Podcasts about aws lambda

AWS Morning Brief for the week of February 17th, with Corey Quinn. Links:Amazon Aurora DSQL is now available in additional AWS RegionsAmazon Bedrock adds support for six fully-managed open weights modelsAWS Config now supports 30 new resource typesAnnouncing new Amazon EC2 general purpose M8azn instancesAWS Network Firewall announces new price reductionsAmazon S3 Tables add partition and sort order definition in the CreateTable APIAmazon Athena adds 1-minute reservations and new capacity control featuresBuilding fault-tolerant applications with AWS Lambda durable functions Simplify cross-account stream processing with AWS Lambda and Amazon DynamoDBAutomated Reasoning checks rewriting chatbot reference implementationMastering Amazon Bedrock throttling and service availability: A comprehensive guideReservoir computing on an analog Rydberg-atom quantum computer

AWS Lambda is fantastic for small, stateless code on demand. But when your “function” starts looking like a workflow (retries, backoff, long waits, human approvals, callbacks), classic Lambda patterns can feel like a fight: 15-minute max runtime, no built-in state, and orchestration glue everywhere (Step Functions, queues, schedules, and state you did not want to own). In this episode of AWS Bites, Eoin and Luciano explore AWS Lambda Durable Functions, announced at re:Invent 2025. It's still Lambda (same runtimes and scaling), but with durable execution superpowers: named steps, automatic checkpointing, and the ability to suspend and resume from a safe point without redoing completed work. We unpack the replay/resume model under the hood, when this approach shines, and the gotchas (determinism, idempotency, replay-aware logging, debugging resumed runs). To make it real, we share how we rebuilt PodWhisperer v2 using Durable Functions to orchestrate a GPU-powered WhisperX pipeline, LLM refinement, speaker naming, and caption generation.In this episode, we mentioned the following resources: AWS announcement blog post: https://aws.amazon.com/blogs/aws/build-multi-step-applications-and-ai-workflows-with-aws-lambda-durable-functions/ Durable Functions best practices: https://docs.aws.amazon.com/lambda/latest/dg/durable-best-practices.html The replay model deep dive (Dev.to): https://dev.to/aws/the-replay-model-how-aws-lambda-durable-functions-actually-work-2a79 Build workflows that last (Dev.to): https://dev.to/aws/aws-lambda-durable-functions-build-workflows-that-last-3ac7 Testing Durable Functions in TypeScript (Dev.to): https://dev.to/aws/testing-aws-lambda-durable-functions-in-typescript-5bj2 Developing Durable Functions with AWS SAM (Dev.to): https://dev.to/aws/developing-aws-lambda-durable-functions-with-aws-sam-ga9 Hands-on notes: https://www.andmore.dev/blog/lambda_durable_functions/ PodWhisperer (open source): https://github.com/fourTheorem/podwhisperer/ WhisperX: https://github.com/m-bain/whisperX Do you have any AWS questions you would like us to address?Leave a comment here or connect with us on X/Twitter, BlueSky or LinkedIn:- https://twitter.com/eoins | https://bsky.app/profile/eoin.sh | https://www.linkedin.com/in/eoins/- https://twitter.com/loige | https://bsky.app/profile/loige.co | https://www.linkedin.com/in/lucianomammino/

Produktmanagement wird dauernd erwähnt, aber selten wirklich erklärt. Und genau da entsteht oft der Frust: Feature Requests prasseln rein, das Jira Backlog wächst wie Unkraut, Stakeholder eskalieren, und am Ende fragt sich jede:r im Team, wer hier eigentlich was entscheidet. Klingt bekannt? Dann ist diese Episode für dich.In dieser Episode schließen wir eine längst überfällige Lücke und steigen tief in das Thema Produktmanagement ein. Zu Gast ist Michael Gasch, Product Manager bei AWS im Serverless Umfeld. Mit ihm schauen wir uns an, was Produktmanagement wirklich ist, warum es nicht einfach Projektmanagement mit neuem Label ist und wie AWS Rollen wie PMT, SDM und TPM trennt, um Delivery, Priorisierung und Ownership sauber zu verzahnen.Wir sprechen über Working Backwards und PR/FAQ Dokumente, datengetriebene Priorisierung unter Dauerbeschuss, Paper Cuts vs. große Launches, Disagree and Commit, Bias for Action und wie Erfolg nach einem GA Launch über Metriken, Telemetrie und Kundenfeedback messbar wird. Als Praxisbeispiel nehmen wir ein echtes AWS Feature: Durable Functions in AWS Lambda, von der Idee im Kopf bis zur AWS re:Invent Bühne.Zum Schluss gibt es noch ein paar Tips:Wie kannst du proaktiver in Produktentscheidungen werden, bessere Inputs liefern und vielleicht sogar selbst Richtung Produktmanagement wechseln?Spoiler: Anforderungsanalyse, Ownership und ein bisschen STAR Methode können viel bewegen.Bonus: Wenn du dachtest, AI macht Produktmanager:innen überflüssig, warten hier ein paar ziemlich gute Gegenargumente auf dich.Unsere aktuellen Werbepartner findest du auf https://engineeringkiosk.dev/partnersDas schnelle Feedback zur Episode:

