO because that's something that I need to control at my companies that I'm working with. Lois: Right. Jeffrey: So because even though I was skeptical I was like if all of these things are appealing to her, I'm going to go ahead, I'm going to take the certification, I'm going to confirm all of these allegations that she's making to just make sure that, you know, it's actually true. And I was pleasantly surprised once I pulled the covers back. 02:59 Lois: So, you mentioned that your wife actually encouraged you to sign up for the free OCI Foundations training. Can you tell me a little bit more about that experience and how it influenced your decision to continue learning? Jeffrey: When she took the OCI test, at first she passed with a 95% score. So, you know, that encouraged me to just, you know, to take it as as as informative as I can. And to be honest, I wanted to beat her score because, you know, we're competitive. Um, upon passing and seeing the high quality of the candidate, you know, of the content. Uh, it was just hard for me to keep this internally. I wanted to share it with my network. I wanted to kind of see if there's others that could benefit from it. But you know my my initial piece was how can I beat her? And when I was able to date the score I I did score a 96 and beat her and I started sharing it with my network. And what happened Lois it was amazing. You know we we found a a cohort of individuals right around 50 who wanted to start taking the similar course. We were like hey this is something that's amazing. We had individuals who were teachers. We had individuals who had work in the corrections facility. We had plumbers. We had electrician. And they were all skeptical about taking this highly technical course. But we said, "Hey, it's self-paced. It's something that you can do and you can really benefit your career." So at the end, we had 50 people who took it. Of the 50, we had 30 brave souls who went ahead and took the certification. Um, and of the 30, we had a 24 people who passed. That's almost a 90% pass rate. Lois: Yeah.  Jeffrey: And it was so successful, we actually had one individual who shared their news. He was able to get a new position where he became a technical project manager and 3x his salary. So, it was just amazing to watch how people were brave enough to take this content, how OCI did an amazing job of making it self-paced and absorbable and then people got the certification, we published it on LinkedIn, and people actually got jobs. So, it was actually quite quite impressive. 05:24 Lois: That's an incredible story. So, you didn't just become a believer, you actually went and built an application on OCI, right? What was the project and how did your new skills play a role in making that happen? Jeffrey: That's that's a funny story. So at the time I was doing the uh the OCI training. I was building a mobile native application for a startup who was at the time looking to impact climate change. They were socially conscious enterprise dedicated to bring human-centered tools to individuals to live a better life and protect our environment. You know, the the main focus was how can they create an application that had no ads, only information, and provide a tool that would allow people to do joyful actions such as recycling, such as, you know, um looking at how you can lower your power consumption in your home, moving from plastics away from your home and just not consuming that much plastic. So we really wanted to gamify that and build an application that could do that. Uh my training gave me the confidence that as I was architecting the solution to say I needed to build something scalable and secure and full transparency at the time my myself and the rest of my development team was looking at completely AWS solutions. From this training I was like no if we really want something secure and scalable, the Oracle Database specifically Autonomous Database is it and we switched we built a multicloud solution across Azure um AWS and um GCP as well as OCI OCI had our backend and we built our application to leverage it specifically because after taking a training I was convinced that the backend needed to on Oracle Database specifically Autonomous Database. So it helped the the application had been running now for 3 years no issues um from a scalability standpoint and it's been fantastic for us. 07:34 Lois: Well that's great. That's a great story to uh to talk about how you leveraged your training and into something that actually made a difference in your job. So let's talk a little bit about your AI certification. You've described the AI foundations training that you took from Oracle University as demystifying. So tell me about some of the biggest takeaways for you. How did it shift your understanding of what AI really is and how it can be used? Jeffrey: That's a great point. Um you know in the last two three years AI has just been the talk of the town and specifically in my role as an advisor to private equity companies, I'm constantly being asked how can AI impact the top line? How can AI the bottom line and help us realize the multiple or investment pieces to exit um our our different companies? My background whenever I look at a problem I need to understand the guts of it and at the time there was all of these myths and and and confusion and scared to be honest around AI. So coming from an engineering background at MIT, one of the things MIT taught me is I need to look under the covers to truly understand something from a technology standpoint. Do my due diligence before sharing best practices with my portfolio companies that I'm working with. So that made me take on this challenge to say hey I need to understand what's the difference between machine learning, deep learning. What are the different you know kind of you know neural networks out there? When do you want to use it? So the AI foundation training that Oracle was offering was compelling to me to the point that I had had great success on the OCI's piece I'm like let me take this on. So that's what really started my journey back in January of 2023 um this was just a few months after the release of ChatGPT and I really wanted to understand how AI can like skyrocket and help our companies you know drive drive value. So that's what made me take it on. I wanted to understand what's the difference between RNN you know recurrent neural networks convolutional um neural networks and what's the best business case that our companies can use? What's the best time to use a vector database? Why is it important? Why is it needed for AI solution? I wanted to be able to articulate the difference between a RAG and Agentic AI workflow to our companies so that's really was the impass of as to why I wanted to take on this piece and why I wanted to do uh the AI foundational training. 10:08 Lois: And your journey didn't stop with you and Kay, right? Your sons are both Oracle AI-certified as well as I understand it. So, tell me a little bit about that. What inspired them? Jeffrey: So our poor boys um you know we have two boys you know both are in college uh you know and one full transparency is a computer science major at at Georgia Tech. The other one is doing a biology major at um Kennesaw State. In our household, we believe in technology and and we believe anyone can look at it. So, after getting a better understanding of AI and realizing AI is really going to impact every aspect of our our society and our industry, we said we should absolutely have our boys do this. Well, of course, with any kind of young kids, they're going to be hesitant. So um we we had to really incentivize them you know for you know for my for our youngest you know who was not you know been exposed to this technology, he was starting his new business and he wanted to learn and for our oldest being at Georgia Tech he was in that computer science major this was going to help him secure some summer internship. So what we did was to incentivize them we had to turn off the Wi-Fi and so the Wi-Fi could only be on if they were doing the certification and and full transparency after I would say a weekend and like 3 days they were able to complete the course and truly um pass and understand on a foundational level like what's the difference between RAG and Agents? What's the difference between you know RNN and CNN? What are neural networks and what's deep learning the machine learning? For my oldest, who was in computer science, it helped him secure a summer internship because he was able to talk about in a very clear way that he understood AI. And then he was also able to show his um his certification and that helped him to secure an internship with Oracle on the OCI team being a software developer. And to be honest, he's going into his third summer where he's going to be at Oracle um coming this next summer in 2026. So, it's been beneficial. I tell people like this is something that you should absolutely do and um we encourage our friends and we tell the story about our boys because it's it's personal. We show that anyone can do it. 12:35 Lois: That's that's an awesome story. And the whole family is AI certified. That's great. So, you mentioned that you've been sharing your experience with your friends and your colleagues and neighbors. What are some of the common misconceptions or fears that you encounter when you're talking about AI with people? How do you help them understand what it means for their careers and for their lives? Jeffrey: Um, no, it's a great question. You know, a lot of people I talk to still think AI is either going to replace them or that it's too technical for them to ever understand. Lois: Right. Jeffrey: And the fear usually comes from not knowing where to start. Um, I tell them that AI is really just a tool and and and learning the basics helps you to see where it fits into your work life. And and once they understand that it's it's here to help, not to replace them, the conversation shifts and become, oh, okay, now how can I become more knowledgeable so I can be less fearful and identify opportunities? So really, I've been having conversation to say, look, it is not something that's here to replace you. It is a tool and it's a tool that really once you understand how you can use it at your job or in your school work or in where you volunteer, it can really drive automation and speed and allow you to do your job much better. Lois: Yeah, that's so true. And the knowledge understanding is so powerful. It really does change people's perspective from being fearful to being excited about the possibilities with AI.  14:13 Be a part of something big by joining the Oracle University Learning Community! Connect with over 3 million members, including Oracle experts and fellow learners. Engage in topical forums, share your knowledge, and celebrate your achievements together. Discover the community today at mylearn.oracle.com. 14:34 Lois: So tell me a little bit about uh how in your private equity work um I know you interact with a wide variety of clients. How does this knowledge about Oracle's AI uh technology and having the certification empower you to have conversations and build trust with your clients? Jeffrey: The biggest value I've received from getting the Oracle AI certification is that it gives me clear and practical foundations for talking to people about what AI is and what it's not. Let's be honest, there's a lot of hype out there about AI and there's a lot of hype and fear that is unproven. You know, in in my work with private equity, clients want to know what's the real, what's possible, what's worth our investment. You know is this something that we should really look at. So when I can explain AI concepts, agentic workflow, you know, neural networks and one is important, you know, what neural networks are better for vision capabilities, what neural networks are better for audio capabilities, what neural networks are just better for for text. Right? When I can really go down to those simple terms and connect with them on the operating challenges that that companies is facing, then I have tangible case studies that I can help work with my companies on that will build credibility and this hype and fear kind of starts to subside and go away. So with that, you know, when when when working with my private equity companies, I don't want to just do something just because it's the hype. We we really need to make sure that whatever we doing can drive growth and drive IBIDA growth so that we could realize our investment thesis. So this certification really helped me to just ground it in the ways that I could have real conversations with our companies about what are the activities that are going to drive growth, what are the activities that's going to be efficient, what are the activities that are going to have value creation for our company. and it's been something that you know has really been helpful. So, another thing I wanted to share is Kay and I have been working with not only, you know, digging it to enterprises, but I want to take it to universities and we've been working with her mother's alma mater, Alabama State, which is a historically black college and university, to help them get on Oracle AI and then get their foundation going because we want to take this down to the college level and help to drive this and offer it. Through that interaction, they've reached out to the city of uh Montgomery and they want to work with the public schools to start getting the school system to start becoming AI foundation um certified and understand how AI can evolve in everything that you do. So, we've been working with them. We actually had a quick event here that Oracle did um at here in Atlanta and they were able to attend and see some of the application and we're hoping to just continue this. So it it's not something that I'm just talking to my private equity companies about. I'm also want to bring this into universities, bring this into the school because it's a fundamentally different way to solve problems and anyone can do it. You don't have to have a technical background. We're at a foundationally different level where anyone can start their AI journey. 18:05 Lois: Right. And we're just at the beginning of this transformation of the industry. It's a great way to teach the next generation how to be prepared so they can have uh you know great careers and leveraging AI. So, one of the things you've mentioned to me when we've talked in the past is that you boil down AI to two things, data and math, right? Not innovation itself but a tool. So can you elaborate a little bit on that? Jeffrey: Yeah, it's one of the the things I like to say. I think if people talk to me and they say, you know, Jeff always boils it down. So, you know, when I look at it, generative AI foundation is based on the concept of machine learning and deep learning.  Lois: Right. Jeffrey: Um both concepts are based on linear algebra, calculus, probability, statistics, optimization theory. You know those are some of the the the foundation of both of those. LLMs use these foundations and data to generate content and execute tasks. So people's actions in system generate the data that these LLMs use and and math follows specific patterns such as Bayer's theorem, Pythagorean theorem. The innovation that comes from those because you have math in terms of the machine learning and you have data requires thinking out of the box and not following one of these pattern, which is only accomplished through people and our unique experience. So when I think of generative AI that's why I see it as a tool. You're always going to require human interaction to drive an outcome.  Lois: Right. Jeffrey: It it is a combination of math and data. Our unique experience of how we engage and how we look at a problem brings innovation to a challenge. So that's one of the things I always say it's I boils it down to it's math and data. Innovation comes from people. And the reason why it comes from people is we all have unique experiences, unique backgrounds. So we look at a problem differently in terms of how we solve it and that difference is what drives the innovation. Lois: Right. And just leverages AI to do so. Jeffrey: Correct. 20:20 Lois: So you've said that AI levels the playing field. What does that mean to you in practical terms and how have you seen it make an impact in your area of expertise? Jeffrey: When I say level the playing ground, what I mean is there's a unique opportunity where this technology is impacting every industry that we know. Prior to this, you know, if there was a technology solution such as, let's look at the big ones, cloud, everyone moving to the cloud, it required you to have some knowledge of cloud technology. Big data it required you to have some knowledge of data solutions. AI is so transformational that you know if we look take a look at vibe coding that's out there. Your ability to think about a problem and break it down in a in a tangible way and build an app and leverage vibe coding where the LLM can actually do the hard work for you is transformational. It doesn't require you to have that knowledge to drive it. Now to take some and to and and that what what does that do? That allows you to quickly take a business idea from concept all the way to an MVP and then you can then move that into production and and and start making money on whatever that idea is. Does that take you 100% away? No. You're still going to need someone to run it and all of that. But what what I love about it is a lot of individuals have many different ideas and many different concepts. You can now quickly materialize those into a technology solution without having to have a technology background because the hard work of executing that code can be handled by an LLM. That's just one example if we just talk about coding. If you look at other industries such as the legal industry that is doing a lot of stuff around um just looking at how can you quickly process documents and read those, it's really revolutional. So what what I mean by it being transformational, it enhances each industry differently. So therefore, it's not that you have to have a technology background. If you're willing to take it on and look at it as a tool, then we are all at the beginning stage. And to be honest, I'll go as far as saying, Lois, if you don't have a technical background, you're actually at an advantage because you don't have to unlearn some of the activities that you used to solve problem with. You actually can come up with new ways leveraging AI agentic workflow to solve those problems quicker. So that's why I really feel like we are at a level a level playing field and it's a transformational piece and I'm encouraging as many people to just start becoming familiar with the different tools that are out there. Get you yourself a ChatGPT account, start working with Anthropic Claude, get yourself a Gemini account, start working with their notebook LLMs to generate, you know, um, infographics. It's amazing. And that's the new thing that I'm playing with right now. Start using these tools because what's happening is as you understand them, your creativity is going to say, "Oh, I can now do this." Uh, mark my word. I think this is going to be one of the pivotal era that we look back and say, "If I had taken full advantage of AI when it came out, I would have started this many businesses." And I don't want people to have that regret. So that's why I think you know dismiss the fear. You do not have to have a technology background to start AI. You can do that now. You can take your business ideas from concept to MVP, sell it to investors to get an investment to take it to production, and hopefully make the winnings that you want with your ideas. So I'm I'm I'm super excited about where we are as a society because I think this is a huge opportunity. Lois: Yeah, I agree with you. I think we're we're witnessing a transformation uh revolution in in so many different ways and the cross industry applications are just you know mind-blowing. Jeffrey: Yeah. 24:36 Lois: So for somebody who might be intimidated about pursuing an AI or OCI certification you just mentioned how you would encourage them you know to get started anyway. What advice would you offer? How would you recommend that they get started? Jeffrey: So first of all I would say go to Oracle University. Lois: Thank you. Jeffrey: You know I check out their courses. You know the thing that I would say that I like about um the courses there is it's self-paced. It's easily easy to absorb and then it goes deep into whatever topic you want. So, it starts off very high level to give you the background of what you need, but it goes really deep if there's something that you want to go in on. That's that's the first thing. The other piece that I love about it is the courses not only just have talking points, but they have hands-on labs that you can actually put to action the content that you just learned. So one of those hands-on lab with the lab is based on Oracle Live Labs and a little plug for my wife. Oracle Live Labs was created by Kay. I remember when she was here at home building this almost three four five years ago and it's amazing to see the coursework that they have. They have so many different hands-on labs that they can do. So, I would say because of the combination of this great structured content, the ability to then have the hands-on lab through Live Lab that you can then put into action the things that you you you've learned, then it's a quick and tangible way to just receive content and actually test it out. And, you know, to watch Live Labs grow, to see where it is. I'm just I'm I'm excited for her. I'm proud. I know it's one of her her passion. She always says it's it's her her gift to developers is Live Labs because as an engineer myself I can't just hear something and learn it. I have to put it to action. So I think that combination of Oracle University having the content and then having mechanisms like Live Lab to do hands-on is why people should go there and start and then some of the courses you guys have they're free. Lois: Absolutely. Jeffrey: I wouldn't do that. So if they're free, like let me go ahead and start it now and then as I go up, you know, even if there's a charge, like there's a benefit. So you guys have offered such a low entry um um hurdle to start that I don't see why you wouldn't just start there. Lois: And all of our OCI training is free as well as the foundations associate certification. So you're right, there's there's no barrier to entry for sure. Jeffrey: Mhm. 27:13 Lois: Well, Jeffrey, I want to thank you so much for sharing your journey with me today. Your enthusiasm, your experience, and your expertise has just really been inspiring and um I've just been really happy to hear about how this has not only impacted your career, but also your outlook on the industry and um influence the people around you. So, thank you again. I really appreciate it. Jeffrey: Anytime. I'm excited that I was able to share my journey and I hope everyone, you know, starts their own. So excited. Thank you. Lois: Thank you. 27:54 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

An airhacks.fm conversation with Thomas Wuerthinger (@thomaswue) about: clarification of GraalVM release cadence changes and decoupling from openJDK releases, GraalVM focusing on LTS Java releases only (skipping non-LTS like Java 26), GraalVM as a multi-vendor polyglot project with community edition and third-party vendors like Red Hat BellSoft and microdoc, increased focus on python support due to AI popularity, GraalVM team alignment with Oracle Database organization, Oracle Multilingual Engine (MLE) for running JavaScript and Python in Oracle Database, MySQL MLE integration, native image support for stored procedures in Oracle Database, shipping lambda functions from client applications to database for temporary execution, treating Oracle Database as an operating system for running business logic, serverless workloads directly in Oracle Database, application snapshotting similar to CRaC but running in user space without kernel privileges, efficient scale-to-zero capabilities with native images, Oracle REST Data Services service generalization for serverless execution platform, database triggers for workflow systems and application wake-up, durable functions with transactional state storage in Oracle Database, comparison to AS400 architecture with transaction manager database and operating system in same memory, memory price increases making GraalVM native image more attractive, lower memory consumption benefits of native image beyond just startup time, CPU-based inference support with SIMD and Vector API, TornadoVM for GPU-based inference built on Graal compiler, WebAssembly compilation target for native images, edge function deployment with WebAssembly, Intel memory protection keys for sandboxed native image execution, native image layers for shared base libraries similar to docker layers, profile-guided optimizations for size reduction, upx binary compression for 3x size reduction, memory savings from eliminated class metadata and profiling data not garbage collector differences, 32-bit object headers in serial GC smaller than HotSpot, polyglot integration allowing Python and JavaScript embedding in Java applications, Micronaut framework compile-time annotation processing, quarkus framework best alignment with native image for smallest binaries, GraalVM roadmap focused on database synergies and serverless innovation Thomas Wuerthinger on twitter: @thomaswue