Chris McHenry, Chief Product Officer at Aviatrix, joined Doug Green, Publisher of Technology Reseller News, to discuss the launch of Aviatrix 8.2 and how the company is redefining zero trust security for modern cloud-native environments. McHenry explained that as critical business data and AI workloads increasingly reside in public clouds such as AWS, Azure, and Google Cloud, traditional perimeter-based security models are no longer sufficient. Aviatrix has spent the last decade building its Cloud Native Security Fabric, a platform designed specifically for cloud operational models rather than retrofitted on-premises approaches. With release 8.2, Aviatrix significantly expands its “zero trust for workloads” capabilities, focusing on Kubernetes, serverless environments, and AI-driven applications. A central theme of the conversation was the evolution of zero trust from a networking concept into a workload-centric security strategy. McHenry noted that recent supply-chain attacks have shown how quickly cloud-native environments can be compromised if basic network controls are missing. Aviatrix 8.2 introduces deeper Kubernetes awareness, policy-as-code integration, and initial native support for securing AWS Lambda, allowing organizations to apply micro-segmentation and least-privilege access directly to modern workloads. McHenry emphasized that cloud security must also evolve operationally. Security teams can no longer rely on slow, ticket-based firewall processes while developers deploy infrastructure at machine speed. Aviatrix 8.2 supports a DevSecOps-friendly model that enables developers to manage zero trust policies within guardrails defined by security teams. As McHenry put it, “If your workloads get more modern but your controls don't, security gets worse without you touching anything.” The discussion concluded with guidance for CIOs and CISOs preparing for the next wave of cloud and AI-driven threats: assess whether existing network security tools truly understand cloud-native workloads, modernize security operations alongside development practices, and prioritize platforms that unify cloud, network, and security teams. More information on Aviatrix 8.2 and the Cloud Native Security Fabric is available at https://aviatrix.ai/.

RexIDE - https://rex.mindmeld360.com⁠

When AWS has a major outage, what actually happens behind the scenes? Ben Hartshorne, a principal engineer at Honeycomb, joins Corey Quinn to discuss a recent AWS outage and how they kept customer data safe even when their systems couldn't fully work. Ben explains why building services that expect things to break is the only way to survive these outages. Ben also shares how Honeycomb used its own tools to cut their AWS Lambda costs in half by tracking five different things in a spreadsheet and making small changes to all of them.About Ben Hartshorne: Ben has spent much of his career setting up monitoring systems for startups and now is thrilled to help the industry see a better way. He is always eager to find the right graph to understand a service and will look for every excuse to include a whiteboard in the discussion.Show highlights: (02:41)Two Stories About Cost Optimization(04:20) Cutting Lambda Costs by 50%(08:01) Surviving the AWS Outage(09:20) Preserving Customer Data During the Outage(13:08) Should You Leave AWS After an Outage?(15:09) Multi-Region Costs 10x More(18:10) Vendor Dependencies(22:06) How LaunchDarkly's SDK Handles Outages(24:40) Rate Limiting Yourself(29:00) How Much Instrumentation Is Too Much?(34:28) Where to Find BenLinks: Linkedin: https://www.linkedin.com/in/benhartshorne/GitHub: https://github.com/maplebedSponsored by: duckbillhq.com