Every system depends on reliable infrastructure behind the scenes. Oracle Cloud Infrastructure (OCI) delivers that reliability with speed, flexibility, and built-in security.   Join Lois Houston and Nikita Abraham as they speak with Oracle Cloud experts David Mills and Tijo Thomas about what makes OCI different and how it drives real results for businesses of every size.   Cloud Business Jumpstart https://mylearn.oracle.com/ou/course/cloud-business-jumpstart/152957 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   -----------------------------------------------   Episode Transcript:   00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Lois: Hello and welcome to the Oracle University Podcast! I'm Lois Houston, Director of Communications and Adoption with Customer Success Services, and with me is Nikita Abraham, Team Lead: Editorial Services with Oracle University. Nikita: Hi everyone, and welcome to a brand-new season of the podcast! We're really excited about this one because we'll be diving into how Oracle Cloud Infrastructure is transforming the way businesses innovate, stay secure, and drive results.  00:55 Lois: And to help us with this, we've got two experts who know this space inside out—David Mills, Senior Principal PaaS Instructor, and Tijo Thomas, Principal OCI Instructor, both from Oracle University. Hi David! For those who might not be familiar, could you explain what Oracle Cloud Infrastructure is? David: OCI, as we call it, is Oracle's enterprise grade cloud platform, built from the ground up to run the systems that matter most to business. It provides the infrastructure and platform services businesses need to build, run, and scale applications securely, globally, and cost effectively. To provide more context, all of Oracle's SaaS applications such as NetSuite, Customer Experience, Human Capital Management, Supply Chain Management, as well as Enterprise Resource and Enterprise Performance Management, they all run on OCI. But OCI isn't just for Oracle's own apps. It's a full featured cloud platform used by thousands of customers to run their own applications, data, and services. OCI includes platform services such as databases, integration, analytics, and many others, and of course, the infrastructure services, such as compute, networking, and storage, which comprise the core of OCI. Bottom line, if something is running on Oracle Cloud, OCI is behind it. OCI includes over 100 services across numerous categories like compute, storage, networking, database, containers, AI, developer tools, integration, security, observability, and much more. So, whether you're lifting and shifting legacy workloads or building new apps in the cloud, OCI has the building blocks. 03:02 Lois: David, who was OCI designed for? David: OCI was built from scratch to address the limitations of first-generation clouds. No patchwork of legacy acquisitions, just a clean, modern, high-performance foundation designed for real enterprise workloads. OCI was designed for businesses that can't compromise financial services, health care, retail, governments, customers with strict regulations, global scale, and mission-critical systems. These are the companies choosing OCI not just because it works, but because it works under pressure. 03:42 Nikita: What else makes OCI different from other cloud platforms? David: Oracle's network and storage architecture delivers low latency results consistently. Then there's pricing—simple, predictable, and often much lower than our competitors. OCI was designed with governance and security in every layer. OCI supports all types of cloud strategies: public cloud, hybrid deployments, multi-cloud environments, and even a dedicated cloud we can install inside your own data center. We call all that distributed cloud, and that's where OCI really shines. OCI gives you everything you need to modernize your technology stack, run securely at scale, and build for the future without giving up control or blowing your budget. 04:37 Lois: Now, Tijo, we've covered what OCI is, who it's for, and what makes it unique. Let's switch gears a bit and talk about cloud regions. For anyone who doesn't know, a cloud region is just a specific geographic location where Oracle, or any cloud provider, runs its own data centers. Why does the choice of region matter for businesses, and what should they think about when picking one? Tijo: Many businesses are required by law to keep their data within national borders, whether it is GDPR in Europe or local privacy laws in Australia or Singapore, choosing the right region would help you to stay compliant.  The closer your applications are to your users, the faster they perform. Running in a nearby region means lower latency, faster response times, and better customer experience. Then there is disaster recovery and high availability. Regions are the building blocks for setting up failover strategies. By deploying workloads in multiple regions, businesses can protect themselves from outages and keeping their systems in running state. Some businesses also need to meet industry-specific compliance requirements. Think of sectors like health care, government, or finance. They often require that the infrastructure and the data should stay within the national or regional boundaries. If your business is growing into new markets, regions allow you to deploy apps and services closer to your customers and without having the need to build new data centers. Regions also enable local integrations and partnerships, whether it is connecting with ISPs, local service providers, or complying with in-country partner requirements. Having a region nearby makes that integrations and operations smoother. Regions are not just about geography. They are a critical part of how the businesses would stay compliant, resilient, and responsive across the globe. Oracle runs a fast-growing global network of cloud regions, and each OCI region is fully independent and fully isolated. You choose your regions, and your data stays there. 07:06 Nikita: And are there different types of cloud regions? Tijo: There are several commercial regions, sovereign regions, government regions, and multi-cloud regions. Even with a wide range of cloud regions, some organizations cannot move their workloads and its data to the public cloud. Those workloads may need to stay in their own on-premises data center, but at the same time, they still want to leverage the benefits of OCI. 07:42 Take your cloud skills to the next level with the new Oracle Database@AWS course. Master provisioning, migration, security, and high availability for Oracle Database on AWS. Then validate your experience with an industry-recognized certification. Stand out in the multicloud space and accelerate your career. Visit mylearn.oracle.com for more information. 08:09 Nikita: Welcome back! We were talking about workloads and how some companies may have to keep their workloads on-premises. Why would they need to do that, Tijo? Tijo: First, data sovereignty. Let's say there may not be a list of public cloud region that the organization is looking for, or maybe the business need to set up a disaster recovery strategy within that specific location. Then there is security and control. Some industries have very strict regulations, and they require physical access and oversight of their infrastructure. And finally, there are latency-sensitive workloads. These are applications that cannot afford the delay of going back and forth to a remote cloud region. They need cloud services right next to their physical data center.  08:59 Nikita: So, how does Oracle help with that? Tijo: To address these requirements, Oracle introduces a set of offerings. The first one is called dedicated region, and the second one is called Cloud@Customer services. Through both these offerings, you get OCI services right in your data center and all behind your firewall, while achieving the benefits of flexibility and automation.  09:24 Nikita: So, what's a dedicated region? Tijo: Dedicated region is a completely managed cloud region that brings all the OCI services and Oracle Fusion SaaS applications within your data centers. Along with deploying the full stack OCI, you would receive support for Oracle Fusion SaaS applications and also gain a consistent experience with the same SLAs, APIs, and the tools available in Oracle Cloud. 09:53 Lois: Ok and what about Cloud@Customer? Tijo: While dedicated region is ideal for large scale enterprise needs, with full stack OCI and SaaS, some organizations just require a lighter footprint. And that's where Cloud@Customer comes in. And to begin with, we'll talk about Compute Cloud@Customer. It is a fully managed rack scale infrastructure that allows you to use the core OCI services, like the OCI compute, OCI storage, and OCI networking services at your on-premises. With Compute Cloud@Customer, you can run applications and middleware systems to provide consistent user experience and simplify IT administration across your distributed cloud architecture. We can plan to run the same application stack everywhere and centrally manage them without needing experts in every location.  10:52 Nikita: Is there a way to make running your Oracle databases easier and more cost-effective? Tijo: That's why Oracle offers you Oracle Exadata Cloud@Customer. Oracle Exadata Cloud@Customer combines the performance of Oracle Exadata with the simplicity, flexibility, and affordability of a managed database service delivered through customer data centers. It is the simplest way to move your current Oracle databases to the cloud, because it provides full compatibility with existing Exadata systems and Exadata Database services in Oracle Cloud Infrastructure. You could also run the fully-managed Oracle Autonomous Database on Exadata Cloud@Customer that would combine all the benefits of having Exadata, along with the simplicity of an autonomous cloud service. And when Compute Cloud@Customer is combined with Exadata Cloud@Customer, you can run full stack applications completely in your own data center. Applications will use the same high performance OCI compute and database services you get in the cloud, so you don't have to change the way you architect or deploy them.  12:09 Nikita: So, what you're saying is that Oracle dedicated region and Cloud@Customer bring OCI services into your data center. Tijo: It enables you to run applications faster using the same high-performance capabilities and autonomous operations. You get all of this while maintaining complete control of your data so that you can address data residency, security, and connectivity concerns.  12:35 Lois: Ok. We've talked about where OCI runs. Now David, let's get into what it actually does. David: OCI compute lets you run business applications on demand without buying or managing physical servers. You choose the type and size of the virtual machine you want, and OCI handles the rest. Need more power for peak traffic? OCI can automatically add capacity and scale it back down after. In addition to virtual machines, bare metal servers are also available for ultra high performance jobs like simulations, AI, or high speed trading. Every business stores data, but not all data needs the same kind of storage. OCI gives you options, fast block storage for your compute servers. It works just like a hard drive for your home computer. Shared file storage for applications and microservices. Large scale object storage for backups, videos, or other data, and low-cost long-term storage for object archives. The system even moves rarely used data to cheaper storage automatically.  13:51 Lois: Given Oracle's expertise in databases, what are some of the database options businesses can access with OCI? David: Oracle Autonomous Database automatically patches, tunes, and scales itself. Need raw power? Use Oracle Exadata, or go open source with MySQL HeatWave, which can be used for real time analytics. With these and many other database options, you get high performance automation and reliability all on demand.  14:24 Nikita: With so many database options, how is everything kept connected and running smoothly on OCI? David: Every cloud service relies on a fast, secure network. OCI's Virtual Cloud network acts like your own private data highway. You control how traffic flows between your apps, your people, and your regions. Need private direct connections to your data center or office? Use OCI FastConnect to bypass the public internet. OCI networking provides high speed performance with enterprise grade security designed for global business. 15:05 Lois: And what security service does Oracle provide? David: OCI doesn't treat this as an optional add on. When you sign up for OCI, your environment is isolated, your data is encrypted, and admin actions are logged. And there are so many security services. Identity and Access Management for handling users and permissions, Cloud Guard to detect threats and misconfigurations, OCI Vault for managing your encryption keys, Data Safe to monitor sensitive data access, as well as many others. You can leverage to meet any government or business compliance requirement. All of these are included in OCI, no need to stitch together third-party tools. 15:55 Lois: What if I want to see what's going on in my environment? David: OCI has monitoring services for metrics, logging services for real-time insights, tracing for distributed applications, and alarms to notify you when things go sideways. All of these services are integrated. So you can see what matters when you need it without all the noise. 16:23 Nikita: David, let's say someone wants to build and deploy an app. What services does OCI offer them?  David: OCI provides numerous developer services for your teams to build apps or digital tools. OCI DevOps supports automated builds and deployments. OCI Container Engine for Kubernetes helps run microservices. OCI Functions supports serverless code that runs on demand. All of this works with familiar languages and frameworks. In short, OCI gives developers what they need to build, test, and deliver quickly without having to manage infrastructure. 17:03 Nikita: How does OCI make it easier for companies to bring their apps together and use AI, even if they don't have a dedicated AI team? David: Modern businesses run dozens of apps, and OCI helps you to connect them with Oracle Integration Cloud. With OIC, you can integrate SaaS applications as well as on-premise apps and systems, automate business processes and workflows, route and transform messages, and you can even expose key services as APIs so partners and systems can interact securely. OCI integration is the glue that holds modern IT together. OCI helps you turn data into decisions without needing an AI team. Use ready-made AI tools for language translation, image recognition, document understanding, speech transcription, and more. Or build your own models with data science and data flow services. It's all designed to bring machine learning into reach for every business. 18:10 Lois: Thank you, David and Tijo, for joining us on this episode of the Oracle University Podcast. If you want to learn more about OCI, visit mylearn.oracle.com and search for the Cloud Business Jumpstart course.  Nikita: Next week, we'll look at why businesses choose OCI and how they're using OCI services to create real outcomes. Until then, this is Nikita Abraham… Lois: And Lois Houston signing off! 18:38 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

This week, hosts Lois Houston and Nikita Abraham are shining a light on multicloud, a game-changing strategy involving the use of multiple cloud service providers. Joined by Senior Manager of CSS OU Cloud Delivery Samvit Mishra, they discuss why multicloud is becoming essential for businesses, offering freedom from vendor lock-in and the ability to cherry-pick the best services. They also talk about Oracle's pioneering role in multicloud and its partnerships with Microsoft Azure, Google Cloud, and Amazon Web Services.   Oracle Cloud Infrastructure Multicloud Architect Professional: https://mylearn.oracle.com/ou/course/oracle-cloud-infrastructure-multicloud-architect-professional-2025-/144474 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, and the OU Studio Team for helping us create this episode.   ------------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Lois: Welcome to the Oracle University Podcast! I'm Lois Houston, Director of Communications and Adoption with Customer Success Services, and with me is Nikita Abraham, Team Lead: Editorial Services with Oracle University.   Nikita: Hi everyone! You're listening to our Best of 2025 series, where over the next few weeks, we're revisiting four of our most popular episodes of the year.      Lois: Today is #2 of 4, and we're throwing it back to an episode with Senior Manager of CSS OU Cloud Delivery Samvit Mishra. This episode was all about shining a light on multicloud, a game-changing strategy involving the use of multiple cloud service providers.     01:07 Nikita: That's right, Lois. Oracle has been an early adopter of multicloud and a pioneer in multicloud services. So, we began that conversation by asking Samvit to explain what multicloud is and why someone would need more than one cloud provider.  Samvit: Multicloud is a very simple, basic concept. It is the coordinated use of cloud services from more than one cloud service provider.  01:30 Nikita: But why would someone want to use more than one cloud service provider? Samvit: There are many reasons why a customer might want to leverage two or more cloud service providers. First, it addresses the very real concern of mitigating or avoiding vendor lock-in. By using multiple providers, companies can avoid being tied down to one vendor and maintain their flexibility. 01:53 Lois: That's like not putting all your eggs in one basket, so to speak. Samvit: Exactly. Another reason is that customers want the best of breed. What that means is basically leveraging or utilizing the best product from one cloud service provider and pairing it against the best product from another cloud service provider. Getting a solution out of the combined products…out of the coordinated use of those services.  02:22 Nikita: So, it sounds like multicloud is becoming the new normal. And as we were saying before, Oracle was a pioneer in this space. But why did we embrace multicloud so wholeheartedly? Samvit: We recognized that our customers were already moving in this direction. Independent studies from Flexera found that 89% of the subjects of the study used multicloud. And we conducted our own study and came to similar numbers. Over 90% of our customers use two or more cloud service providers.  HashiCorp, the big infrastructure as code company, came to similar numbers as well, 94%. They basically asked companies if multicloud helped them advance their business goals. And 94% said yes. And all this is very recent data.  03:13 Lois: Can you give us the backstory of Oracle's entry into the multicloud space? Samvit: Sure. So back in 2019, Oracle and Microsoft Azure joined forces and announced the interconnect service between Oracle Cloud Infrastructure and Microsoft Azure. The interconnect was between Oracle's FastConnect and Microsoft Azure's ExpressRoute. This was a big step, as it allowed for a direct connection between the two providers without needing a third-party. And now we have several of our data centers interconnected already. So, out of the 48 regions, 12 of them are already interconnected. And more are coming. And you can very easily configure the interconnect.  This interconnectivity guarantees low latency, high throughput, and predictable performance. And also, on the OCI side, there are no egress or ingress charges for your data.  There's also a product called Oracle Database@Azure, where Oracle and Microsoft deliver Oracle Database services in Microsoft Azure data centers.  04:20 Lois: That's exciting! And what are the benefits of this product? Samvit: The main advantage is the co-location. Being co-located with the Microsoft Azure data center offers you native integration between Azure and OCI resources. No manual configuration of a private interconnect between the two providers is needed. You're going to get microsecond latency between your applications and the Oracle Database.  The OCI-native Exadata Database Service is available on Oracle Database@Azure. This enables you to get the highest level of Oracle Database performance, scalability, security, and availability. And your tech support can be provided either from Microsoft or from Oracle.  05:11 AI is being used in nearly every industry…healthcare, manufacturing, retail, customer service, transportation, agriculture, you name it! And it's only going to get more prevalent and transformational in the future. It's no wonder that AI skills are the most sought-after by employers. If you're ready to dive in to AI, check out the OCI AI Foundations training and certification that's available for free! It's the perfect starting point to build your AI knowledge. So, get going! Head on over to mylearn.oracle.com to find out more.  05:51 Nikita: Welcome back. Samvit, there have been some new multicloud milestones from OCI, right? Can you tell us about them?  Samvit: That's right, Niki. I am thrilled to share the latest news on Oracle's multicloud partnerships. We now have agreements with Microsoft Azure, Google Cloud, and Amazon Web Services.  So, as we were discussing earlier, with Azure, we have the Oracle Interconnect for Azure and Oracle Database@Azure. Now, with Google Cloud, we have the Oracle Interconnect for Google Cloud. And it is very similar to the Oracle Interconnect for Azure. With Google Cloud, we have physically interconnected data centers and they provide a sub-2 millisecond latency private interconnection. So, you can come in and provision virtual circuits going from Oracle FastConnect to Google Cloud Interconnect.  And the best thing is that there are no egress or ingress charges for your data. The way it is structured is you have your Oracle Cloud Infrastructure on one side, with your virtual cloud network, your subnets, and your resources. And on the other side, you have your Google Cloud router with your virtual private cloud subnet and your resources interconnecting.  You initiate the connectivity on the Google Cloud side, retrieve the service key and provide that service key to Oracle Cloud Infrastructure, and complete the interconnection on the OCI side. So, for example, our US East Ashburn interconnect will match with us-east4 on the Google Cloud side.  07:29 Lois: Now, wasn't the other major announcement Oracle Database@Google Cloud? Tell us more about that, please. Samvit: With Oracle Database@Google Cloud, you can run your applications on Google Cloud and the database inside the Google Cloud platform. That's the Oracle Cloud Infrastructure database co-located in Google Cloud platform data centers. It allows you to run native integration between GCP and OCI resources with no manual configuration of private interconnect between these two cloud service providers.  That means no FastConnect, no Interconnect because, again, the database is located in the Google Cloud data center. And you're going to get microsecond latency and the OCI native Exadata Database Service. So, you're going to gain the highest level of Oracle Database performance, scalability, security, and availability.  08:25 Lois: And how is the tech support managed? Samvit: The technical support is a collaboration between Google Cloud and Oracle Cloud Infrastructure. That means you can either have the technical support provided to completion by Google Cloud or by Oracle. One of us will provide you with an end-to-end solution.  08:43 Nikita: During CloudWorld last year, we also announced Oracle Database@AWS, right?  Samvit: Yes, Niki. That's where Oracle and Amazon Web Services deliver the Oracle Database service on Oracle Cloud Infrastructure in your AWS data center. This will provide you with native integration between AWS and OCI resources, with no manual configuration of private interconnect between AWS and OCI. And you're getting microsecond latency with the OCI-native Exadata Database Service.  And again, as with Oracle Database@Google Cloud and Oracle Database@Azure, you're gaining the highest level of Oracle Database performance, scalability, security, and availability. And the technical support is provided by either AWS or Oracle all the way to completion. Now, Oracle Database@AWS is currently available in limited preview, with broader availability in the coming months as it expands to new regions to meet the needs of our customers.  09:49 Lois: That's great. Now, how does Oracle fare when it comes to pricing, especially compared to our major cloud competitors?  Samvit: Our pricing is pretty consistent. You'll see that in all cases across the world, we have the less expensive solution for you and the highest performance as well.  10:06 Nikita: Let's move on to some use cases, Samvit. How might a company use the multicloud setup? Samvit: Let's start with the split-stack architecture between Oracle Cloud Infrastructure and Microsoft Azure.  Like I was saying earlier, this partnership dates back to 2019. And basically, we eliminated the FastConnect partner from the middle. And this will provide you with high throughput, low latency, and very predictable performance, all of this on highly available links. These links are redundant, ensuring business continuity between OCI and Azure.  And you can have your database on the OCI side and your application on Microsoft Azure side or the other way around. You can have SQL Server on Azure and the application running on Oracle Cloud Infrastructure. And this is very easy to configure.  10:55 Lois: It really sounds like Oracle is at the forefront of the multicloud revolution. Thanks so much, Samvit, for shedding light on this exciting topic.  Samvit: It was my pleasure.  Nikita: That's a wrap for today. To learn more about what we discussed, head over to mylearn.oracle.com and search for the Oracle Cloud Infrastructure Multicloud Architect Professional course.  Lois: We hope you enjoyed that conversation. Join us next week for another throwback episode. Until then, this is Lois Houston...   Nikita: And Nikita Abraham, signing off!   11:26 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

In today's Cloud Wars Minute, I take a look at how Oracle's bold multicloud partnerships — with Microsoft, AWS, and Google Cloud.Highlights00:15 — One of the ways in which Oracle has been distinguishing itself is not just with its new technology, but with interesting go-to-market approaches. Now, Ellison recently said that while Oracle's multicloud business, where its three competitors, Microsoft, AWS, and Google Cloud, all offer the Oracle Database to their customers, that revenue was up over 1,500%.01:11 — He said so far, almost all of that growth has been generated by the Microsoft partnership because it was the first to come on board. Ellison believes that as the AWS partnership and Google get up to speed — and they get all the infrastructure set up to support that — you'd think that's going to drive a new round of growth for the Oracle Database business.02:12 — Can the Oracle Database hit $20 billion in revenue in five years? Ellison seemed bullish on that. One reason is the new Oracle AI Database, purpose-built for the AI Revolution. Second is these multicloud partnerships. There's such a demand among customers who have wanted the Oracle Database but have felt trapped using Microsoft Azure, AWS, or Google Cloud.03:15 — The AI reasoning, which Ellison was calling it, also known as inferencing, is something a lot of companies are going to be doing when they take these new tools and say, “How do I suit this for my retail company or my clothing company or my trucking company?” That's where, Ellison said, everybody's going to want to do this. He sees massive demand for it.04:32 — In a full-length article that I have today on CloudWars.com, I offer four specific points on why this approach that Ellison led with Oracle — and that the others fully agreed to — is so important. It's a great trend moving forward in the direction of more capability, more choice, more power in the hands of customers here in the buyer-seller equation. Visit Cloud Wars for more.