AWS Morning Brief for the week of December 8th, with Corey Quinn. Links:Introducing Amazon Route 53 Global Resolver for secure anycast DNS resolution (preview)Introducing AWS Lambda Managed Instances: Serverless simplicity with EC2 flexibilityAWS announces preview of AWS Interconnect - multicloudIntroducing AWS Transform custom: Crush tech debt with AI-powered code modernizationAmazon CloudWatch introduces unified data management and analytics for operations, security, and complianceAmazon EC2 P6e-GB300 UltraServers accelerated by NVIDIA GB300 NVL72 are now generally availableIntroducing AWS AI FactoriesIntroducing AWS DevOps Agent (preview), frontier agent for operational excellenceAmazon S3 Storage Lens adds performance metrics, support for billions of prefixes, and export to S3 TablesBuild multi-step applications and AI workflows with AWS Lambda durable functionsAmazon S3 increases the maximum object size to 50 TBAmazon S3 Tables now offer the Intelligent-Tiering storage classChina-nexus cyber threat groups rapidly exploit React2Shell vulnerability (CVE-2025-55182)Introducing Database Savings Plans for AWS Databases

In dieser Episode von AWS Cloud Horizonte spricht Oliver Steenbuck mit Malte Polley (Teamleader Data Analytics & AI) und Ahmet Akduman (Head of Business Organization) von MRH Trowe, einem der größten inhabergeführten Versicherungsmakler in Deutschland, über den Aufbau einer modernen Daten- und KI-Plattform auf AWS. Im Mittelpunkt steht die Frage, wie man eine stetig wachsende Flut an Dokumenten beherrschbar macht – und generative KI nicht als Buzzword, sondern als produktives Werkzeug einsetzt. Kernthemen der Episode: Klassifizierung und Routing eingehender Dokumente (Post, E-Mail, Scans) in einem schnell wachsenden Maklerunternehmen Aufbau einer skalierbaren Dokumenten- und Datenpipeline mit AWS-Services wie Amazon S3, AWS Lambda, AWS Step Functions, Amazon Textract und Amazon Bedrock Einsatz von generativer KI zur Dokumentenklassifizierung und -anreicherung: vom unstrukturierten PDF zum verwertbaren Datensatz Technische Stellschrauben: Kontextfenster, Tokenanzahl, Latenz, Kosten – und warum Vorverarbeitung oft wichtiger ist als „das größte Modell" Organisatorische Herausforderungen des Buy-and-Build-Ansatzes: Integration neuer Maklerhäuser, Harmonisierung von Prozessen und Systemen Lessons Learned auf dem Weg von der Idee zu belastbaren, produktiven Workflows Highlights: Ein konkreter End-to-End-Use-Case: vom Papierbrief mit QR-Code über den AWS Simple Email Service, S3, Textract und Bedrock bis ins Bestandssystem Wie MRH Trowe mit einem schlanken Team produktive KI-Workflows baut – ohne großes Data-Science-Lab Praktische Erfahrungen mit Prompting, Modellwahl (z. B. Anthropic-Modelle auf Bedrock) und Qualitätskontrolle Welche Dokumenten-Use-Cases heute schon gut funktionieren – und wo die Grenzen aktuell noch liegen Wie sich die Arbeit der Sachbearbeitung verändert, wenn KI Routineaufgaben übernimmt Über die Gäste: Malte Polley – Teamleader Data Analytics & AI bei MRH Trowe und verantwortlich für den Aufbau der Cloud-Infrastruktur und Plattform-Services Ahmet Akduman – Head of Business Organization bei MRH Trowe und Brückenbauer zwischen Fachbereichen, Prozessen und datengetriebenen Lösungen Host: Oliver Steenbuck (AWS)  