In this episode, hosts Lois Houston and Nikita Abraham team up with Senior Principal OCI Instructor Sergio Castro to unpack the basics of cloud networking and the Domain Name System (DNS). You'll learn how local and virtual networks connect devices, and how DNS seamlessly translates familiar names like oracle.com into addresses computers understand.   Cloud Tech Jumpstart: https://mylearn.oracle.com/ou/course/cloud-tech-jumpstart/152992 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ------------------------------------------------ Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Lois: Hello and welcome to the Oracle University Podcast! I'm Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services. Nikita: Hi everyone! For the last few weeks, we've been talking about different aspects of cloud data centers. Today, we're focusing on something that's absolutely key to how everything works in the cloud: networking and domain name systems.  00:52 Lois: And to guide us through it, we've got Sergio Castro, Senior Principal OCI Instructor at Oracle University. We'll start by trying to understand why networking is so crucial and how it connects everything behind the scenes. Sergio, could you explain what networking means in simple terms, especially for folks new to cloud tech? Sergio: Networking is the backbone of cloud computing. It is a fundamental service because it provides the infrastructure for connecting users, applications, and resources within a cloud environment. It basically enables data transfers. It facilitates remote access. And ensures that cloud services are accessible to users. This provided that these users have the correct credentials.  01:38 Nikita: Ok, can you walk us through how a typical network operates? Sergio: In networking, typically starts with the local area network. Basically, networking is a crucial component for any IT service because it's the foundation for the architecture framework of any of the services that we consume today. So, a network is two or more computers interconnected to each other. And not necessarily it needs to be a computer. It can be another device such as a printer or an IP TV or an IP phone or an IP camera. Many devices can be part of a local area network. And a local area network can be very small. Like I mentioned before, two or more computers, or it could grow into a very robust and complicated set of interconnected networks. And if that happens, then it can become very expensive as well. Cloud networking, it's the Achilles heel for many of the database administrators, programmers, quality assurance engineers, any IT other than a network administrator. Actually, when the network starts to grow, managing access and permissions and implementing robust security measures, this coupled with the critical importance of reliable, and secure performance, can create significant hurdles. 03:09 Nikita: What are the different types of networks we have? Sergio: A local area network is basically in one building. It covers… it can be maybe two buildings that are in close proximity in a small campus, but typically it's very small by definition, and they're all interconnected to each other via one router, typically. A metropolitan area network is a typical network that spans into a city or a metro area, hence the name metropolitan area network. So, one building can be on one edge of the city and the other building can be at the other edge of the city, and they are interconnected by a digital circuit typically. So that's the case. It's more than one building, and the separation of those buildings is considerable. It can go into several miles.  And a wide area network is a network that spans multiple cities, states, countries, even international. 04:10 Lois: I think we'll focus on the local area network for today's conversation. Could you give us a real-world example, maybe what a home office network setup looks like? Sergio: If you are accessing this session from your home office or from your office or corporate office even, but a home office or a home network, typically, you have a router that is being provided to you by the internet vendor—the internet service provider. And then you have your laptop or your computer, your PC connected to that router. And then you might have other devices either connected via cable—ethernet cable—or Wi-Fi. And the interconnectivity within that small building is what makes a local area network. And it looks very similar once you move on into a corporate office. Again, it's two or more computers interconnected. That's what makes a local area network. In a corporate office, the difference with a home office or your home is that you have many more computers. And because you have many more computers, that local area network might be divided into subnets. And for that, you need a switch. So, you have additional devices like a switch and a firewall and the router. And then you might have a server as well. So that's the local area network. Two or more computers. And local area networks are capable of high speeds because they are in close proximity to each other.  05:47 Nikita: Ok… so obviously a local area network has several different components. Let's break them down. What's a client, what's a server, and how do they interact? Sergio: A client basically is a requester of a service. Like when you hop into your browser and then you want to go to a website, for example, oracle.com, you type www.oracle.com, you are requesting a service from a server. And that server typically resides in a data center like oracle.com under the Oracle domain is a big data center with many interconnected servers. Interconnected so they can concurrently serve multiple millions of requests coming into www.oracle.com at the same time. So, servers provide services to client computers. So basically, that's the relation. A client requests a service and the server provides that service.  06:50 Lois: And what does that client-server setup actually look like? Sergio: So, let's continue with our example of a web browser requesting a service from a web server. So, in this case, the physical computer is the server. And then it has a software running on it. And that makes it a web server. So, once you type www.oracle.com, it sends the request and the request is received. And provided that everything's configured correctly and that there are no typos, then it will provide a response and basically give the view of the website. And that's obviously in the local area network, maybe quality assurance when they were testing this for going live. But when it goes live, then you have the internet in the middle. And the internet in the middle then have many routers, hubs, switches. 07:51 Transform the way you work with Oracle Database 23ai! This cutting-edge technology brings the power of AI directly to your data, making it easier to build powerful applications and manage critical workloads. Want to learn more about Database 23ai? Visit mylearn.oracle.com to pick from our range of courses and enroll today!   08:16 Nikita: Welcome back! Sergio, would this client-server model also apply to my devices at home? Sergio: In your own local area network, you have client server even without noticing. For example, let's go back to our home office example. What happens if we add another laptop into the scenario? Then all of these devices, they need a way for them to communicate. And for that, they have an IP address. And who provides that IP address? The minute that you add, the other device is going to send a request to the router. The router, we call it router, but it has multiple functions like the mobile device, the handheld device that we call smartphone. It has many functions like camera and calendar and many other functionalities. The router has an additional functionality called the dynamic host configuration protocol at DHCP server. So basically, the laptop requests, hey, give me an IP address, and then the router or the DHCP server replies, here's your IP address. And it's going to be a different one. So, they don't overlap. So that's an example of client server. 09:32 Lois: And where do virtual networks fit into all this?  Sergio: A virtual network is basically, a software version of the physical network. It looks and feels exactly as a physical network does. We do have a path or a communication, in this case, in the physical network, you have either Wi-Fi or you have internet cable. And then you add your workstations or devices on top of that. And then you might create subnets.  So, in a software-defined network or in a virtual network, you have a software-defined connectivity, physical cable and all of that. Everything is software-defined. And it looks exactly the same, except that everything is software. In a software or a virtual network, you can communicate with a physical network as if that software or that virtual network was another physical network. Again, this is a software network or a software-defined network, a virtual network, no longer a physical network.  10:42 Lois: Let's switch gears a little and talk about Domain Name Systems. Sergio, can you explain what DNS is, and why it's important when we browse the web? Sergio: DNS is the global database for internet addressing. The DNS plays a very important role on the internet. And many internet services are closely related to DNS. The main functionality of DNS is to translate easy-to-remember names into IP addresses. Some IP addresses might be very easy to remember. But however, if you have many of them, then it's easier to remember oracle.com or ucla.edu or navy.mil for military or eds.org for organization or gobierno.mx for Mexico. So that's the main feature of the DNS. It's very similar to a mobile phone to the contacts application in your mobile phone, because the contacts application maps names to phone numbers. It's easier to remember Bob's phone than 555-123-4567. So, it's easier to remember the name of the persons in your contacts list, like it is easier to remember, as previously mentioned, oracle.com than 138.1.33.162. Again, 138.1.33.162 might be easy for you to remember if that's the only one that you need to remember. But if you have 20, 40, 50, like we do with phone numbers, it's easier to remember oracle.com or ucla.edu. And this is essential, this mapping, again, because we work with names it's easier for us to remember. However, the fact is that computers, they still need to use IP addresses. And remember that this is the decimal representation of the binary number. It's a lot harder for us to remember the 32 bits or each one of the octets in binary. So that's the main purpose of DNS. Now the big difference is that the contact list in a cell phone is unique to that individual phone. However, DNS is global. It applies to everybody in the world. Anybody typing oracle.com will translate that into 138.1.33.162. Now this is an actual IP address of oracle.com. Oracle.com has many IP addresses. If you ping oracle.com, chances are that this is one of the many addresses that maps to oracle.com. 13:35 Nikita: You mentioned that a domain name like oracle.com can have many IP addresses. So how does DNS help my computer find the right one? Sergio: So, let's say that you want to look for www.example.com, how do you do that? So, you type in your computer instance or in your terminal, in your laptop, in your computer, you type in your browser "www.example.com." If the browser doesn't have that information in cache, then it's going to first ask your DNS server, the one that you have assigned and indicating in your browser's configuration. And if the DNS server then it will relate that the information is 96.7.128.198. This address is real, and your browser will go to this address once you type www.example.com. 14:34 Nikita: But what happens if the browser doesn't know the address?  Sergio: This is where it gets interesting. Your browser wants to go to www.example.com. And it's going to go and look within its cache. If it doesn't have it, then the first step is to go ahead to your DNS server and ask them, hey, if you don't know this address, go ahead and find out. So, it goes to the root server. All the servers are administrated by IANA. And it's going to send the information, hey, what's the IP address for www.example.com? And if the root server doesn't know it, it's going to let you know, hey, ask the top-level domain name server, in this case, the .com. It's a top-level domain name server. So, you go ahead and ask this top-level domain name server to do that for you. In this case, again, the .com and you asked, hey, what's the IP address for example.com? And if the top-level domain name server doesn't know, it's going to ask you, hey, ask example.com. And example.com is actually within the customer's domain. And then based on these instructions you ask, what is the IP address for www.example.com? So, it will provide you with the IP address. And once your DNS server has the IP address, then it's going to relate to your web browser. And this is where your web browser actually reaches 96.7.128.198. Very interesting, isn't it? 16:23 Lois: Absolutely! Sergio, you mentioned top-level domain names. What are they and how are they useful? Sergio: A top level domain is the rightmost segment of a domain name, and it's located after the last visible dot in the domain name. So oracle.com or cloud.oracle.com is a domain name. So, .com is a top-level domain. And the purpose of the top-level domain is to recognize certain elements of a website. This top-level domain indicates that this is a commercial site. Now, .edu, for example, is a top-level domain name for higher education. We also have .org for nonprofit organizations, .net for network service providers. And we also have country specific. .ca for Canadian websites, .it for Italian websites. Now .it, a lot of companies that are in the information technology business utilizes this one to indicate that they're in information technology. There's also the .us. And for US companies, most of the time this is optional. .com, .org, .net is understood that they are from the US. Now if .com is a top-level domain name, what is that .oracle in cloud? So, Oracle is the second-level domain name. And in this case, Cloud is the third-level domain name. And lately you've been seeing a lot more top-level domain names. These are the classic ones. But now you get .AI, .media, .comedy, .people, and so on and so forth. You have many, many, even companies now have the option of registering their company name as the top-level domain name. 18:24 Nikita: Thank you, Sergio, for this deep dive into local area networks and domain name systems. If you want to learn about the topics we covered today, go to mylearn.oracle.com and search for the Cloud Tech Jumpstart course.  Lois: And don't forget to join us next week for another episode on networking essentials. Until next time, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 18:46 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

In today's Cloud Wars Minute, I dive into Oracle's bold AI-driven transformation and its stunning forecast to reach $225 billion in annual revenue by 2030, powered by explosive OCI and multi-cloud growth.Highlights00:12 — As we wrap things up here at Oracle AI world, we had the financial analyst meeting. Oracle's Principal Financial Officer Doug Kehring revealed that Oracle has raised its revenue projections again for the future, and says that they will hit the astonishing total of $225 billion in total revenue for fiscal year 30.00:52 — This was one of the most dynamic, interesting Oracle events I've ever been to. So when I talk about them being on fire, it's powered by their hyper growth OCI business. But it goes beyond that to what they're doing across the board and the AI Revolution really kicking in. It's why Larry Ellison pivoted the entire company to integrate AI in everything that they do.01:55 — The company's two new CEOs, Clay Magouyrk and Mike Sicilia, along with Larry Ellison, repeated throughout the event: "There's no limitation on us about demand. We have more demand by far than we can handle. We are supply-constrained. And they revealed a lot of plans about all the things Oracle is doing to be able to overcome that capacity constraint."02:21 — So, it is not just OpenAI. They talked about how the RPO, which when they released their numbers a few weeks ago, that is for the quarter ending August 31, their RPO was $455 billion in just the six or seven weeks since that quarter ended, that RPO is now over $500 billion. So again, it was not just the big deal with OpenAI.04:25 — We'll have more coming up next week. I'll go into more detail about this. But part of what was so interesting at this financial analyst meeting today, Larry Ellison talked said: "What about in the areas of like plant genomes?" Larry Ellison wove together the ideas of how this new Oracle Database along with the Oracle AI Data Platform is going to make that possible. Visit Cloud Wars for more.

I've been attending Oracle Yatra in July 2025 in Bengaluru, and AI and Multicloud are core concepts discussed, along with Oracle Database concepts. It's interesting to see how Oracle is encouraging a multicloud strategy and AI capabilities within the Oracle ecosystem. In this article, we will discuss an overview of the Oracle Multicloud Strategy through Oracle @ AWS.https://builder.aws.com/content/31MWAULLazXegTJlsNVw8q36FLM/oracle-multicloud-a-new-era-with-oracle-databaseaws

In today's Cloud Wars Minute, sponsored by CLOUDVICE, I explore how Oracle's new CEOs, Mike Sicilia and Clay Magouyrk, are steering the company deeper into the AI revolutionHighlights00:00 — Today's episode is brought to you by CloudVice, winner of the 2025 Oracle North America Technology and Cloud AI Innovation Partner Award. “We're honored to receive the 2025 Oracle North America Technology & Cloud AI Innovation Partner Award, a recognition that underscores CLOUDVICE's unwavering commitment to advancing enterprise AI on Oracle Cloud,” said Jaison Correya, CEO of CLOUDVICE. “This achievement reflects the breakthrough projects and real-world transformations we've delivered with Oracle — and at Oracle AI World 2025, we took that vision even further by unveiling CORX, our next-generation platform where AI thinks, Cloud scales, Blockchain verifies, and Robotics acts. It represents the next leap in intelligent automation and the future of real-world autonomy."00:25 — So, we're beginning to hear the strategies Oracle's two new CEOs are taking. That's Mike Sicilia and Clay Magouyrk. It's clear they think that Oracle's supremacy in data and infrastructure is going to make them successful in AI — to the point that their main focus is: how do we drive great customer outcomes using AI services?01:20 — And Oracle's plan, which they've been talking about a little bit and will unveil this week in much more detail, is that while LLMs currently work with public internet data, they're going to make available — very securely, privately, and with all requisite compliance — enterprise data that also can be accessed by those LLMs.02:21 — Clay Magouyrk talked a bit about the work Oracle has done to reach the point where its infrastructure is seen as superior. Magouyrk said that inside Oracle, the idea came up — “What if we shrunk the cloud down to a very tiny size? Could we get better performance, and could we give more deployment options to customers?” — it turned out that was exactly the case.03:28 — This week at Oracle AI World, they're going to introduce a new cloud bundle that has three racks — from 40 to three. Also, the stunning multicloud agreements that Oracle has reached with other hyperscalers — Microsoft, Google Cloud, and AWS — mean that those three competitors of Oracle sell the Oracle Database to their customers through their own clouds.04:21 — Because for all the things Oracle has done in its first 48 or 49 years, the next five years, triggered by all these changes we've just described, are going to be very different. Sicilia said, “One of the things you can count on as we move forward into those next five years is that we are currently, at Oracle, taking a very different approach.” Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explore how the long-dismissed "legacy" giant Oracle continues to defy the odds and outperform expectations — particularly in the cloud database space.Highlights00:14 — It's interesting what a little bit of time reveals to us. I was looking over Oracle's numbers last week. It made me think back not too long ago, 10–12 years, we heard about all the Oracle Database killers, these startups with different companies that were going to knock Oracle off. So that whole fantasy fizzled.01:42 — There were some wild fantasies that some high-level executives were willing to attach their names to publicly. So here's a good one: The Oracle killer, was supposedly a new project by AWS — a database service 10 years ago, a database migration service brought out by AWS. It had been out for one week, and Business Insider called it the Oracle killer.02:26 — The former MongoDB CEO, in multiple articles, prophesied Oracle's doom. He said they'd lost the heart and soul of the developers, that they were legacy, that they couldn't keep up. I wonder what this guy's doing now — see if he's got his storyline a little bit more tightly fastened to what reality is doing.03:02 — We see that Oracle's cloud database services for Q1, which ended August 31, were up 32% to almost $700 million — so getting close to a $3 billion annualized run rate. And its multi-cloud business — where they've got the Oracle Database that wasn't killed, now being sold by Microsoft, AWS, and Google Cloud — that revenue was up over 1,500%.05:10 — I love these startup tech companies — they're creating lots of new value. It's when one, two, three, or four of those startups start chirping about how they're going to rule the world soon, and they're going to be the “so-and-so killers.” That, to me, is a good sign that you should look elsewhere to give your business. Visit Cloud Wars for more.

Gary Miller, Executive Vice President and Customer Success Officer, Oracle, talks to Bob Evans about how Oracle is helping customers navigate their AI journeys — whether they're just starting out or scaling enterprise-wide adoption. He shares how Oracle is embedding AI across its entire technology stack, aligning partner and customer success strategies, and empowering organizations through tools like Cloud Success Navigator, Innovation Studios, and democratized AI training to deliver real, measurable business value.AI-Powered Customer WinsThe Big Themes:Embedding AI Across the Entire Stack: Oracle is not just adding AI as a feature — it's fundamentally integrating AI into its entire technology stack. Gary Miller notes that many customers are surprised to discover that large language models are being trained and deployed on OCI, and that hundreds of AI capabilities are embedded directly into Fusion Applications and Oracle Database. Once customers understand this depth of integration, they quickly shift from curiosity to action, asking for guidance on how to adopt AI now, what use cases to prioritize, and how to define success.Cloud Success Navigator Is Central to AI Adoption Strategy: The Oracle Cloud Success Navigator has emerged as a pivotal tool for AI and cloud adoption. What started as a promise in a previous conversation is now a robust, free digital platform that helps customers and partners create innovation roadmaps, prioritize features, and accelerate time to value. With over 6,000 customers and 235 partners using the platform since March, the tool enables organizations to track over 11,000 adopted features — including 450 AI-specific ones.AI World 2025 Will Spotlight Real Customer Outcomes: At the upcoming AI World 2025 event, Oracle plans to go beyond product announcements to highlight customer success stories. Miller will host a keynote titled “Bold Outcomes,” featuring innovative customers and partners sharing their journeys. Oracle is also gamifying the learning experience with “AI Industry Adventure,” a theme-park-style game in Customer Success Central. Attendees will solve real-world industry challenges using Oracle Cloud AI solutions, making learning both interactive and fun.The Big Quote: “Customers are often unaware of how Oracle has embedded AI capabilities across the whole stack. Once they understand that, then they ask us for expert guidance on how best to achieve their transformation goals using Oracle AI solutions. I had one CEO, he said, after he saw this, he said, 'Well, don't let us fumble around in the dark looking for value. You know, where it is, point us there.' And so they asked, how can I start adopting AI in my current environment? . . . How do I define AI, success metrics, and realize AI value? That's the key thing."More from Gary Miller and Oracle:Connect with Gary Miller on LinkedIn or learn more about Oracle and AI. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I break down how Oracle's $455 billion RPO surge is being driven by Larry Ellison's bold vision to lead not just in AI training — but in the even larger market of AI inferencing.Highlights00:46 — First, Ellison talked about AI training. Then, he discussed AI inferencing, which will be much, much bigger than AI training. Ellison said that AI inferencing will be used for everything — from robotic cars, robotic factories, and robotic greenhouses, to biomolecular synthesis to come up with new drugs.01:20 — He said, “We think Oracle is particularly well-positioned to go after this because of Oracle's history.” He said AI inferencing is the key, and Oracle is going to succeed because it's going to be able to provide data of multiple types for businesses that they can then use with these AI-trained models to be able to answer any sort of questions.02:33 — So Ellison thinks, therefore, business customers using Oracle Database and Oracle AI, Oracle inferencing, will be able to get any question answered they want, and that will also help them develop the AI agents that Oracle goes deeply into. Ellison and Oracle are redefining the whole nature of what data means, what AI means, what's possible.03:42 — CEO Safra Catz said she thinks that it won't be long before Oracle has RPOs above half a trillion dollars. So they're doing some remarkable things. Larry Ellison has always been a master of the long game. We're really seeing this play out here, and it's, I think, very interesting to see how he perceives these two multi-trillion dollar markets04:15 — The Oracle way is to go after them both, AI training and AI inferencing. No doubt there'll be lots of competitors. It's going to be a great market — great opportunities for businesses. And as we always say, the biggest winners in the Cloud Wars are always, always the customers. Visit Cloud Wars for more.

In today's Cloud Wars Minute, I explored why the groundbreaking Oracle–Google Cloud partnership around Gemini AI marks a bold new era for multi-cloud collaboration.Highlights00:14 — It's a brilliant move by Oracle and Google Cloud to form a partnership where Gemini AI is now available on the Oracle Cloud. Gemini on OCI is pretty wild. Both Oracle and Google compete viciously against each other. At the same time, they're both customer-centric enough to say: " ... in this other area, we're going to create new and significant value for customers."01:52 — Too often, I think tech vendors get into this mindset of: "Well, they're a competitor, so I'm not going to do anything with them — even if that might make life better for customers."I think those days are over. That's why I feel this is truly transformative.02:08 — Both executives from Google Cloud and Oracle spoke in great detail about how this partnership will make life easier for customers. They also talked about how this reflects their new philosophy: "We've got to be open. We've got to give choice — regardless of where it comes from."03:05 — Beyond Oracle and Google Cloud, I'd love to see AWS do some things with competitors. Microsoft has done some of this, but I think there's still room for all these companies to do more. It's the best of both worlds for customers: being able to get combinations of technologies and vendor capabilities rolled into single packages.03:41 — You're going to have both Google Cloud and Oracle salespeople now able to sell Gemini on Oracle Cloud. Just like about a year ago with the multi-cloud agreements — where Oracle Database became available on Azure, AWS, and Google Cloud — those hard and fast walls that used to separate vendors from ever cooperating are coming down. And they're coming down quickly.04:12 — What we see here is that tech vendors have to be not only world-class in the technology they're developing, but also in how they're willing to go to market in unprecedented ways to drive new and significant value for customers. That's going to be one of the primary yardsticks by which vendors are measured — not just by the power of their technology. Visit Cloud Wars for more.

Wei Hu is the Senior Vice President, High Availability Technologies, at Oracle. In today's Cloud Wars Live, Hu sits down with Bob Evans for a wide-ranging discussion on Oracle's globally distributed database, AI-native workloads, and how Oracle is helping businesses meet data sovereignty requirements while delivering high performance, elasticity, and always-on availability across regions.Where AI Meets Your DataThe Big Themes:Globally Distributed Exadata Database on Exascale: Oracle's Globally Distributed Exadata Database on Exascale Infrastructure delivers something few cloud providers can: high performance, high availability, and full compliance. Built on Oracle's powerful Exadata platform, this architecture removes the traditional need to purchase or manage hardware. Organizations can start small and elastically scale compute and memory across multiple regions.Agentic AI and Vector Search at Enterprise Scale: Oracle's database innovation is designed for real-world AI demands, especially agentic AI. AI agents need massive compute, consistent availability, and extremely fast access to live business data. Oracle's globally distributed architecture supports in-memory vector indexes for lightning-fast retrieval augmented generation (RAG), making AI more responsive and effective. Additionally, Oracle keeps AI close to the data — eliminating stale data issues and ensuring compliance.Built for a Sovereign Cloud World: Data residency and sovereignty are no longer optional, they're legal imperatives. Countries around the world are implementing strict rules on where data must be stored, how it can be accessed, and who can process it. Oracle addresses these challenges with policy-driven data distribution, allowing customers to define how and where data lives. Whether it's for compliance with India's payment data regulations or Europe's GDPR, Oracle enables precise control without requiring app changes or replication of the full stack.The Big Quote: “The other thing that's interesting about agentic AI is that it's very dynamic. The work comes in, the demands comes in, like a tidal wave. Then it goes away, right, then a little, then when it comes again, there's another tidal wave. So, what you really want to do is have an infrastructure that is elastic, that can scale up and down depending on the demand."More from Wei Hu and Oracle:Connect with Wei Hu on LinkedIn and learn more about Globally Distributed Exadata Database on Exascale Infrastructure.* Sponsored Podcast * Visit Cloud Wars for more.

In today's special edition of Cloud Wars Live, Bob Evans talks with Kris Rice, Senior Vice President, Software Development, Oracle Database, about the rapid rise of AI, the strategic impact of the new MCP Server, Oracle's unique approach to integrating LLMs with private data, and what to expect at this year's CloudWorld. Rice shares how Oracle is meeting developers where they are, enabling seamless AI-powered interactions with enterprise data.Inside Oracle's MCP StrategyThe Big Themes:Oracle's Strategic Integration of MCP: Oracle's implementation of the Model Context Protocol (MCP) represents more than a technical upgrade. Rice explains that MCP, though technically simple, becomes powerful because of how it's supported across AI agents, Copilots, cloud desktops, and IDEs. Oracle's distinctive approach lies in integrating MCP directly into its existing developer environments rather than layering on new tools.Oracle Marries AI with Data Sovereignty: Oracle has the unique ability to merge large language models (LLMs) with enterprise-grade data privacy and sovereignty. While many companies hesitate to use public AI platforms for sensitive queries, Oracle's approach — running LLMs on private GPUs in Oracle Cloud Infrastructure (OCI) — lets customers leverage cutting-edge AI while keeping data entirely within their own virtual cloud networks.Oracle CloudWorld 2025: Looking ahead to CloudWorld, Rice promises more than vision — he promises practical value. Attendees can expect hands-on labs, demos, and real-world use cases showing exactly how Oracle's MCP server and GenAI services can be applied immediately. From natural language-driven infrastructure provisioning using Terraform MCP to business logic queries run autonomously by AI agents, the event will be centered on tangible outcomes, not speculative futures.The Big Quote: “I saw the other day that the Google AI Studio supports MCP. So you could literally go to the Google AI studio, drop in your Oracle Database MCP support, and talk to your Oracle database that's on GCP, and never leave the boundaries of Google."More from Kris Rice and Oracle:Connect with Kris Rice on LinkedIn and learn more about Oracle and MCP* Sponsored podcast * Visit Cloud Wars for more.

Explore how the Oracle Database@AWS collaboration eliminates multi-cloud compromises, integrating Oracle's capabilities within AWS to enhance security, performance, and compliance. Learn how this partnership enables businesses to lift and shift existing workloads easily, leverage AI automation, and achieve rapid data integration, all while maintaining enterprise-grade security and scalability. Read the original blog post here: https://www.kuppingercole.com/blog/balaganski/oracle-databaseaws-combining-the-best-of-both-clouds

Hosts Lois Houston and Nikita Abraham continue their discussion with Mitchell Flinn, VP of Program Management for the CSS Platform, by exploring how Oracle Cloud Success Navigator helps teams align faster, reduce risk, and drive value.   Learn how built-in quality benchmarks, modern best practices, and Starter Configuration tools accelerate cloud adoption, and explore ways to stay ahead with a mindset of continuous innovation.   Oracle Cloud Success Navigator Essentials: https://mylearn.oracle.com/ou/course/oracle-cloud-success-navigator-essentials/147489/242186 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ----------------------------------------------------------------- Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Lois: Welcome to the Oracle University Podcast! I'm Lois Houston, Director of Innovation Programs with Oracle University and with joining me today is Nikita Abraham, Team Lead of Editorial Services.  Nikita: Hi everyone! In our last episode, we gave you a broad overview of the Oracle Cloud Success Navigator platform—what it is, how it works, and its key features and benefits. Today, we're continuing that discussion with Mitchell Flinn. Mitchell is VP of Program Management for Oracle Cloud Success Navigator, and in this episode, we're going to ask him to walk us through some of the core components of the platform that we couldn't get into last week. 01:04 Lois: Right, Niki. Hi Mitchell! You spoke a little about Cloud Quality Standards in our last episode. But how do they contribute or align with the vision of Oracle Cloud Success Navigator?  Mitchell: The vision for Navigator is to support customers throughout every phase of their cloud journey, providing timely advice to help improve outcomes to reduce cost and increase overall value. This model is driven through Oracle Cloud Quality Standards. These standards are intended to improve the transparency and collaboration between customer, partner, and Oracle members of a project. This is a project blueprint to include the ability for business and IT users to align on project coordination, expectations, and ultimately drive tighter alignment. Tracking key milestones and activities can help visualize and measure progress. You can build assessments and help answer questions so that at the right time, you have the right resources to make the right decisions for an organization. Cloud Quality Standards represent the key milestone dates and accomplishments along the journey. You can leverage these to increase project transparency, reduce risk, and increase the overall collaboration. Cloud Quality Standards are proactive list of must haves leveraged by customers, partners, and Oracle. They're a collection of knowledge and lessons learned from thousands of implementations globally. Cloud Quality Standards are partner agnostic and complimentary to all SI methodologies and tool sets. And they've been identified to address delivery issues before they happen and reduce the risk of implementations. 02:34 Lois: Ok, and a crucial component of Oracle Cloud Success Navigator is Oracle Modern Best Practice, or OMBP, right? Can you tell us more about what this is?  Mitchell: Oracle Modern Best Practices are based on distilled knowledge of our customers' needs gained from 10,000 successful delivery projects. They illustrate the business process components and their optimization to take advantage of the latest Oracle applications and technologies. Oracle Modern Best Practices comprise industry best practices and processes powered by Oracle technology. Engineered in Fusion Applications, OMBPs simplify and streamline workflows. They enable organizations to leverage modern, efficient, and scalable practices. As we align our assets with OMBPs, there's a stronger connection between global process owners and business process innovation within a customer's organization. 03:21 Nikita: And how do they help deliver end-to-end success for businesses?  Mitchell: An OMBP approach involves a digital business process, so evolving and adapting in real time to changing market dynamics. End-to-end across the organization, so we're breaking down silos and ensuring there's operational agility and a seamless collaboration between departments. We're leveraging emerging technologies, so utilizing AI, other cutting-edge technologies to automate routine tasks, enabling greater human creativity and unlocking new value and insights. And radically superior results, driving a significant improvement in measurable outcomes. OMBPs are dynamic, and when regularly updated, they meet evolving customer needs and technologies. They're trusted, tested, and validated by Oracle experts and publicly available and download on oracle.com. If you go to oracle.com and search modern best practice, you'll find more detailed introduction to Oracle Modern Best Practices. You'll also find Oracle Modern Best Practice business processes for domains such as ERP, EPM, Supply Chain, HCM, and Customer  Experience. We also have Oracle Modern Best Practices for specific industries. 04:25 Nikita: What are the key benefits of OMBP? Mitchell: Revolutionary new technologies are available for organizations and business leaders. You might wonder how existing business processes are optimized with old technology and how they can drive the best solution. With more emerging technologies reaching commercial availability, existing best practices become outdated. And to stay competitive, organizations need to continuously innovate and incorporate new technology within their best practices. In Oracle's definition of OMBPs, common business processes are considered historic input, but we also factor in what could be done with new technologies. And based on this approach, Oracle Modern Best Practices help us evolve with the organizational needs as market dynamics change, work end to end across organizations to eliminate department silos and ensure agility. It allows us to use technologies such as AI to automate the mundane and unlock human creativity for new value and insight. This allows us to incorporate next generation digital technologies to enable radically superior, measurable results. To achieve these, Oracle makes use of key differentiators such as analytics and AI and machine learning. Analytics are also known as business intelligence provides you with information in the form of pre-built dashboards, showing your key metrics in real time. Embedded analytic capabilities enable you to monitor business performance and make better decisions. 05:44 Lois: And what about AI and machine learning? Mitchell: These focus on building systems that learn or improve performance based on the data that they consume. Smart digital assistants, recommendation engines, predictive analytics, they're all used within AI and machine learning to help organizations automate operations and drive innovation, and ultimately make better decisions faster. 06:02 Nikita: Mitchell, let's move on to the Starter Configuration. Can you explain what it is and how it helps during a cloud implementation? Mitchell: Starter Configuration is a predefined configuration of Oracle Cloud Applications aligned with the Oracle Modern Best Practices. It's very comprehensive and includes business processes in several domains, such as ERP, HCM, Supply Chain, EPM, and so on. It includes sample, master, and transactional data, and predetermined usernames, which aligns and tests based on the same use cases you saw in Oracle Modern Best Practices in Cloud Success Navigator. Customers can request deployment of a Starter Configuration into their test environment. Oracle will run an automated process for replicating the configuration, master data, transaction data, and predetermined usernames from Oracle to the Oracle Cloud Applications Test Environment of the customer's choice. For best user experience, customers can add a basic level of personalization, such as their customer name, limited number of employees, suppliers, customers, and a few other items. Starter Configuration's delivered with predetermined step guides for comprehensive set of use cases. Using these, customers can relay the same use cases they've seen in Oracle Modern Best Practices and Success Navigator. In the Oracle Cloud Applications Test Environment Customer, we've been able to enable an in-app guidance using Oracle Guided Learning. This helps to make it easier for navigation through the business processes supported by the application. Oracle can deploy the Starter Configuration in days, not weeks or months, which means the implementation partners don't need to invest time and effort for the first configuration of an Oracle Cloud Application environment before they can even get the chance to show it to a customer. In turn, once Starter Configuration is deployed, it's ready to be used for solution familiarization and design activities. Using Starter Configuration of Oracle Cloud Applications early in the cloud journey will offer several benefits to customers. 08:00 Lois: What are these benefits? Mitchell: The first, it helps to cut down on environment configuration time from several weeks or months to potentially just days. Next, implementation partners can engage stakeholders early, and get them familiar with Oracle Cloud Applications, especially those that maybe have never participated in the sales cycle. Because customer stakeholders actually see what Oracle Cloud solutions might look like in the future, it becomes easier to take design decisions. Starter Configuration provides hands-on familiarization with Oracle Cloud Applications and Oracle Leading Practices. This makes it easier to understand what leading practices and standard features can be adopted to support future business processes. It also reduces the level of customization and accelerates implementation. 08:45 Transform the way you work with Oracle Database 23ai! This cutting-edge technology brings the power of AI directly to your data, making it easier to build powerful applications and manage critical workloads. Want to learn more about Database 23ai? Visit mylearn.oracle.com to pick from our range of courses and enroll today!   09:10 Nikita: Welcome back! Mitchell, how can customers and implementation partners best use the Starter Configuration?  Mitchell: Customers and implementation partners will work in close collaboration to make the implementation successful. Hence, Oracle recommends that customers and implementation partner discuss how the best use of Starter Configuration will take place. This is one of the key activities in the mobilize stage of the cloud journey. First, Oracle recommends to use Starter Configuration to prepare the customer stakeholders for the project. Customer stakeholders who participate in the project should go to the Oracle Modern Best Practice section of Success Navigator platform in order to learn more about the modern best practices, business processes, personas, leading practices, and use cases. Project team can request Starter Configuration early in the project to allow customer stakeholders to get their hands-on experience with performing use cases in the Starter Configuration. Customer stakeholders will perform use cases in Starter Config to learn more about modern best practices. They'll use the step-by-step guides and Guided Learning to easily perform the use cases within the Starter Configuration. This is how they'll visualize use cases in Oracle Cloud Applications and get a good understanding of Oracle Modern Best Practices. Next, mobilize stage of the journey, project team can use Starter Configuration to visualize the solution and make design decisions with confidence. First, by requesting Starter Configuration, implementation partners can engage stakeholders early and create the space to get familiar with Oracle Applications. This applies especially to those that may have not participated during the sales cycle. You could personalize Starter Configuration to enhance the user experience to help the customer connect to the application and, for example, change the company name, the logo, few supplier names, customer names, employee names, etc. And implementation partners are going to be able to run sessions to familiarize the customer with modern best practices and show how cloud applications support use cases. For structured guidance, the implementation partners can use the step guides. It includes screenshots of OGL within cloud applications environments. And you could run design workshop and use Starter Configuration, show and explain which design decisions must take place to define a customer-centric configuration. Finally, you can show use cases that help you explain what the impact of design decisions might be. 11:20 Lois: Mitchell, before we wrap up, can you take us through how the Release Readiness features facilitate innovation?  Mitchell: In order to innovate with the Release Readiness features, it's important to learn about the new features in a one-stop shop, and then connect with the capability. The first item is to be able to find and familiarize yourself with the content as they exist within Release Notes. From there, it's important to be able to actually experience those items by looking at the text, and pictures, and the Oracle University videos that we provide in the Feature Overviews, as well as additional capabilities that will be coming with the Navigator in the preview environment, your ability to get your hands on in a demo experience through Cloud Success Navigator. Furthermore, it's important for you to be able to explore across theme-based items, which we call Adoption Centers, currently ready for AI in Redwood. This gives you the ability to span across Release Notes and different releases in order to understand the themes of the trends around AI and Redwood, and how those capabilities in our technology can advance your innovation in the Cloud. And finally, you need to be able to understand those opportunities based off of business processes, data insights, and industry benchmarks. That way, you can understand the capabilities as they exist, not just for your business specifically, but in the context of the broader industry and technology trends. From there, it's important for you to then think about your ability to collaborate to drive continuous innovation. We want to be able to leverage Cloud Success Navigator to drive collaboration to increase confidence across all members of the project team, whether it be you as a customer, our partners, or the Oracle team. It should also be able to drive an increased efficiency within decision making, driving greater value and readiness as you think about the proposed adoption changes. Finally, we want to think about the ability to reduce cycles related to features and decisions so that you can more quickly adapt, and adjust, and consume innovations as they're produced on a quarterly basis.  13:09 Nikita: I think we can end with that. Thank you so much, Mitchell, for taking us through the Navigator platform. Lois: And if you liked what you heard today, head over to mylearn.oracle.com and take a look at the Oracle Cloud Success Navigator Essentials course to learn more. It's available for free! Until next time, this is Lois Houston…. Nikita: And Nikita Abraham, signing off! 13:33 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.  

In the final episode of this series on Oracle GoldenGate 23ai, Lois Houston and Nikita Abraham welcome back Nick Wagner, Senior Director of Product Management for GoldenGate, to discuss how parameters shape data replication. This episode covers parameter files, data selection, filtering, and transformation, providing essential insights for managing GoldenGate deployments.   Oracle GoldenGate 23ai: Fundamentals: https://mylearn.oracle.com/ou/course/oracle-goldengate-23ai-fundamentals/145884/237273 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. --------------------------------------------------------------- Podcast Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Lois: Hello and welcome to the Oracle University Podcast! I'm Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services.  Nikita: Hi everyone! This is the last episode in our Oracle GoldenGate 23ai series. Previously, we looked at how you can manage Extract Trails and Files. If you missed that episode, do go back and give it a listen.  00:50 Lois: Today, Nick Wagner, Senior Director of Product Management for GoldenGate, is back on the podcast to tell us about parameters, data selection, filtering, and transformation. These are key components of GoldenGate because they allow us to control what data is replicated, how it's transformed, and where it's sent. Hi Nick! Thanks for joining us again. So, what are the different types of parameter files? Nick: We have a GLOBALS parameter file and your runtime parameter files. The global one is going to affect all processes within a deployment. It's going to be things like where's your checkpoint table located in name, things like the heartbeat table. You want to have a single one of these across your entire deployment, so it makes sense to keep it within a single file. We also have runtime parameter files. This are going to be associated with a specific extract or replicat process. These files are located in your OGG_ETC_HOME/conf/ogg. The GLOBALS file is just simply named GLOBALS and all capitals, and your parameter file names for the processes themselves are named with the process.prm. So if my extract process is EXT demo, my parameter file name will be extdemo.prm. When you make changes to parameter files, they don't take effect until the process is restarted. So in the case of a GLOBALS parameter file, you need to restart the administration service. And in a runtime parameter file, you need to restart that specific process before any changes will take effect. We also have what we call a managed process setting profile. And this allows you to set up auto restart profiles for each process. And the GoldenGate Gate classic architecture, this was contained within the GLOBALS parameter file and handled by the manager. And microservices is a little bit different, it's handled by the service manager itself. But now we actually set up profiles. 02:41 Nikita: Ok, so what can you tell us about the extract parameter file specifically?  Nick: There's a couple things within the extract parameter file is common use. First, we want to tell what the group name is. So in this case, it would be our extract name. We need to put in information on where the extract process is going to be writing the data it captures to and that would be our trail files, and extract process can write to one or more trail files. We also want to list out the list of tables and schemas that we're going to be capturing, as well as any kind of DDL changes. If we're doing an initial load, we want to set up the SQL predicate to determine which tables are being captured and put a WHERE clause on those to speed up performance. We can also do filtering within the extract process as well. So we write just the information that we need to the trail file. 03:27 Nikita: And what are the common parameters within an extract process? Nick: There are a couple of common parameters within your extract process. We have table to list out the list of tables that GoldenGate is going to be capturing from. These can be wildcarded. So I can simply do table.star and GoldenGate will capture all the tables in that database. I can also do schema.star and it will capture all the tables within a schema. We have our EXTTRAIL command, which tells GoldenGate which trail to write to. If I want to filter out certain rows and columns, I can use the filter cols and cols except parameter. GoldenGate can also capture sequence changes. So we would use the sequence parameter. And then we can also set some high-level database options for GoldenGate that affect all the tables and that's configured using the tranlog options parameter.  04:14 Lois: Nick, can you talk a bit about the different types of tranlogoptions settings? How can they be used to control what the extract process does? Nick: So one of the first ones is ExcludeTag. So GoldenGate has the ability to exclude tagged transactions. Within the database itself, you can actually specify a transaction to be tagged using a DBMS set tag option. GoldenGate replicat also sets its transactions with a tag so that the GoldenGate process knows which transactions were done by the replicat and it can exclude them automatically. You can do exclude tag with a plus. That simply means to exclude any transaction that's been tagged with any value. You can also exclude specific tags.  Another good option for TranLogOptions is enable procedural replication. This allows GoldenGate to actually capture and replicate database procedure calls, and this would be things like DBMS AQ, NQ operations, or DQ operations. So if you're using Oracle advanced queuing and you need GoldenGate to replicate those changes, it can.  Another valuable tranlogoption setting is enable auto capture. Within the Oracle Database, you can actually set ALTER TABLE command that says ALTER TABLE, enable logical replication. Or when you create a table, you can actually do CREATE TABLE statement and at the end use the enable logical replication option for that CREATE TABLE statement. And this tells GoldenGate to automatically capture that table. One of the nice features about this is that I don't need to specify that table and my parameter file, and it'll automatically enable supplemental logging on that table for me using scheduling columns. So it makes it very easy to set up replication between Oracle databases.  06:01 Nikita: Can you tell us about replicat parameters, Nick? Nick: Within a replicat, we'll have the group name, some common other parameters that we'll use is a mapping parameter that allows us to map the source to target table relationships. We can do transformation within the replicat, as well as error handling and controlling group operations to improve performance. Some common replicat parameters include the replicat parameter itself, which tells us what the name of that replicat is. We have our map statement, which allows us to map a source object to a target object. We have things like rep error that control how to handle errors. Insert all records allows us to change and convert, update, and delete operations into inserts. We can do things like compare calls, which helps with active-active replication in determining which columns are used in the GoldenGate WHERE clause. We also have the ability to use macros and column mapping to do additional transformation and make the parameter file look elegant. 07:07 AI is being used in nearly every industry…healthcare, manufacturing, retail, customer service, transportation, agriculture, you name it! And it's only going to get more prevalent and transformational in the future. It's no wonder that AI skills are the most sought-after by employers. If you're ready to dive in to AI, check out the OCI AI Foundations training and certification that's available for free! It's the perfect starting point to build your AI knowledge. So, get going! Head on over to mylearn.oracle.com to find out more. 07:47 Nikita: Welcome back! Let's move on to some of the most interesting topics within GoldenGate… data mapping, selection, and transformation. As I understand, users can do pretty cool things with GoldenGate. So Nick, let's start with how GoldenGate can manipulate, change, and map data between two different databases. Nick: The map statement within a Replicat parameter allows you to provide specifications on how you're going to map source and target objects. You can also use a map and an extract, but it's pretty rare. And that would be used if you needed to write the object name. Inside the trail files is a different name than the actual object name that you're capturing from. GoldenGate can also do different data selection, mapping, and manipulation, and this is all controlled within the Extract and Replicat parameter files. In the classic architecture of GoldenGate, you could do a rudimentary level of transformation and filtering within the extract pump. Now, the distribution service is only allowing you to do filtering. Any transformation that you had within the pump would need to be moved to the Extract or the Replicat process.  The other thing that you can do within GoldenGate is select and filter data based on different levels and conditions. So within your parameter clause, you have your Table and Map statement. That's the core of everything. You have your filtering. You have COLS and COLSEXCEPT, which allow you to determine which columns you're going to include or exclude from replication. The Table and Map statement works at the table level. The FILTER works at the row level. And COLS and COLSEXCEPTs works at the column level. We also have the ability to filter by operation type too. So GoldenGate has some very easy parameters called GitInserts, GitUpdates, GitDeletes, and conversely ignore updates, ignore deletes, ignore inserts. And that will affect the operation type. 09:40 Lois: Nick, are there any features that GoldenGate provides to make data replication easier? Nick: The first thing is that GoldenGate is going to automatically match your source and target column names with a parameter called USEDEFAULTS. You can specify it inside of your COLMAP clause, but again, it's a default, so you don't need to worry about it. We also handle all data type and character set conversion. Because we store the metadata in the trail, we know what that source data type is like. When we go to apply the record to the target table, the Replicat process is going to look up the definition of that record and keep a repository of that in memory. So that when it knows that, hey, this value coming in from the trail file is going to be of a date data type, and then this value in the target database is going to be a character data type, it knows how to convert that date to a character, and it'll do it for you. Most of the conversion is going to be done automatically for data types. Things where we don't do automatic data type conversion is if you're using abstract data types or user-defined data types, collections arrays, and then some types of CLOB operations. For example, if you're going from a BLOB to a JSON, that's not really going to work very well. Character set conversion is also done automatically. It's not necessarily done directly by GoldenGate, but it's done by the database engine. So there is a character set value inside that source database.  And when GoldenGate goes to apply those changes into the target system, it's ensuring that that character set is visible and named so that that database can do the necessary translation. You can also do advanced filtering transformation. There's tokens that you can attach from the source environment, database, or records into a record itself on the trail file. And then there's also a bunch of metadata that GoldenGate can use to attach to the record itself. And then of course, you can use data transformation within your COLMAP statement. 11:28 Nikita: Before we wrap up, what types of data transformations can we perform, Nick?  Nick: So there's quite a few different data transformations. We can do constructive or destructive transformation, aesthetic, and structural. 11:39 Lois: That's it for the Oracle GoldenGate 23ai: Fundamentals series. I think we covered a lot of ground this season. Thank you, Nick, for taking us through it all.  Nikita: Yeah, thank you so much, Nick. And if you want to learn more, head over to mylearn.oracle.com and search for the Oracle GoldenGate 23ai: Fundamentals course. Until next time, this is Nikita Abraham… Lois: And Lois Houston, signing off! 12:04 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. 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GoldenGate 23ai takes security seriously, and this episode unpacks everything you need to know. GoldenGate expert Nick Wagner breaks down how authentication, access roles, and encryption protect your data.   Learn how GoldenGate integrates with identity providers, secures communication, and keeps passwords out of storage. Understand how trail files work, why they only store committed data, and how recovery processes prevent data loss.   Whether you manage replication or just want to tighten security, this episode gives you the details to lock things down without slowing operations.   Oracle GoldenGate 23ai: Fundamentals: https://mylearn.oracle.com/ou/course/oracle-goldengate-23ai-fundamentals/145884/237273 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   --------------------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Lois: Hello and welcome to the Oracle University Podcast! I'm Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services.  Nikita: Welcome, everyone! This is our fourth episode on Oracle GoldenGate 23ai. Last week, we discussed the terminology, different processes and what they do, and the architecture of the product at a high level. Today, we have Nick Wagner back with us to talk about the security strategies of GoldenGate. 00:56 Lois: As you know by now, Nick is a Senior Director of Product Management for GoldenGate at Oracle. He's played a key role as one of the product designers behind the latest version of GoldenGate. Hi Nick! Thank you for joining us again. Can you tell us how GoldenGate takes care of data security? Nick: So GoldenGate authentication and authorization is done in a couple of different ways. First, we have user credentials for GoldenGate for not only the source and target databases, but also for GoldenGate itself. We have integration with third-party identity management products, and everything that GoldenGate does can be secured. 01:32 Nikita: And we must have some access roles, right? Nick: There's four roles built into the GoldenGate product. You have your security role, administrator, operator, and user. They're all hierarchical. The most important one is the security user. This user is going to be the one that provides the administrative tasks. This user is able to actually create additional users and assign roles within the product. So do not lose this password and this user is extremely important. You probably don't want to use this security user as your everyday user. That would be your administrator. The administrator role is able to perform all administrative tasks within GoldenGate. So not only can they go in and create new extracts, create new replicats, create new distribution services, but they can also start and stop them. And that's where the operator role is and the user role. So the operator role allows you to go in and start/stop processes, but you can't create any new ones, which is kind of important. So this user would be the one that could go in and suspend activity. They could restart activity. But they can't actually add objects to replication. The user role is really a read-only role. They can come in. They can see what's going on. They can look at the log files. They can look at the alerts. They can look at all the watches and see exactly what GoldenGate is doing. But they're unable to make any changes to the product itself. 02:54 Lois: You mentioned the roles are hierarchical in nature. What does that mean? Nick: So anything that the user role does can be done by the operator. Anything that the operator and user roles can do can be done by the administrator. And anything that the user, operator, and administrator roles do can be done by the security role. 03:11 Lois: Ok. So, is there a single sign-on available for GoldenGate? Nick: We also have a password plugin for GoldenGate Connections. A lot of customers have asked for integration with whatever their single sign-on utility is, and so GoldenGate now has that with GoldenGate 23ai. So these are customer-created entities. So, we have some examples that you can use in our documentation on how to set up an identity provider or a third-party identity provider with GoldenGate. And this allows you to ensure that your corporate standards are met. As we started looking into this, as we started designing it, every single customer wanted something different. And so instead of trying to meet the needs for every customer and every possible combination of security credentials, we want you to be able to design it the way you need it. The passwords are never stored. They're only retrieved from the identity provider by the plugin itself. 04:05 Nikita: That's a pretty important security aspect…that when it's time to authenticate a user, we go to the identity provider. Nick: We're going to connect in and see if that password is matching. And only then do we use it. And as soon as we detect that it's matched, that password is removed. And then for the extract and replicats themselves, you can also use it for the database, data source, and data target connections, as well as for the GoldenGate users. So, it is a full-featured plugin. So, our identity provider plugin works with IAM as well as OAM. These are your standard identity manager authentication methods. The standard one is OAuth 2, as well as OIDC. And any Identity Manager that uses that is able to integrate with GoldenGate. 04:52 Lois: And how does this work? Nick: The way that it works is pretty straightforward. Once the user logs into the database, we're going to hand off authentication to the identity provider. Once the identity provider has validated that user's identity and their credentials, then it comes back to GoldenGate and says that user is able to log in to either GoldenGate or the application or the database. Once the user is logged in, we get that confirmation that's been sent out and they can continue working through GoldenGate. So, it's very straightforward on how it works. There's also a nice little UI that will help set up each additional user within those systems. All the communication is also secured as well. So any communication done through any of the GoldenGate services is encrypted using HTTPS. All the REST calls themselves are all done using HTTPS as well. All the data protection calls and all the communication across the network when we send data across a distribution service is encrypted using a secure WebSocket. And there's also trail file encryption at the operating system level for data at REST. So, this really gives you the full level of encryption for customers that need that high-end security. GoldenGate does have an option for FIPS 140-2 compliance as well. So that's even a further step for most of those customers. 06:12 Nikita: That's impressive! Because we want to maintain the highest security standards, right? Especially when dealing with sensitive information. I now want to move on to trail files. In our last episode, we briefly spoke about how they serve as logs that record and track changes made to data. But what more can you tell us about them, Nick? Nick: There's two different processes that write to the trail files. The extract process will write to the trail file and the receiver service will write to the trail file. The extract process is going to write to the trail file as it's pulling data out of that source database. Now, the extract process is controlled by a parameter file, that says, hey, here's the exact changes that I'm going to be pulling out. Here's the tables. Here's the rows that I want. As it's pulling that data out and writing it to the trail files, it's ensuring that those trail files have enough information so that the replicat process can actually construct a SQL statement and apply that change to that target platform. And so there's a lot of ways to change what's actually stored in those trail files and how it's handled. The trail files can also be used for initial loads. So when we do the initial load through GoldenGate, we can grab and write out the data for those tables, and that excludes the change data. So initial loads is pulling the data directly from the tables themselves, whereas ongoing replication is pulling it from the transaction logs. 07:38 Lois: But do we need to worry about rollbacks? Nick: Our trail files contain committed data only and all data is sequential. So this is two important things. Because it contains committed data only, we don't need to worry about rollbacks. We also don't need to worry about position within that trail file because we know all data is sequential. And so as we're reading through the trail file, we know that anything that's written in a prior location in that trial file was committed prior to something else. And as we get into the recovery aspects of GoldenGate, this will all make a lot more sense. 08:13 Lois: Before we do that, can you tell us about the naming of trail files? Nick: The trail files as far as naming, because these do reside on the operating system, you start with a two-letter trail file abbreviation and then a nine-digit sequential value. So, you almost look at it as like an archive log from Oracle, where we have a prefix and then an affix, which is numeric. Same kind of thing. So, we have our two-letter, in this case, an ab, and then we have a nine-digit number. 08:47 Transform the way you work with Oracle Database 23ai! This cutting-edge technology brings the power of AI directly to your data, making it easier to build powerful applications and manage critical workloads. Want to learn more about Database 23ai? Visit mylearn.oracle.com to pick from our range of courses and enroll today! 09:12 Nikita: Welcome back! Ok, Nick. Let's get into the GoldenGate recovery process. Nick: When we start looking at the GoldenGate recovery process, it essentially makes GoldenGate kind of point-in-time like. So on that source database, you have your extract process that's going to be capturing data from the transaction logs. In the case of Oracle, the Oracle Database is actually going to be reading those transaction logs from us and passing the change records directly to GoldenGate. We call them an LCR, Logical Change Record. And so the integrated extract and GoldenGate, the extract portion tells the database, hey, I'm now going to be interested in the following list of tables. And it gives a list of tables to that internal component, the log mining engine within the database. And it says, OK, I'm now pulling data for those tables and I'm going to send you those table changes. And so as the extract process gets sent those changes, it's going to have checkpoint information. So not only does it know where it was pulling data from out of that source database, but what it's also writing to the trail file. The trail files themselves are all sequential and they have only committed data, as we talked about earlier. The distribution service has checkpoint information that says, hey, I know where I'm reading from in the previous trail file, and I know what I've sent across the network. The receiver service is the same thing. It knows what it's receiving, as well as what it's written to the trail file and the target system. The replicat also has a checkpoint. It knows where it's reading from in the trail file, and then it knows what it's been applying into that target database.  This is where things start to become a little complicated. Our replicat process in most cases are parallel, so it'll have multiple threads applying data into that target database. Each of those threads is applying different transactions. And because of the way that the parallelism works in the replicat process, you can actually get situations where one replicat thread might be applying a transaction higher than another thread. And so you can eliminate that sequential or serial aspect of it, and we can get very high throughput speeds to the replicat. But it means that the checkpoint needs to be kind of smart enough to know how to rebuild itself if something fails. 11:32 Lois: Ok, sorry Nick, but can you go through that again? Maybe we can work backwards this time?  Nick: If the replicat process fails, when it comes back up, it's going to look to its checkpoint tables inside that target database. These checkpoint tables keep track of where each thread was at when it crashed. And so when the replicat process restarts, it goes, oh, I was applying these threads at this location in these SCNs. It'll then go and read from the trail file and say, hey, let me rebuild that data and it only applies transactions that it hasn't applied yet to that target system. There is a synchronized replicat command as well that will tell a crashed replicat to say, hey, bring all your threads up to the same high watermark. It does that process automatically as it restarts and continues normal replication. But there is an option to do it just by itself too. So that's how the replicat kind of repairs and recovers itself. It'll simply look at the trail files. Now, let's say that the replicat crashed, and it goes to read from the trail files when it restarts and that trail profile is missing. It'll actually communicate to the distribution, or excuse me, to the receiver service and say, hey, receiver service, I don't have this trail file. Can you bring it back for me? And the receiver service will communicate downstream and say, hey, distribution service, I need you to resend me trail find number 6. And so the distribution service will resend that trail file so that the replicat can reprocess it. So it's often nice to have redundant environments with GoldenGate so we can have those trail files kind of around for availability. 13:13 Nikita: What if one of these files gets corrupted? Nick: If one of those trail files is corrupt, let's say that a trail file on the target site became corrupt and the replicat can't read from it for one reason or another. Simply stop the replicat process, delete the corrupt trail file, restart the replicat process, and now it's going to rebuild that trail file from scratch based on the information from the source GoldenGate environment. And so it's very recoverable. Handles it all very well. 13:40 Nikita: And can the extract process bounce back in the same way? Nick: The extract process can also recover in a similar way. So if the extract process crashes, when it restarts itself, there's a number of things that it does. The first thing is it has to rebuild any open transactions. So it keeps all sorts of checkpoint information about the oldest transaction that it's keeping track of, any open transactions that haven't been committed, and any other transactions that have been committed that it's already written to the trail file. So as it's reprocessing that data, it knows exactly what it's committed to trail and what hasn't been committed. And there's a number of ways that it does this.  There's two main components here. One of them is called bounded recovery. Bounded recovery will allow you to set a time limit on transactions that span a certain length of time that they'll actually get flushed out to disk on that GoldenGate Hub. And that way it'll reduce the amount of time it takes GoldenGate to restart the extract process. And the other component is cache manager. Cache manager stores uncommitted transactions. And so it's a very elegant way of rebuilding itself from any kind of failure. You can also set up restart profiles so that if any process does crash, the GoldenGate service manager can automatically restart that service an x number of times across y time span. So if I say, hey, if my extract crashes, then attempt to restart it 100 times every 5 seconds. So there's a lot of things that you can do there to make it really nice and automatic repair itself and automatically resilient.  15:18 Lois: Well, that brings us to the end of this episode. Thank you, Nick, for going through the security strategies and recovery processes in such detail. Next week, we'll look at the installation of GoldenGate. Nikita: And if you want to learn more about the topics we discussed today, head over to mylearn.oracle.com and take a look at the Oracle GoldenGate 23ai Fundamentals course. Until next time, this is Nikita Abraham… Lois: And Lois Houston signing off! 15:44 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

In this episode, Lois Houston and Nikita Abraham continue their deep dive into Oracle GoldenGate 23ai, focusing on its evolution and the extensive features it offers. They are joined once again by Nick Wagner, who provides valuable insights into the product's journey.   Nick talks about the various iterations of Oracle GoldenGate, highlighting the significant advancements from version 12c to the latest 23ai release. The discussion then shifts to the extensive new features in 23ai, including AI-related capabilities, UI enhancements, and database function integration.   Oracle GoldenGate 23ai: Fundamentals: https://mylearn.oracle.com/ou/course/oracle-goldengate-23ai-fundamentals/145884/237273 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   -----------------------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Lois: Hello and welcome to the Oracle University Podcast! I'm Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services.  Nikita: Hi everyone! Last week, we introduced Oracle GoldenGate and its capabilities, and also spoke about GoldenGate 23ai. In today's episode, we'll talk about the various iterations of Oracle GoldenGate since its inception. And we'll also take a look at some new features and the Oracle GoldenGate product family. 00:57 Lois: And we have Nick Wagner back with us. Nick is a Senior Director of Product Management for GoldenGate at Oracle. Hi Nick! I think the last time we had an Oracle University course was when Oracle GoldenGate 12c was out. I'm sure there's been a lot of advancements since then. Can you walk us through those? Nick: GoldenGate 12.3 introduced the microservices architecture. GoldenGate 18c introduced support for Oracle Autonomous Data Warehouse and Autonomous Transaction Processing Databases. In GoldenGate 19c, we added the ability to do cross endian remote capture for Oracle, making it easier to set up the GoldenGate OCI service to capture from environments like Solaris, Spark, and HP-UX and replicate into the Cloud. Also, GoldenGate 19c introduced a simpler process for upgrades and installation of GoldenGate where we released something called a unified build. This means that when you install GoldenGate for a particular database, you don't need to worry about the database version when you install GoldenGate. Prior to this, you would have to install a version-specific and database-specific version of GoldenGate. So this really simplified that whole process. In GoldenGate 23ai, which is where we are now, this really is a huge release.  02:16 Nikita: Yeah, we covered some of the distributed AI features and high availability environments in our last episode. But can you give us an overview of everything that's in the 23ai release? I know there's a lot to get into but maybe you could highlight just the major ones? Nick: Within the AI and streaming environments, we've got interoperability for database vector types, heterogeneous capture and apply as well. Again, this is not just replication between Oracle-to-Oracle vector or Postgres to Postgres vector, it is heterogeneous just like the rest of GoldenGate. The entire UI has been redesigned and optimized for high speed. And so we have a lot of customers that have dozens and dozens of extracts and replicats and processes running and it was taking a long time for the UI to refresh those and to show what's going on within those systems. So the UI has been optimized to be able to handle those environments much better. We now have the ability to call database functions directly from call map. And so when you do transformation with GoldenGate, we have about 50 or 60 built-in transformation routines for string conversion, arithmetic operation, date manipulation. But we never had the ability to directly call a database function. 03:28 Lois: And now we do? Nick: So now you can actually call that database function, database stored procedure, database package, return a value and that can be used for transformation within GoldenGate. We have integration with identity providers, being able to use token-based authentication and integrate in with things like Azure Active Directory and your other single sign-on for the GoldenGate product itself. Within Oracle 23ai, there's a number of new features. One of those cool features is something called lock-free reservation columns. So this allows you to have a row, a single row within a table and you can identify a column within that row that's like an inventory column. And you can have multiple different users and multiple different transactions all updating that column within that same exact row at that same time. So you no longer have row-level locking for these reservation columns. And it allows you to do things like shopping carts very easily. If I have 500 widgets to sell, I'm going to let any number of transactions come in and subtract from that inventory column. And then once it gets below a certain point, then I'll start enforcing that row-level locking. 04:43 Lois: That's really cool… Nick: The one key thing that I wanted to mention here is that because of the way that the lock-free reservations work, you can have multiple transactions open on the same row. This is only supported for Oracle to Oracle. You need to have that same lock-free reservation data type and availability on that target system if GoldenGate is going to replicate into it. 05:05 Nikita: Are there any new features related to the diagnosability and observability of GoldenGate?  Nick: We've improved the AWR reports in Oracle 23ai. There's now seven sections that are specific to Oracle GoldenGate to allow you to really go in and see exactly what the GoldenGate processes are doing and how they're behaving inside the database itself. And there's a Replication Performance Advisor package inside that database, and that's been integrated into the Web UI as well. So now you can actually get information out of the replication advisor package in Oracle directly from the UI without having to log into the database and try to run any database procedures to get it. We've also added the ability to support a per-PDB Extract.  So in the past, when GoldenGate would run on a multitenant database, a multitenant database in Oracle, all the redo data from any pluggable database gets sent to that one redo stream. And so you would have to configure GoldenGate at the container or root level and it would be able to access anything at any PDB. Now, there's better security and better performance by doing what we call per-PDB Extract. And this means that for a single pluggable database, I can have an extract that runs at that database level that's going to capture information just from that pluggable database. 06:22 Lois And what about non-Oracle environments, Nick? Nick: We've also enhanced the non-Oracle environments as well. For example, in Postgres, we've added support for precise instantiation using Postgres snapshots. This eliminates the need to handle collisions when you're doing Postgres to Postgres replication and initial instantiation. On the GoldenGate for big data side, we've renamed that product more aptly to distributed applications in analytics, which is really what it does, and we've added a whole bunch of new features here too. The ability to move data into Databricks, doing Google Pub/Sub delivery. We now have support for XAG within the GoldenGate for distributed applications and analytics. What that means is that now you can follow all of our MAA best practices for GoldenGate for Oracle, but it also works for the DAA product as well, meaning that if it's running on one node of a cluster and that node fails, it'll restart itself on another node in the cluster. We've also added the ability to deliver data to Redis, Google BigQuery, stage and merge functionality for better performance into the BigQuery product. And then we've added a completely new feature, and this is something called streaming data and apps and we're calling it AsyncAPI and CloudEvent data streaming. It's a long name, but what that means is that we now have the ability to publish changes from a GoldenGate trail file out to end users. And so this allows through the Web UI or through the REST API, you can now come into GoldenGate and through the distributed applications and analytics product, actually set up a subscription to a GoldenGate trail file. And so this allows us to push data into messaging environments, or you can simply subscribe to changes and it doesn't have to be the whole trail file, it can just be a subset. You can specify exactly which tables and you can put filters on that. You can also set up your topologies as well. So, it's a really cool feature that we've added here. 08:26 Nikita: Ok, you've given us a lot of updates about what GoldenGate can support. But can we also get some specifics? Nick: So as far as what we have, on the Oracle Database side, there's a ton of different Oracle databases we support, including the Autonomous Databases and all the different flavors of them, your Oracle Database Appliance, your Base Database Service within OCI, your of course, Standard and Enterprise Edition, as well as all the different flavors of Exadata, are all supported with GoldenGate. This is all for capture and delivery. And this is all versions as well. GoldenGate supports Oracle 23ai and below. We also have a ton of non-Oracle databases in different Cloud stores. On an non-Oracle side, we support everything from application-specific databases like FairCom DB, all the way to more advanced applications like Snowflake, which there's a vast user base for that. We also support a lot of different cloud stores and these again, are non-Oracle, nonrelational systems, or they can be relational databases. We also support a lot of big data platforms and this is part of the distributed applications and analytics side of things where you have the ability to replicate to different Apache environments, different Cloudera environments. We also support a number of open-source systems, including things like Apache Cassandra, MySQL Community Edition, a lot of different Postgres open source databases along with MariaDB. And then we have a bunch of streaming event products, NoSQL data stores, and even Oracle applications that we support. So there's absolutely a ton of different environments that GoldenGate supports. There are additional Oracle databases that we support and this includes the Oracle Metadata Service, as well as Oracle MySQL, including MySQL HeatWave. Oracle also has Oracle NoSQL Spatial and Graph and times 10 products, which again are all supported by GoldenGate. 10:23 Lois: Wow, that's a lot of information! Nick: One of the things that we didn't really cover was the different SaaS applications, which we've got like Cerner, Fusion Cloud, Hospitality, Retail, MICROS, Oracle Transportation, JD Edwards, Siebel, and on and on and on.  And again, because of the nature of GoldenGate, it's heterogeneous. Any source can talk to any target. And so it doesn't have to be, oh, I'm pulling from Oracle Fusion Cloud, that means I have to go to an Oracle Database on the target, not necessarily.  10:51 Lois: So, there's really a massive amount of flexibility built into the system.  11:00 Unlock the power of AI Vector Search with our new course and certification. Get more accurate search results, handle complex datasets easily, and supercharge your data-driven decisions. From now through May 15, 2025, we are waiving the certification exam fee (valued at $245). Visit mylearn.oracle.com to enroll. 11:26 Nikita: Welcome back! Now that we've gone through the base product, what other features or products are in the GoldenGate family itself, Nick? Nick: So we have quite a few. We've kind of touched already on GoldenGate for Oracle databases and non-Oracle databases. We also have something called GoldenGate for Mainframe, which right now is covered under the GoldenGate for non-Oracle, but there is a licensing difference there. So that's something to be aware of. We also have the OCI GoldenGate product. We are announcing and we have announced that OCI GoldenGate will also be made available as part of the Oracle Database@Azure and Oracle Database@ Google Cloud partnerships.  And then you'll be able to use that vendor's cloud credits to actually pay for the OCI GoldenGate product. One of the cool things about this is it will have full feature parity with OCI GoldenGate running in OCI. So all the same features, all the same sources and targets, all the same topologies be able to migrate data in and out of those clouds at will, just like you do with OCI GoldenGate today running in OCI.  We have Oracle GoldenGate Free.  This is a completely free edition of GoldenGate to use. It is limited on the number of platforms that it supports as far as sources and targets and the size of the database.  12:45 Lois: But it's a great way for developers to really experience GoldenGate without worrying about a license, right? What's next, Nick? Nick: We have GoldenGate for Distributed Applications and Analytics, which was formerly called GoldenGate for big data, and that allows us to do all the streaming. That's also where the GoldenGate AsyncAPI integration is done. So in order to publish the GoldenGate trail files or allow people to subscribe to them, it would be covered under the Oracle GoldenGate Distributed Applications and Analytics license. We also have OCI GoldenGate Marketplace, which allows you to run essentially the on-premises version of GoldenGate but within OCI. So a little bit more flexibility there. It also has a hub architecture. So if you need that 99.99% availability, you can get it within the OCI Marketplace environment. We have GoldenGate for Oracle Enterprise Manager Cloud Control, which used to be called Oracle Enterprise Manager. And this allows you to use Enterprise Manager Cloud Control to get all the statistics and details about GoldenGate. So all the reporting information, all the analytics, all the statistics, how fast GoldenGate is replicating, what's the lag, what's the performance of each of the processes, how much data am I sending across a network. All that's available within the plug-in. We also have Oracle GoldenGate Veridata. This is a nice utility and tool that allows you to compare two databases, whether or not GoldenGate is running between them and actually tell you, hey, these two systems are out of sync. And if they are out of sync, it actually allows you to repair the data too. 14:25 Nikita: That's really valuable…. Nick: And it does this comparison without locking the source or the target tables. The other really cool thing about Veridata is it does this while there's data in flight. So let's say that the GoldenGate lag is 15 or 20 seconds and I want to compare this table that has 10 million rows in it. The Veridata product will go out, run its comparison once. Once that comparison is done the first time, it's then going to have a list of rows that are potentially out of sync. Well, some of those rows could have been moved over or could have been modified during that 10 to 15 second window. And so the next time you run Veridata, it's actually going to go through. It's going to check just those rows that were potentially out of sync to see if they're really out of sync or not. And if it comes back and says, hey, out of those potential rows, there's two out of sync, it'll actually produce a script that allows you to resynchronize those systems and repair them. So it's a very cool product.  15:19 Nikita: What about GoldenGate Stream Analytics? I know you mentioned it in the last episode, but in the context of this discussion, can you tell us a little more about it?  Nick: This is the ability to essentially stream data from a GoldenGate trail file, and they do a real time analytics on it. And also things like geofencing or real-time series analysis of it.  15:40 Lois: Could you give us an example of this? Nick: If I'm working in tracking stock market information and stocks, it's not really that important on how much or how far down a stock goes. What's really important is how quickly did that stock rise or how quickly did that stock fall. And that's something that GoldenGate Stream Analytics product can do. Another thing that it's very valuable for is the geofencing. I can have an application on my phone and I can track where the user is based on that application and all that information goes into a database. I can then use the geofencing tool to say that, hey, if one of those users on that app gets within a certain distance of one of my brick-and-mortar stores, I can actually send them a push notification to say, hey, come on in and you can order your favorite drink just by clicking Yes, and we'll have it ready for you. And so there's a lot of things that you can do there to help upsell your customers and to get more revenue just through GoldenGate itself. And then we also have a GoldenGate Migration Utility, which allows customers to migrate from the classic architecture into the microservices architecture. 16:44 Nikita: Thanks Nick for that comprehensive overview.  Lois: In our next episode, we'll have Nick back with us to talk about commonly used terminology and the GoldenGate architecture. And if you want to learn more about what we discussed today, visit mylearn.oracle.com and take a look at the Oracle GoldenGate 23ai Fundamentals course. Until next time, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 17:10 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

In a new season of the Oracle University Podcast, Lois Houston and Nikita Abraham dive into the world of Oracle GoldenGate 23ai, a cutting-edge software solution for data management. They are joined by Nick Wagner, a seasoned expert in database replication, who provides a comprehensive overview of this powerful tool.   Nick highlights GoldenGate's ability to ensure continuous operations by efficiently moving data between databases and platforms with minimal overhead. He emphasizes its role in enabling real-time analytics, enhancing data security, and reducing costs by offloading data to low-cost hardware. The discussion also covers GoldenGate's role in facilitating data sharing, improving operational efficiency, and reducing downtime during outages.   Oracle GoldenGate 23ai: Fundamentals: https://mylearn.oracle.com/ou/course/oracle-goldengate-23ai-fundamentals/145884/237273 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode. ---------------------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Nikita: Welcome to the Oracle University Podcast! I'm Nikita Abraham, Team Lead: Editorial Services with Oracle University, and with me is Lois Houston: Director of Innovation Programs. Lois: Hi everyone! Welcome to a new season of the podcast. This time, we're focusing on the fundamentals of Oracle GoldenGate. Oracle GoldenGate helps organizations manage and synchronize their data across diverse systems and databases in real time.  And with the new Oracle GoldenGate 23ai release, we'll uncover the latest innovations and features that empower businesses to make the most of their data. Nikita: Taking us through this is Nick Wagner, Senior Director of Product Management for Oracle GoldenGate. He's been doing database replication for about 25 years and has been focused on GoldenGate on and off for about 20 of those years.  01:18 Lois: In today's episode, we'll ask Nick to give us a general overview of the product, along with some use cases and benefits. Hi Nick! To start with, why do customers need GoldenGate? Nick: Well, it delivers continuous operations, being able to continuously move data from one database to another database or data platform in efficiently and a high-speed manner, and it does this with very low overhead. Almost all the GoldenGate environments use transaction logs to pull the data out of the system, so we're not creating any additional triggers or very little overhead on that source system. GoldenGate can also enable real-time analytics, being able to pull data from all these different databases and move them into your analytics system in real time can improve the value that those analytics systems provide. Being able to do real-time statistics and analysis of that data within those high-performance custom environments is really important. 02:13 Nikita: Does it offer any benefits in terms of cost?  Nick: GoldenGate can also lower IT costs. A lot of times people run these massive OLTP databases, and they are running reporting in those same systems. With GoldenGate, you can offload some of the data or all the data to a low-cost commodity hardware where you can then run the reports on that other system. So, this way, you can get back that performance on the OLTP system, while at the same time optimizing your reporting environment for those long running reports. You can improve efficiencies and reduce risks. Being able to reduce the amount of downtime during planned and unplanned outages can really make a big benefit to the overall operational efficiencies of your company.  02:54 Nikita: What about when it comes to data sharing and data security? Nick: You can also reduce barriers to data sharing. Being able to pull subsets of data, or just specific pieces of data out of a production database and move it to the team or to the group that needs that information in real time is very important. And it also protects the security of your data by only moving in the information that they need and not the entire database. It also provides extensibility and flexibility, being able to support multiple different replication topologies and architectures. 03:24 Lois: Can you tell us about some of the use cases of GoldenGate? Where does GoldenGate truly shine?  Nick: Some of the more traditional use cases of GoldenGate include use within the multicloud fabric. Within a multicloud fabric, this essentially means that GoldenGate can replicate data between on-premise environments, within cloud environments, or hybrid, cloud to on-premise, on-premise to cloud, or even within multiple clouds. So, you can move data from AWS to Azure to OCI. You can also move between the systems themselves, so you don't have to use the same database in all the different clouds. For example, if you wanted to move data from AWS Postgres into Oracle running in OCI, you can do that using Oracle GoldenGate. We also support maximum availability architectures. And so, there's a lot of different use cases here, but primarily geared around reducing your recovery point objective and recovery time objective. 04:20 Lois: Ah, reducing RPO and RTO. That must have a significant advantage for the customer, right? Nick: So, reducing your RPO and RTO allows you to take advantage of some of the benefits of GoldenGate, being able to do active-active replication, being able to set up GoldenGate for high availability, real-time failover, and it can augment your active Data Guard and Data Guard configuration. So, a lot of times GoldenGate is used within Oracle's maximum availability architecture platinum tier level of replication, which means that at that point you've got lots of different capabilities within the Oracle Database itself. But to help eke out that last little bit of high availability, you want to set up an active-active environment with GoldenGate to really get true zero RPO and RTO. GoldenGate can also be used for data offloading and data hubs. Being able to pull data from one or more source systems and move it into a data hub, or into a data warehouse for your operational reporting. This could also be your analytics environment too. 05:22 Nikita: Does GoldenGate support online migrations? Nick: In fact, a lot of companies actually get started in GoldenGate by doing a migration from one platform to another. Now, these don't even have to be something as complex as going from one database like a DB2 on-premise into an Oracle on OCI, it could even be simple migrations. A lot of times doing something like a major application or a major database version upgrade is going to take downtime on that production system. You can use GoldenGate to eliminate that downtime. So this could be going from Oracle 19c to Oracle 23ai, or going from application version 1.0 to application version 2.0, because GoldenGate can do the transformation between the different application schemas. You can use GoldenGate to migrate your database from on premise into the cloud with no downtime as well. We also support real-time analytic feeds, being able to go from multiple databases, not only those on premise, but being able to pull information from different SaaS applications inside of OCI and move it to your different analytic systems. And then, of course, we also have the ability to stream events and analytics within GoldenGate itself.  06:34 Lois: Let's move on to the various topologies supported by GoldenGate. I know GoldenGate supports many different platforms and can be used with just about any database. Nick: This first layer of topologies is what we usually consider relational database topologies. And so this would be moving data from Oracle to Oracle, Postgres to Oracle, Sybase to SQL Server, a lot of different types of databases. So the first architecture would be unidirectional. This is replicating from one source to one target. You can do this for reporting. If I wanted to offload some reports into another server, I can go ahead and do that using GoldenGate. I can replicate the entire database or just a subset of tables. I can also set up GoldenGate for bidirectional, and this is what I want to set up GoldenGate for something like high availability. So in the event that one of the servers crashes, I can almost immediately reconnect my users to the other system. And that almost immediately depends on the amount of latency that GoldenGate has at that time. So a typical latency is anywhere from 3 to 6 seconds. So after that primary system fails, I can reconnect my users to the other system in 3 to 6 seconds. And I can do that because as GoldenGate's applying data into that target database, that target system is already open for read and write activity. GoldenGate is just another user connecting in issuing DML operations, and so it makes that failover time very low. 07:59 Nikita: Ok…If you can get it down to 3 to 6 seconds, can you bring it down to zero? Like zero failover time?   Nick: That's the next topology, which is active-active. And in this scenario, all servers are read/write all at the same time and all available for user activity. And you can do multiple topologies with this as well. You can do a mesh architecture, which is where every server talks to every other server. This works really well for 2, 3, 4, maybe even 5 environments, but when you get beyond that, having every server communicate with every other server can get a little complex. And so at that point we start looking at doing what we call a hub and spoke architecture, where we have lots of different spokes. At the end of each spoke is a read/write database, and then those communicate with a hub. So any change that happens on one spoke gets sent into the hub, and then from the hub it gets sent out to all the other spokes. And through that architecture, it allows you to really scale up your environments. We have customers that are doing up to 150 spokes within that hub architecture. Within active-active replication as well, we can do conflict detection and resolution, which means that if two users modify the same row on two different systems, GoldenGate can actually determine that there was an issue with that and determine what user wins or which row change wins, which is extremely important when doing active-active replication. And this means that if one of those systems fails, there is no downtime when you switch your users to another active system because it's already available for activity and ready to go. 09:35 Lois: Wow, that's fantastic. Ok, tell us more about the topologies. Nick: GoldenGate can do other things like broadcast, sending data from one system to multiple systems, or many to one as far as consolidation. We can also do cascading replication, so when data moves from one environment that GoldenGate is replicating into another environment that GoldenGate is replicating. By default, we ignore all of our own transactions. But there's actually a toggle switch that you can flip that says, hey, GoldenGate, even though you wrote that data into that database, still push it on to the next system. And then of course, we can also do distribution of data, and this is more like moving data from a relational database into something like a Kafka topic or a JMS queue or into some messaging service. 10:24 Raise your game with the Oracle Cloud Applications skills challenge. Get free training on Oracle Fusion Cloud Applications, Oracle Modern Best Practice, and Oracle Cloud Success Navigator. Pass the free Oracle Fusion Cloud Foundations Associate exam to earn a Foundations Associate certification. Plus, there's a chance to win awards and prizes throughout the challenge! What are you waiting for? Join the challenge today by visiting visit oracle.com/education. 10:58 Nikita: Welcome back! Nick, does GoldenGate also have nonrelational capabilities?  Nick: We have a number of nonrelational replication events in topologies as well. This includes things like data lake ingestion and streaming ingestion, being able to move data and data objects from these different relational database platforms into data lakes and into these streaming systems where you can run analytics on them and run reports. We can also do cloud ingestion, being able to move data from these databases into different cloud environments. And this is not only just moving it into relational databases with those clouds, but also their data lakes and data fabrics. 11:38 Lois: You mentioned a messaging service earlier. Can you tell us more about that? Nick: Messaging replication is also possible. So we can actually capture from things like messaging systems like Kafka Connect and JMS, replicate that into a relational data, or simply stream it into another environment. We also support NoSQL replication, being able to capture from MongoDB and replicate it onto another MongoDB for high availability or disaster recovery, or simply into any other system. 12:06 Nikita: I see. And is there any integration with a customer's SaaS applications? Nick: GoldenGate also supports a number of different OCI SaaS applications. And so a lot of these different applications like Oracle Financials Fusion, Oracle Transportation Management, they all have GoldenGate built under the covers and can be enabled with a flag that you can actually have that data sent out to your other GoldenGate environment. So you can actually subscribe to changes that are happening in these other systems with very little overhead. And then of course, we have event processing and analytics, and this is the final topology or flexibility within GoldenGate itself. And this is being able to push data through data pipelines, doing data transformations. GoldenGate is not an ETL tool, but it can do row-level transformation and row-level filtering.  12:55 Lois: Are there integrations offered by Oracle GoldenGate in automation and artificial intelligence? Nick: We can do time series analysis and geofencing using the GoldenGate Stream Analytics product. It allows you to actually do real time analysis and time series analysis on data as it flows through the GoldenGate trails. And then that same product, the GoldenGate Stream Analytics, can then take the data and move it to predictive analytics, where you can run MML on it, or ONNX or other Spark-type technologies and do real-time analysis and AI on that information as it's flowing through.  13:29 Nikita: So, GoldenGate is extremely flexible. And given Oracle's focus on integrating AI into its product portfolio, what about GoldenGate? Does it offer any AI-related features, especially since the product name has “23ai” in it? Nick: With the advent of Oracle GoldenGate 23ai, it's one of the two products at this point that has the AI moniker at Oracle. Oracle Database 23ai also has it, and that means that we actually do stuff with AI. So the Oracle GoldenGate product can actually capture vectors from databases like MySQL HeatWave, Postgres using pgvector, which includes things like AlloyDB, Amazon RDS Postgres, Aurora Postgres. We can also replicate data into Elasticsearch and OpenSearch, or if the data is using vectors within OCI or the Oracle Database itself. So GoldenGate can be used for a number of things here. The first one is being able to migrate vectors into the Oracle Database. So if you're using something like Postgres, MySQL, and you want to migrate the vector information into the Oracle Database, you can. Now one thing to keep in mind here is a vector is oftentimes like a GPS coordinate. So if I need to know the GPS coordinates of Austin, Texas, I can put in a latitude and longitude and it will give me the GPS coordinates of a building within that city. But if I also need to know the altitude of that same building, well, that's going to be a different algorithm. And GoldenGate and replicating vectors is the same way. When you create a vector, it's essentially just creating a bunch of numbers under the screen, kind of like those same GPS coordinates. The dimension and the algorithm that you use to generate that vector can be different across different databases, but the actual meaning of that data will change. And so GoldenGate can replicate the vector data as long as the algorithm and the dimensions are the same. If the algorithm and the dimensions are not the same between the source and the target, then you'll actually want GoldenGate to replicate the base data that created that vector. And then once GoldenGate replicates the base data, it'll actually call the vector embedding technology to re-embed that data and produce that numerical formatting for you.  15:42 Lois: So, there are some nuances there… Nick: GoldenGate can also replicate and consolidate vector changes or even do the embedding API calls itself. This is really nice because it means that we can take changes from multiple systems and consolidate them into a single one. We can also do the reverse of that too. A lot of customers are still trying to find out which algorithms work best for them. How many dimensions? What's the optimal use? Well, you can now run those in different servers without impacting your actual AI system. Once you've identified which algorithm and dimension is going to be best for your data, you can then have GoldenGate replicate that into your production system and we'll start using that instead. So it's a nice way to switch algorithms without taking extensive downtime. 16:29 Nikita: What about in multicloud environments?  Nick: GoldenGate can also do multicloud and N-way active-active Oracle replication between vectors. So if there's vectors in Oracle databases, in multiple clouds, or multiple on-premise databases, GoldenGate can synchronize them all up. And of course we can also stream changes from vector information, including text as well into different search engines. And that's where the integration with Elasticsearch and OpenSearch comes in. And then we can use things like NVIDIA and Cohere to actually do the AI on that data.  17:01 Lois: Using GoldenGate with AI in the database unlocks so many possibilities. Thanks for that detailed introduction to Oracle GoldenGate 23ai and its capabilities, Nick.  Nikita: We've run out of time for today, but Nick will be back next week to talk about how GoldenGate has evolved over time and its latest features. And if you liked what you heard today, head over to mylearn.oracle.com and take a look at the Oracle GoldenGate 23ai Fundamentals course to learn more. Until next time, this is Nikita Abraham… Lois: And Lois Houston, signing off! 17:33 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

The final episode of the multicloud series focuses on Oracle Database@Azure, a powerful cloud database solution. Hosts Lois Houston and Nikita Abraham, along with Senior Manager of CSS OU Cloud Delivery Samvit Mishra, discuss how this service allows customers to run Oracle databases within the Microsoft Azure data center, simplifying deployment and management. The discussion also highlights the benefits of native integration with Azure services, eliminating the need for complex networking setups.   Oracle Cloud Infrastructure Multicloud Architect Professional: https://mylearn.oracle.com/ou/course/oracle-cloud-infrastructure-multicloud-architect-professional-2025-/144474 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, and the OU Studio Team for helping us create this episode.   ---------------------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Lois: Hello and welcome to the Oracle University Podcast! I'm Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services. Nikita: Hi everyone! For the last two weeks, we've been talking about different aspects of multicloud. In the final episode of this three-part series, Samvit Mishra, Senior Manager of CSS OU Cloud Delivery, joins us once again to tell us about the Oracle Database@Azure service. Hi Samvit! Thanks for being here today. Samvit: Hi Niki! Hi Lois! Happy to be back. 01:01 Lois: In our last episode, we spoke about the strategic partnership between Oracle and Microsoft, and specifically discussed the Oracle Interconnect for Azure.  Nikita: Yeah, and Oracle Database@Azure is yet another addition to this partnership. What can you tell us about this service, Samvit? Samvit: The Oracle Database@Azure service, which was made generally available in 2023, runs right inside the Microsoft Azure data center and uses Azure networking. The entire Oracle Cloud Database Service infrastructure resides in the Azure data center, while it is managed by an expert Oracle Cloud Infrastructure operations team.  It provides customers simple and secure access to Oracle Cloud database services within their chosen Azure deployment region, without getting into the complexity of managing networking between the cloud vendors. It is natively integrated with various Microsoft Azure services. This provides a seamless user experience when configuring and using the different Azure services with OCI Oracle database, since much of the complexity associated with the configuration is greatly simplified.  There is no need to set up a private interconnect between Microsoft Azure and OCI because the service itself resides within the Azure data center and uses the Azure network. This is very beneficial in terms of strategic deployment because customers can experience microseconds network latency between the endpoints, while receiving a high-performance database environment.  02:42 Nikita: How do I get started with the Oracle Database@Azure service? Samvit: You begin by purchasing the subscription from Oracle and setting up your billing account. Then you provision the database, resources, and service.  With that you are ready to configure your application to connect to the database and work on the remaining deployment. As you continue using the service, you can monitor the different resource metrics using the Azure monitoring services and analyze those logs using Azure Log Analytics.  03:15 Lois: So, the adoption is pretty easy, then. What about the responsibilities? Who is responsible for what? Samvit: The Oracle Cloud operations team is entirely responsible for managing the Exadata Database Infrastructure and the VM cluster resources that are provisioned in the Microsoft Azure data center.  Oracle is responsible for maintaining the service software and infrastructure by applying updates as they are released. Any issues arising from the OCI Database Service and the resources will be addressed by Oracle Support. You have to raise a support ticket for them to investigate and provide a resolution.  And as Azure customers, you have to do rightsizing, based on your workload needs, and provision the Exadata Database Infrastructure and VM cluster in the OCI pod within the Azure data center. You have to provision the database in Exadata Database Service, apply the database and system updates, and take advantage of the cloud automation to maintain and manage the database.  You have to load data, establish the connectivity, and support development on your database. As a customer, you monitor the database and infrastructure metrics and events, and also analyze those logs using the Microsoft Azure-provided native services.  04:42 Nikita: Samvit, what sort of challenges were being faced by customers that necessitated the creation of the Oracle Database@Azure service?  Samvit: A common deployment scenario in customer environments was that a lot of critical applications, which could be packaged applications, in-house applications, or customized third-party applications, used Oracle Database as their primary database solution.  These Oracle databases were deployed in Exadata Infrastructure on-premises or even in Enterprise Server hardware. Some customers evaluated and migrated many of their packaged and other applications to Microsoft Azure compute. Since Oracle Exadata was not supported in Azure, they had to configure a hybrid deployment in order to use Oracle databases that reside in the Exadata infrastructure on-premises.  They needed to configure a dedicated and secure network between the Azure data center and their on-premises data center. This added complexity, incurred high costs, had a latency effect, and was even unreliable. There were also cases where customers migrated Oracle databases on Enterprise Server on-premises to Oracle databases hosted on Azure compute.  This did not boost efficiency to a large scale. And those were the only options available when provisioning Oracle Database in Azure because Exadata was not available earlier in Azure. 06:18 Lois: And how has that been resolved now? Samvit: With the Oracle Database@Azure service, customer requirements have been aptly met by allowing them to host their Oracle databases on Exadata infrastructure, right next to their application in the Azure data center.  Customers, while migrating their applications to Azure compute, can also migrate their Oracle databases on-premises on Exadata infrastructure directly to Exadata Database Service in Azure. And Oracle databases that are on Enterprise Server on-premises can be consolidated directly into Exadata Database Service in Azure, providing them the benefits of scalability, security, performance, and availability, all that are inherent property of OCI Oracle Exadata Database Service.  Customers can see growth in the operational efficiency, saving on the overall cost.  07:17 Nikita: Can you take us through the process of deployment?  Samvit: It's quite simple, actually. First, you deploy the Exadata Database Service that is plugged into Azure VNET. Next, you provision the required number of databases, which might be migrated as is or with a consolidated exercise.  You can use any of the Oracle database tools or utilities to do the migration or even use the Oracle Zero Downtime Migration method to automate the entire Oracle database migration. Finally, migrate your enterprise application into the Azure environment.  Establish the required network configuration to allow communication between the migrated applications and Oracle databases.  And then you are all set to publish your application that is running entirely in Azure. You can leverage other Azure services, like monitoring, log analytics, Power BI, or DevOps tools, to enhance existing or even build and deploy newer enterprise applications that are powered by OCI Oracle Database Service in the back end.  08:25 Lois: What about multi-cloud deployment scenarios where applications reside in Azure, but the Oracle databases are deployed on third-party cloud providers, either as a native solution or in computes? Samvit: These Oracle databases can be migrated to Exadata Database Service in the Oracle Database@Azure service.  There is no need for the complex cross-cloud connectivity setup between the vendors. And at the same time, you experience the lowest latency between the application and the database deployment. 09:05 Want to learn how to design stunning, responsive enterprise applications directly from your browser with minimal coding? The new Oracle APEX Developer Professional learning path and certification enables you to leverage AI-assisted development, including generative AI and Database 23ai, to build secure, scalable web and mobile applications with advanced AI-powered features. From now through May 15, 2025, we're waiving the certification exam fee (valued at $245). So, what are you waiting for? Visit mylearn.oracle.com to get started today. 09:45 Nikita: Welcome back! Samvit, what's the onboarding process like? Samvit: You have to complete the onboarding process to use the service in Microsoft Azure. But before you do that, you first have to complete the subscription process. You must have an active Microsoft Azure account subscription that will be used for subscribing and onboarding the Oracle Database@Azure service.  To subscribe to Oracle Database@Azure, you need to purchase an Oracle Database@Azure private offer from Azure Marketplace. As a customer, you will first reach out to Oracle Sales and negotiate a price for the service. Oracle will provide you with the billing account ID and contact details of the person within the organization who will be handling the service.  After this, Oracle will create a private offer in Azure Marketplace.  10:40 Lois: Sorry to interrupt you, but what's a private offer? Samvit: That's alright, Lois. Private offers are basically solutions or services created for customers by a Microsoft partner, which, in this case, is Oracle. Purchase of those private offers happens from the private offer management page of Azure Marketplace.  But there is a prerequisite. The Azure account must be enabled to make private offer purchases on the subscription from Azure Marketplace. You can refer to the Azure documentation to enable the account, if it is not enabled. You review the offer terms and accept the purchase offer, which will take you to the Create Oracle Subscription page.  You validate the subscription and other particulars and proceed with the process. After the service is deployed, the purchase status of the private offer changes to subscribed.  There are a few points to note here. Billing and payment are done via Azure, and you can use Microsoft Azure Consumption Commitment.  You can also use your on-premises licenses with the Bring Your Own License option and the Unlimited License Agreements to pay towards your service consumption. And you also receive Oracle Support rewards for every dollar spent on the service.  12:02 Nikita: OK, now that I'm subscribed, what's next? Samvit: After you complete the subscription step, Oracle Database@Azure will appear as an Azure resource, just like any other Azure service, and you can move on to onboarding. Onboarding begins with the linking of your OCI account, which will be used for provisioning and managing database resources.  The account is also used for provisioning infrastructure and software maintenance updates for the database service. You can either provide an existing OCI account or create a new one. Then you set up Identity Federation between the Azure account and the OCI tenancy.  This can authenticate login to the OCI portal using Azure credentials, which you require while performing certain operations in OCI. For example, provisioning databases, getting infrastructure and software maintenance updates, and so on. This is an optional step, but it is recommended that you complete the Federation.  The last step is to authorize users by assigning groups and roles in order to have the needed privileges to perform different operations. For example, some groups of users can manage Exadata Database Service resources in Azure, while some can manage the databases in OCI.  You can refer to OCI documentation to get detailed descriptions of roles and group names. 13:31 Lois: Right. That will ensure you assign the correct permissions to the appropriate users. Samvit: Exactly. Assigning the correct roles and permissions to individuals inside the organization is a necessary step for transacting in the marketplace and guaranteeing a smooth purchasing experience. Azure Marketplace uses Azure Role-Based Access Control to enable you to acquire solutions certified to run on Azure. Those are then going to determine the purchasing privileges within the organization.  14:03 Nikita: There's so much more we can discuss about Oracle Database@Azure, but we have to stop somewhere! Thank you so much, Samvit, for joining us over these last three episodes. Lois: Yeah, it's been great to have you, Samvit. Samvit: Thank you for having me. Nikita: Remember, we also have the Oracle Database@Google Cloud service. So, if you want to learn about that, or even if you want to dive deeper into the topics we covered today, go to mylearn.oracle.com and search for the Oracle Cloud Infrastructure Multicloud Architect Professional course.  Lois: There are a lot of demonstrations that you'll surely find useful. Well, that's all we have for today. Until next time, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 14:43 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

This week, hosts Lois Houston and Nikita Abraham are shining a light on multicloud, a game-changing strategy involving the use of multiple cloud service providers. Joined by Senior Manager of CSS OU Cloud Delivery Samvit Mishra, they discuss why multicloud is becoming essential for businesses, offering freedom from vendor lock-in and the ability to cherry-pick the best services. They also talk about Oracle's pioneering role in multicloud and its partnerships with Microsoft Azure, Google Cloud, and Amazon Web Services.   Oracle Cloud Infrastructure Multicloud Architect Professional: https://mylearn.oracle.com/ou/course/oracle-cloud-infrastructure-multicloud-architect-professional-2025-/144474 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, and the OU Studio Team for helping us create this episode.   -----------------------------------------------------------------   Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:25 Lois: Hello and welcome to the Oracle University Podcast! I'm Lois Houston, Director of Innovation Programs with Oracle University, and with me today is Nikita Abraham, Team Lead: Editorial Services. Nikita: Hi everyone! Today, we're moving on to multicloud. In our next three episodes, we'll be discussing what multicloud is and why there's so much of a buzz around it. With us is Samvit Mishra, Senior Manager of CSS OU Cloud Delivery. Hi Samvit! Thanks for joining us today. 00:55 Samvit: Hi Niki! Hi Lois! Happy to be here. Lois: So Samvit, we know that Oracle has been an early adopter of multicloud and a pioneer in multicloud services. But for anyone who isn't familiar with what multicloud is, can you explain what it means? Samvit: Absolutely, Lois. Multicloud is a very simple, basic concept. It is the coordinated use of cloud services from more than one cloud service provider.  01:21 Nikita: But why would someone want to use more than one cloud service provider? Samvit: There are many reasons why a customer might want to leverage two or more cloud service providers. First, it addresses the very real concern of mitigating or avoiding vendor lock-in. By using multiple providers, companies can avoid being tied down to one vendor and maintain their flexibility. 01:45 Lois: That's like not putting all your eggs in one basket, so to speak. Samvit: Exactly. Another reason is that customers want the best of breed. What that means is basically leveraging or utilizing the best product from one cloud service provider and pairing it against the best product from another cloud service provider. Getting a solution out of the combined products…out of the coordinated use of those services.  02:14 Nikita: So, it sounds like multicloud is becoming the new normal. And as we were saying before, Oracle was a pioneer in this space. But why did we embrace multicloud so wholeheartedly? Samvit: We recognized that our customers were already moving in this direction. Independent studies from Flexera found that 89% of the subjects of the study used multicloud. And we conducted our own study and came to similar numbers. Over 90% of our customers use two or more cloud service providers.  HashiCorp, the big infrastructure as code company, came to similar numbers as well, 94%. They basically asked companies if multicloud helped them advance their business goals. And 94% said yes. And all this is very recent data.  03:04 Lois: Can you give us the backstory of Oracle's entry into the multicloud space? Samvit: Sure. So back in 2019, Oracle and Microsoft Azure joined forces and announced the interconnect service between Oracle Cloud Infrastructure and Microsoft Azure. The interconnect was between Oracle's FastConnect and Microsoft Azure's ExpressRoute. This was a big step, as it allowed for a direct connection between the two providers without needing a third-party. And now we have several of our data centers interconnected already. So, out of the 48 regions, 12 of them are already interconnected. And more are coming. And you can very easily configure the interconnect.  This interconnectivity guarantees low latency, high throughput, and predictable performance. And also, on the OCI side, there are no egress or ingress charges for your data.  There's also a product called Oracle Database@Azure, where Oracle and Microsoft deliver Oracle Database services in Microsoft Azure data centers.  04:12  Lois: That's exciting! And what are the benefits of this product? Samvit: The main advantage is the co-location. Being co-located with the Microsoft Azure data center offers you native integration between Azure and OCI resources. No manual configuration of a private interconnect between the two providers is needed. You're going to get microsecond latency between your applications and the Oracle Database.  The OCI-native Exadata Database Service is available on Oracle Database@Azure. This enables you to get the highest level of Oracle Database performance, scalability, security, and availability. And your tech support can be provided either from Microsoft or from Oracle.  05:03 Unlock the power of AI Vector Search with our new course and certification. Get more accurate search results, handle complex datasets easily, and supercharge your data-driven decisions. From now through May 15, 2025, we are waiving the certification exam fee (valued at $245). Visit mylearn.oracle.com to enroll. 05:30 Nikita: Welcome back. Samvit, there have been some new multicloud milestones from OCI, right? Can you tell us about them?  Samvit: That's right, Niki. I am thrilled to share the latest news on Oracle's multicloud partnerships. We now have agreements with Microsoft Azure, Google Cloud, and Amazon Web Services.  So, as we were discussing earlier, with Azure, we have the Oracle Interconnect for Azure and Oracle Database@Azure. Now, with Google Cloud, we have the Oracle Interconnect for Google Cloud. And it is very similar to the Oracle Interconnect for Azure. With Google Cloud, we have physically interconnected data centers and they provide a sub-2 millisecond latency private interconnection. So, you can come in and provision virtual circuits going from Oracle FastConnect to Google Cloud Interconnect.  And the best thing is that there are no egress or ingress charges for your data. The way it is structured is you have your Oracle Cloud Infrastructure on one side, with your virtual cloud network, your subnets, and your resources. And on the other side, you have your Google Cloud router with your virtual private cloud subnet and your resources interconnecting.  You initiate the connectivity on the Google Cloud side, retrieve the service key and provide that service key to Oracle Cloud Infrastructure, and complete the interconnection on the OCI side. So, for example, our US East Ashburn interconnect will match with us-east4 on the Google Cloud side.  07:08 Lois: Now, wasn't the other major announcement Oracle Database@Google Cloud? Tell us more about that, please. Samvit: With Oracle Database@Google Cloud, you can run your applications on Google Cloud and the database as well inside the Google Cloud platform. That's the Oracle Cloud Infrastructure database co-located in Google Cloud platform data centers. It allows you to run native integration between GCP and OCI resources with no manual configuration of private interconnect between these two cloud service providers.  That means no FastConnect, no Interconnect because, again, the database is located in the Google Cloud data center. And you're going to get microsecond latency and the OCI native Exadata Database Service. So, you're going to gain the highest level of Oracle Database performance, scalability, security, and availability.  08:04 Lois: And how is the tech support managed? Samvit: The technical support is a collaboration between Google Cloud and Oracle Cloud Infrastructure. That means you can either have the technical support provided to completion by Google Cloud or by Oracle. One of us will provide you with an end-to-end solution.  08:22 Nikita: During CloudWorld last year, we also announced Oracle Database@AWS, right?  Samvit: Yes, Niki. That's where Oracle and Amazon Web Services deliver the Oracle Database service on Oracle Cloud Infrastructure in your AWS data center. This will provide you with native integration between AWS and OCI resources, with no manual configuration of private interconnect between AWS and OCI. And you're getting microsecond latency with the OCI-native Exadata Database Service.  And again, as with Oracle Database@Google Cloud and Oracle Database@Azure, you're gaining the highest level of Oracle Database performance, scalability, security, and availability. And the technical support is provided by either AWS or Oracle all the way to completion. Now, Oracle Database@AWS is currently available in limited preview, with broader availability in the coming months as it expands to new regions to meet the needs of our customers.  09:28 Lois: That's great. Now, how does Oracle fare when it comes to pricing, especially compared to our major cloud competitors?  Samvit: Our pricing is pretty consistent. You'll see that in all cases across the world, we have the less expensive solution for you and the highest performance as well.  09:45 Nikita: Let's move on to some use cases, Samvit. How might a company use the multicloud setup? Samvit: Let's start with the split-stack architecture between Oracle Cloud Infrastructure and Microsoft Azure.  Like I was saying earlier, this partnership dates back to 2019. And basically, we eliminated the FastConnect partner from the middle. And this will provide you with high throughput, low latency, and very predictable performance, all of this on highly available links. These links are redundant, ensuring business continuity between OCI and Azure.  And you can have your database on the OCI side and your application on Microsoft Azure side or the other way around. You can have SQL Server on Azure and the application running on Oracle Cloud Infrastructure. And this is very easy to configure.  10:34 Lois: It really sounds like Oracle is at the forefront of the multicloud revolution. Thanks so much, Samvit, for shedding light on this exciting topic.  Samvit: It was my pleasure.  Nikita: That's a wrap for today. To learn more about what we discussed, head over to mylearn.oracle.com and search for the Oracle Cloud Infrastructure Multicloud Architect Professional course. In our next episode, we'll take a close look at Oracle Interconnect for Azure. Until then, this is Nikita Abraham… Lois: And Lois Houston, signing off! 11:05 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

Oracle announced the Oracle Fusion Cloud Applications Suite is now available on Oracle EU Sovereign Cloud to enable private and public sector organizations across the European Union. NetSuite announced it is migrating to Oracle Autonomous Database to enable its customers to take advantage of the enhanced security, reliability, and performance of a fully managed Oracle Database in OCI with integrated AI. Salesforce, in collaboration with Hugging Face, Cohere, and Carnegie Mellon University, announced the release of the AI Energy Score, a first-of-its-kind benchmarking tool that enables AI developers and users to evaluate, identify, and compare the energy consumption of AI models.Connect with us!https://www.erpadvisorsgroup.com866-499-8550LinkedIn:https://www.linkedin.com/company/erp-advisors-groupTwitter:https://twitter.com/erpadvisorsgrpFacebook:https://www.facebook.com/erpadvisorsInstagram:https://www.instagram.com/erpadvisorsgroupPinterest:https://www.pinterest.com/erpadvisorsgroupMedium:https://medium.com/@erpadvisorsgroup

In this episode, Lois Houston and Nikita Abraham discuss the basics of MySQL installation with MySQL expert Perside Foster. Perside covers every key step, from preparing your environment and selecting the right software, to installing MySQL, setting up secure initial user accounts, configuring the system, and managing updates efficiently.   MySQL 8.4 Essentials: https://mylearn.oracle.com/ou/course/mysql-84-essentials/141332/226362 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, and the OU Studio Team for helping us create this episode.   --------------------------------------------------------   Episode Transcript:   00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative  podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Nikita: Welcome back to another episode of the Oracle University Podcast. I'm Nikita Abraham, Team Lead of Editorial Services with Oracle University, and I'm joined by Lois Houston, Director of Innovation Programs. Lois: Hi everyone! In our last episode, we spoke about Oracle MySQL ecosystem and its various components. We also discussed licensing, security, and some key tools. What's on the agenda for today, Niki? 00:52 Nikita: Well Lois, today, we're going beyond tools and features to talk about installing MySQL. Whether you're setting up MySQL for the first time or looking to understand its internal structure a little better, this episode will be a valuable guide.  Lois: And we're lucky to have Perside Foster back with us. Perside is a MySQL Principal Solution Engineer at Oracle. Hi Perside! Say I wanted to get started and install MySQL. What factors should I keep in mind before I do that?  01:23 Perside: The first thing to consider is the environment for the database server. MySQL is supported on many different Linux distributions. You can also run it on Windows or Apple macOS.  You can run MySQL on a variety of host platforms. You can use dedicated servers in a server room or virtual machines in a data center. Developers might prefer to deploy on Docker or Kubernetes containers. And don't forget, you can deploy HeatWave, the MySQL cloud version, in many different clouds. MySQL has great multithreading capability. It also has support for Non-Uniform Memory Access or NUMA. This is particularly important if you run large systems with hundreds of concurrent connections. MySQL storage engine, InnoDB, makes effective use of your available memory. It stores your active data in a buffer pool. This greatly improves access time compared to reading straight from disk. Of course, SSDs and other solid state media are much faster than hard disks. But don't forget, MySQL can make full use of that performance benefit too. Redundancy is very important for the MySQL server. Hardware with redundant power supply, storage media, and network connections can make all the difference to your uptime. Without redundancy, a single point of failure will bring down the server if it fails. 03:26 Nikita: Got it. Perside, from where can I download the different editions of MySQL? Perside: Our most popular software is the MySQL Community Edition. It is available at no cost for mysql.com for many platforms. This version is why MySQL is the most popular database for web application. And it is also open source. MySQL Enterprise Edition is the commercial edition. It is fully supported by Oracle. You can get it from support.oracle.com as an Oracle customer. If you want to try out the enterprise features but are not yet a customer, you can get the latest version of MySQL as a trial edition from edelivery.oracle.com. Because MySQL is open source, you can get the source code from either mysql.com or GitHub. Most people don't need the source. But any developer who wants to modify the code or even contribute back to the project are welcome to do so.  04:43 Lois: Perside, can you walk us through MySQL's release model? Perside: This is divided into LTS and Innovation releases, each with a different target audience. LTS stands for long-term support. MySQL 8.4 is an LTS release and will be supported for several years. LTS releases are feature-stable. When you install an LTS release, you can apply future bug fixes and security patches without changing any behavior in the product. The bug fixes and security patches are designed to be backward compatible. This means you can upgrade easily from previous releases. LTS releases come every two years. This allows you to maintain a stable system without having to change your underlying application too frequently. You will not be forced to upgrade after two years. You can continue to enjoy support for an LTS release for up to eight years. Along with LTS releases, we also have Innovation releases. These contain the latest leading-edge features that are developed even in the middle of an LTS cycle. You can upgrade from LTS to Innovation and back again, depending on which features you require in your application. Innovation releases have a much more rapid cadence. You can get the latest features every quarter. This means Innovation releases are supported only for their specific release. So, if you're on the Innovation track, you must upgrade more frequently. All editions of MySQL are shipped as both LTS and Innovation releases. This includes the self-managed editions and also HeatWave in the cloud. You can treat both LTS and Innovation releases as production-ready. This means they are generally available releases. Innovation does not mean beta quality software. You get the same quality support from Oracle whether you're using LTS or Innovative software. The MySQL client software and other tools will operate with both LTS and innovation releases.  07:43 Nikita: What are connectors in the context of MySQL? Perside: Connectors are the language-specific software component that connects your application to MySQL. You should use the latest version of connectors. Connectors are also production-ready, generally available software. They will work with any version of MySQL that is supported at the time of the connector's release. 08:12 Nikita: How does MySQL integrate with Docker and other container platforms? Perside: You might already be familiar with the Docker store. It is used for getting containerized images of software. As an Oracle customer, you might be familiar with My Oracle Support. It provides support and updates for all supported Oracle software in patches.  MySQL works well with virtualization and container platform, including Docker. You can get images from the Community Edition on Docker Hub. If you are an Enterprise Edition customer, you can get images from the Docker store for MySQL Oracle Support or from Oracle container's registry.  09:04 Lois: What resources are available for someone who wants to know more about MySQL? Perside: MySQL has detailed documentation. You should familiarize yourself with the documentation as you prepare to install MySQL. The reference manual for both Community and Enterprise editions are available at the Developer Zone at dev.mysql.com. Oracle customers also have access to the knowledge base at support.oracle.com. It contains support information on use cases and reference architectures. The product team regularly posts announcements and technical articles to several blogs. These blogs often contain pre-release announcements of upcoming features to help you prepare for your next project. Also, you'll find deep dives into technical topics and complex problems that MySQL solves. This includes some problems specific to highly available architecture. We also feature individual blogs from high profile members of our team. These include the MySQL Community evangelist lefred. He posts about upcoming events and interesting features. Also, Dimitri Kravchuk offers blogs that provide deep dives into performance. 10:53 Nikita: Ok, now that I have all this information and am prepped and ready, how do I actually install MySQL on my operating system? What's the process like? Perside: You can install MySQL on various operating system, depending on your needs. These might include several distributions of Linux or UNIX, Windows, Mac OS, Oracle Linux based on the Unbreakable Enterprise Kernel, Solaris, and freeBSD. As always, the MySQL documentation provides full details on supported operating system. It also provides the specific installation steps for each of the operating system. Plus, it tells you how to perform the initial configuration and further administrative steps.  If you're installing on Windows, you have a couple of options. First, the MySQL Installer utility is the easiest way to install MySQL. It installs MySQL and performs the initial configuration based on options that you choose at installation time. It includes not only the MySQL server, but also the most important connectors, the MySQL Shell Client, MySQL Workbench Client with user interface and common utilities for troubleshooting and administration. It also installs several sample databases and models and documentation. It's the easiest way to install MySQL because it uses an installation wizard. It lets you select your installation target location, what components to install, and other options. 12:47 Lois: But what if I want to have more control?  Perside: For more control over your installation, you can install MySQL from the binary zip archive. This does not include sample or supporting tools and connectors, but only contains the application's binaries, which you can install anywhere you want. This means that the initial configuration is not performed by selecting an option through a wizard. Instead, you must configure the Windows service and MySQL configuration file yourself. Linux installation is more varied. This is because of the different distribution and also because of its terms of flexibility. On many distributions of Linux, you can use the package manager native to that distribution. For example, you can use the yum package manager in all Oracle Linux to install RPM files. You can also use a binary archive to install only the files. To decide which method you want to use, it's based on several factors. How much you know about MySQL files and configuration and the operating system on which you're going to do the installation? Any applicable standard or operating procedures within your own company's IT infrastructure, how much control do you need over this installation and how flexible a method do you need? For example, the RPM package for Oracle Linux, it installs the file in specific locations and with a specific service, MySQL user account. 14:54 Transform the way you work with Oracle Database 23ai! This cutting-edge technology brings the power of AI directly to your data, making it easier to build powerful applications and manage critical workloads. Want to learn more about Database 23ai? Visit mylearn.oracle.com to pick from our range of courses and enroll today! 15:18 Nikita: Welcome back! Is there a way for me to extend the functionality of MySQL beyond its default capabilities? Perside: Much of MySQL's behavior is standard and always exists when you install the server. However, you can configure some additional behaviors by extending MySQL with plugins or components. Plugins operate closely with the server and by calling APIs exposed by the server, they add features by providing extra functions or variables. Not only do they add variables, they can also interact with the servers on global variables and functions. That makes them work as if they are dynamically loadable parts of the server itself. Components also extend functionality, but they are separate from the server and extend its functionality through a service-based architecture. You can also extend MySQL in other ways-- by creating stored procedures, triggers, and functions with standard SQL and MySQL extensions to that language, or by creating external dynamically loaded user-defined functions. 16:49 Lois: Perside, can we talk about the initial user accounts? Perside: A MySQL account identifier is more than just a username and password. It consists of three elements, two that identify the account, and one that is used for authentication. The three elements are the username, it's used to log in from the client; the hostname element, it identifies a computer or set of computers; and the password, it must be provided to gain access to MySQL. The hostname is a part of the account identifier that controls where the user can log in. It is typically a DNS computer name or an IP address. You can use a wildcard, which is the percentage sign to allow the name user to log in from any connected host, or you can use the wildcard as part of an IP address to allow login from a limited range of IP addresses. 17:58 Nikita: So, what happens when I install MySQL on my computer? Perside: When you first install MySQL on your computer, it installs several system accounts. The only user account that you can log in to is the administrative account. That's called the root account. Depending on the installation method that you use, you'll either see the initial root password on the console as you install the server, or you can read it from the log file. For security reasons, the password of a new account, such as the root account must change. MySQL prevents you from executing any other operation with that account until you have changed the password.  18:46 Lois: What are the system requirements for installing and running MySQL? Perside: The MySQL service must run as a system-level user. Each operating system has its own method for creating such a user. All operating system follows the same general principles. However, when using the MySQL installer on Windows or the RPM package installation on Oracle Linux, each installation process creates and configure the system-level user. 19:22 Lois: Perside, since MySQL is always evolving, how do I upgrade it when newer versions become available?  Perside: When you upgrade MySQL, you have to bring the server down so that the upgrade process can replace all of the relevant binary executable files. And if necessary, update the data and configuration to suit the new software. The safest thing to do is to back up your whole MySQL environment. This includes not only your data in the files, such as binaries and configuration files, but also logical elements, including triggers, stored procedures, user configuration, and anything else that's required to rebuild your system. The upgrade process gives you two main options. An in-place upgrade uses your existing data directory. After you shut down your MySQL server process, you either replace the package or binaries with new versions, or you install the new binary executables in a new location and point your symbolic links to this new location. The server process detects that the data directory belongs to an earlier version and performs any required upgrade checks. 20:46 Lois: Thank you, Perside, for taking us through the practical aspects of using MySQL. If you want to learn about the MySQL architecture, visit mylearn.oracle.com and search for the MySQL 8.4: Essentials course.  Nikita: Before you go, we wanted to take a minute to thank you for taking the Oracle University Podcast survey that we put out at the end of last year. Your insights were invaluable and will help shape our future episodes. Lois: And if you missed taking the survey but have feedback to share, you can write to us at ou-podcast_ww@oracle.com. That's ou-podcast_ww@oracle.com. We'd love to hear from you. Join us next week for a discussion on MySQL database design. Until then, this is Lois Houston… Nikita: And Nikita Abraham signing off! 21:45 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

An airhacks.fm conversation with Gerald Venzl (@GeraldVenzl) about: discussion on prepared statements and their benefits in Oracle databases, explanation of hard parsing vs soft parsing in database queries, overview of connection pooling and its importance in database performance, introduction to Oracle's Database Resident Connection Pool (DRCP), exploration of Oracle's support for serverless workloads, discussion on PL/SQL and JavaScript support in Oracle databases, brief mention of ADA programming language and its influence on PL/SQL, introduction to GraalVM and its role in Oracle databases, comparison of performance between PL/SQL and JavaScript in Oracle, mention of Oracle database support for ARM architecture including M1 Macs and Raspberry Pi 5, explanation of database sharding vs partitioning, discussion on the benefits of stored procedures for data-intensive operations Gerald Venzl on twitter: @GeraldVenzl

On this Screaming in the Cloud Replay, Corey is joined by Nipun Agarwal, Senior Vice President of MySQL HeatWave Development at Oracle, to discuss the release of MySQL HeatWave and how it will benefit users among the sea of database offerings on AWS. Nipun reveals why Oracle decided to develop HeatWave, how HeatWave is providing meaningful cost savings to users, and how HeatWave has been optimized for the cloud. Nipun explains how they've lowered the barriers to entry for new users of HeatWave, and Oracle's focus on implementing customer feedback when developing new offerings.Show Highlights(0:00) Intro(0:55) The Duckbill Group sponsor read(1:28) The significance of HeatWave coming to AWS(2:20) What is MySQL HeatWave?(5:13) What jumped out to Corey during his conversations with Nipun on Oracle(8:40) What's “under the hood” of MySQL HeatWave(14:12) How Oracle built out its pricing for MySQL HeatWave(16:41) Why MySQL HeatWave doesn't show up on AWS bills(21:27) The Duckbill Group sponsor read(22:09) Oracle's historical customer base and the company's credit system(24:30) The point behind MySQL HeatWave(27:51) How MySQL HeatWave runs(33:53) Where you can find more from Nipun and OracleAbout Nipun AgarwalNipun Agarwal is a Senior Vice President, MySQL HeatWave and Advanced Development, Oracle. His interests include distributed data processing, machine learning, cloud technologies and security. Nipun was part of the Oracle Database team where he introduced a number of new features. He has been awarded over 170 patents., Nipun Agarwal is Senior Vice President of MySQL Database & HeatWave Development. He leads a global engineering organization responsible for Oracle's MySQL innovations that enable organizations to use a single database for both transactional and analytical workloads. His interests include data processing, distributed systems, machine learning, cloud computing and security. Prior to his current position, Nipun was with Oracle Labs and the Oracle Database team, where he introduced a number of new features. He has been awarded over 175 patents.LinksOracle: https://oracle.comMySQL HeatWave info: https://www.oracle.com/mysql/ MySQL Service on AWS and OCI login (Oracle account required): https://cloud.mysql.comOriginal Episodehttps://www.lastweekinaws.com/podcast/screaming-in-the-cloud/heatwave-and-the-latest-evolution-of-mysql-with-nipun-agarwal/SponsorThe Duckbill Group: duckbillgroup.com

The Oracle-AWS partnership is revolutionizing the way businesses migrate and modernize their Oracle Database workloads.

Join Dan Vega and DaShaun Carter for the latest updates from the Spring Ecosystem. In this episode, Dan and DaShaun are joined by Mark Nelson and Anders Swanson from Oracle to discuss Spring Cloud Oracle. At the end of this episode, you will understand how Spring Cloud Oracle simplifies integration with Oracle Database and OCI services, including UCP, vector databases, and more. You can participate in our live stream to ask questions or catch the replay on your preferred podcast platform.Show Notes:Introduction to Spring Cloud Oracle and its purposeOverview of Oracle Cloud Infrastructure (OCI) free tierDiscussion on Universal Connection Pool (UCP) vs HikariCPOracle's vector database support and Spring AI integrationOracle's in-database message broker and Spring Cloud Stream binderVirtual threads support in Java 21Server-side connection pooling for microservicesJSON collections and relational duality views in Oracle DatabaseObservability features in OCIUpcoming OpenTelemetry support for distributed tracingSpring CLI and project templates for Oracle CloudTest container support for Oracle DatabaseUpcoming open-rewrite recipes for HikariCP to UCP migrationResources:Oracle Cloud free tier: https://www.oracle.com/cloud/free/ Spring Cloud Oracle GitHub: https://github.com/oracle/spring-cloud-oracleKey Takeaways:Spring Cloud Oracle simplifies integration between Spring applications and Oracle Database/OCI servicesOracle offers a generous free tier for developers to explore and test OCI servicesUpcoming features include improved observability, distributed tracing, and migration tools

On this episode of the Six Five Podcast Enterprising Insights, host Keith Kirkpatrick is joined by Robert Kramer, VP and principal analyst at Moor Insights & Strategy, and Guy Currier, CTO at Visible Impact, to discuss the announcements and experiences from Oracle CloudWorld and NetSuite SuiteWorld. He then closes the show by asking them to rant or rave about one item in the enterprise market.

August ends on the high side - (like July) and then gets knocked down hard (like August) and then Rips higher on Monday (like August) Rate cut bets are in place Market very skittish - September not the best month on average VIX hits 25 last week PLUS we are now on Spotify and Amazon Music/Podcasts! Click HERE for Show Notes and Links DHUnplugged is now streaming live - with listener chat. Click on link on the right sidebar. Love the Show? Then how about a Donation? Follow John C. Dvorak on Twitter Follow Andrew Horowitz on Twitter DONATIONS ? Warm Up - Another Rough Start to the month - Apple Event - market was - Last episode - ETF and Funds Education - lots of great comments on that! - DEBATE TIME - right in the middle of our show! Someone needs to look at our schedule Market Update - August ends on the high side - (like July) and then gets knocked down hard (like August) and then Rips higher on Monday (like August) - Rate cut bets are in place - Market very skittish - September not the best month on average - VIX hits 25 last week - Yen Carry trade issue not fully resolved - YIELD CURVE UPDATE Big News - Yield curve normalizes for 2/10's - Yield curve is not normal - this is what happened  in 2001 and 2008 Apple Event - Apple introduces Apple Watch Series X with a new design. - Largest most advanced display ever with 30% more screen area. - The display is larger than the Apple Watch Ultra. - Display will be 40% brighter. - Watch will be 10% thinner than Apple Watch 9. - Background noise will be surprised on phone calls. - Smart Stack will add widgets whenever you need them. - Adding translate application. -Apple Watch can track menstrual cycles. - Apple Watch can alert users to sleep apnea. - Starts at $399. - A few incremental updates otherwise and talk of AI to come - one day someday More Apple - Europe's top court on Tuesday ruled against Apple in the tech giant's 10-year court battle over its tax affairs in Ireland. - The Commission in 2016 ordered Dublin to recover up to 13 billion euros ($14.4 billion) in back taxes from Apple, at the time saying that the tech company had received "illegal" tax benefits from Ireland over the course of two decades. - So is this final this time? - How is this possible anyway - Ireland granted tax benefits for the purpose of benefiting jobs etc.... Apple Competition - Huawei's tri-fold phone receives over 4 mln pre-orders ($2,800 per) - Have you seen this? - VERY COOL device Palantir -  Palantir Technologies hits best levels since early 2021 following inclusion in S&P 500 - +15% on the  news Dell - Dell also is added to the S&P 500 - Etsy and American Airlines out Tech - Oracle Earnings - Oracle beats on some metrics and has some great outlook - Missed on EPS - Partnering with Amazon - The company said Oracle Database is thriving, and the multi-cloud agreements it has with Microsoft, Google, and now AWS make it easier for its customers to run their Oracle Databases in the cloud. - Stock at ATH NVDA - WORST DAY EVER for a stock - Slide last week took at $300 BILLION on market value in one day. - New DOJ probe in anti-trust case - The agency is asking questions about whether Nvidia makes it harder to switch to other suppliers of AI chips. - Nvidia has over 80% of the market for data center AI chips, according to industry estimates. Best Buy - People are buying... - Raising full year guidance - Comparable sales declined 2.3% during the quarter, compared with a 6.2% decline a year earlier. --- It is all about  the expectations... Glasses - Again? - Qualcomm CEO Cristiano Amon told CNBC the chip designer is working with Samsung and Google to explore a mixed-reality set of glasses linked to a smartphone - Last year, Google, Samsung and Qualcomm struck a partnership to develop mixed-reality technology. - This is supposed to be a smaller version of what is out the...

An airhacks.fm conversation with Gerald Venzl (@GeraldVenzl) about: from a 386 computer with SimCity to Oracle's database evangelist, early interest in computer hardware and software, apprenticeship as a programmer in Austria, work experience with Oracle database and PLSQL, Steven Feuerstein, PLSQL expert, career moves to New York, London, and San Francisco, role as product manager and team leader at Oracle, efforts to attract developers to Oracle technologies, involvement in Oracle ACE Program, work on docker files for Oracle Database, challenges with ARM port for Mac, popular JavaOne talk on optimizing Java code for database performance, discussion of Oracle's various database technologies including NoSQL and TimesTen, importance of educating developers on database best practices, evolution of database performance techniques, future topics for discussion including Oracle architecture, Java integration, and business logic in databases, Gerald's team of evangelists across Europe, ways to contact Gerald and his team for speaking engagements or information Gerald Venzl on twitter: @GeraldVenzl

Recorded Date: 31 May 2024 Title: Blow your Brains Out Overview Josh, Kito, and Danno are joined by fellow Java Champion , the maintainer of JReleaser and a Senior Principal Product Manager at Oracle. They discuss new updates to JReleaser, reproducible builds, the EU's Cyber Resilience Act (CRA), a new free version of Oracle Database, JetBrains Aqua, the discontinuation of Grails funding, OpenRewrite, JakartaEE 11, and more. Social links (for reference when posting to social media) @kito99 @kito99@mastadon.social @Java_Champions @JavaChampions@mastodon.social @javajuneau @javajuneau@fosstodon.org https://www.linkedin.com/in/dhevolutionnext/ @dhinojosa @dhinojosa@mastodon.social https://bsky.app/profile/dhinojosa.bsky.social @ianhlavats About Andres Almiray Socials:Twitter Mastodon Bluesky Title: Senior Principal Product Manager, Oracle Bio: Andres is a Java/Groovy developer and a Java Champion with more than 20 years of experience in software design and development. He has been involved in web and desktop application development since the early days of Java. Andres is a true believer in open source and has participated on popular projects like Groovy, Griffon, and DbUnit, as well as starting his own projects (Json-lib, EZMorph, GraphicsBuilder, JideBuilder). Founding member of the Griffon framework and Hackergarten community event. Server Side Java Object Computing Discontinues Grails Support Jakarta EE 11 Forthcoming Tools JReleaser Tell us about CycloneDX, SPDX, SBoms, and JReleaser, publication to Sonatype Portal, SLSA, Swid Tags NixOS OpenRewrite JetBrains Aqua Commonhaus Foundation Devoxx Genie Data Oracle Database 23ai Free | Oracle Oracle Autonomous Database (Cloud) Oracle Database Docker Images Oracle Database Docker images from Oracle Container Registry Java Platform GitHub - moditect/layrry: A Runner and API for Layered Java Applications Security The Open Source Community is Building Cybersecurity Processes for CRA Compliance | Life at Eclipse Picks SnoreLab (Kito) Ollama (Kito) OCI Generative AI Certification - Free (for now) (Josh) AI Assistant (JetBrains) (Danno) Conventional Commits (Andres) Wagakki Band - 焔 (Homura) + 暁ノ糸 (Akatsuki no Ito) / 1st JAPAN Tour 2015 Hibiya Yagai Ongakudo (Andres) GitHub - diffplug/spotless: Keep your code spotless (Danno) youtu.be/z8L202FlmD4?si=6pdHKx (Danno) The Rise of Oracle, SQL and the Relational Database (Danno) Other Pubhouse Network podcasts OffHeap Java Pubhouse Events ÜberConf July 16 - 19, 2024 Westminster, CO jconf.dev - September 24-26 Dallas, Texas Code.talks - Sep 19-20, Hamburg, Germany Devoxx Morocco - Oct 2-4, Marrakech, Morocco Devoxx Belgium - Oct 7-11, Antwerp, Belgium Codemotion Milan - Oct 22-23, Milan, Italy Twin Cities Software Symposium August 9-10, 2024 Northern Virginia Software Symposium September 5-6, 2024 Central Iowa Software Symposium September 12-13, 2024 DevOps Vision December 2-4, 2024 Tech Leader Summit December 4-6, 2024 Arch Conf December 9-12, 2024 Dev2next - Sept 30 - Oct 3, Lone Tree, Colorado, USA, 2024 https://jakartaone.org/ JakartaOne Livestream Dec 3, 2024