# 2025-11-18 - News - Episode 245# Hosts: - Daniel Garcia - Senior Developer at Ortus Solutions- Jacob Beers - Senior Developer at Ortus Solutions# summaryIn this episode of the Modernize or Die Podcast, hosts Daniel Garcia and Jacob Beers discuss the latest updates from Ortus Solutions, including the release of ColdBox 8 and BoxLang 1.7. They delve into new features such as server-sent events, serverless capabilities with AWS Lambda, and the introduction of SocketBox for WebSocket integration. The conversation also covers upcoming events, training opportunities, and important updates regarding CFML, including the end of life for ColdFusion 2021. The hosts emphasize the growing impact of BoxLang within the Java community and its new PDF handling capabilities.# TakeawaysColdBox 8 introduces groundbreaking capabilities for web development.The upgrade path from ColdBox 7 to 8 is smooth and efficient.Server-sent events allow real-time data streaming from server to client.BoxLang is making strides in serverless architecture with AWS Lambda.SocketBox simplifies WebSocket integration in ColdFusion applications.BXCompatUI facilitates easy migration from CFML to BoxLang.BoxLang is gaining recognition in the broader Java community.The new PDF handling features in BoxLang enhance document manipulation.ColdFusion 2021 has reached its end of life, with no further updates.Into the Box 2026 is a must-attend conference for developers.# Chapters00:00 Welcome00:18 Ortus News & BoxLang Updates14:24 CFML Updates17:30 Upcoming Events and Conferences20:31 Thank You# Join the Ortus CommunityBe part of the movement shaping the future of web development. Stay connected and receive the latest updates on, **product launches, tool updates, promo services and much more.**Follow Us on Social media and don't miss any news and updates:-  https://twitter.com/ortussolutions-  https://www.facebook.com/OrtusSolutions-  https://www.linkedin.com/company/ortus-solutions-corp-  https://www.youtube.com/OrtusSolutions- https://github.com/Ortus-Solutions# KeywordsColdBox, BoxLang, Ortus Solutions, serverless, WebSockets, CFML, Java, PDF handling, cloud deployment, software development ★ Support this podcast on Patreon ★

An airhacks.fm conversation with Philipp Page (@PagePhilipp) about: Discussion about refactoring AWS Lambda Power Tools to remove AspectJ dependency and introduce functional interfaces, comparison between AspectJ and lombok for code generation, benefits of offloading work to build time for AWS Lambda performance, using quarkus build-time optimizations with Jandex and gizmo utilities, replacing slf4j with Java System Logger to reduce dependencies, implementing log buffering feature that flushes debug logs only on errors for proactive debugging, thread safety considerations in multi-threaded AWS Lambda executions, using Embedded Metrics Format (EMF) for CloudWatch metrics without prometheus, caching Parameter Store values to avoid throttling limits, structured logging benefits for nested JSON queries in CloudWatch Insights, detecting cold starts without reflection using class initialization tricks, future support for Java 25 and modern Java features like Scoped Values, Maven and Gradle plugin development for annotation processing, custom serializers for Kafka and Avro messages, potential java.util.json support for lightweight JSON parsing, middleware chain pattern implementation for Power Tools utilities, differences between reactive and proactive debugging approaches, cost optimization through EMF metrics instead of Prometheus scraping, BCE (Boundary Control Entity) architecture pattern for business metrics, performance benefits of removing reflection from metrics utility, CDK integration considerations for generated classes, request stream handlers as reflection-free alternatives Philipp Page on twitter: @PagePhilipp

Send us a textIn this episode of What's New in Cloud FinOps, Stephen Old and Frank discuss the latest updates in cloud computing, including AWS Outposts' integration with third-party storage, new Amazon EC2 Mac instances, Azure's managed services, and Google Cloud VM Engine updates. They also explore pricing changes in Azure, the deprecation of Azure Machine Learning data labeling, and the introduction of new metrics in software development. The conversation highlights the importance of sustainability in cloud services and concludes with reflections on the podcast's five-year anniversary.TakeawaysAWS Outposts now supports third-party storage integration with Dell and HPE.Amazon EC2 introduces new Mac instances for developers.Azure managed services now include Grafana dashboards at no extra cost.Google Cloud VM Engine V1 SKUs are now end of sale.Azure UltraDisk pricing has been reduced significantly in specific regions.Azure Machine Learning data labeling will be deprecated by 2026.AWS Transform Assessment helps visualize storage migration benefits.New cost to serve software metric introduced by AWS.Cortex Framework now deploys sustainability modules for SAP.AWS Lambda cold start billing changes will take effect in 2025.

An airhacks.fm conversation with Philipp Page (@PagePhilipp) about: early computing experiences with Windows XP and Intel Pentium systems, playing rally car games like Dirt with split-screen multiplayer, transitioning from gaming to server administration through Minecraft, running Minecraft servers at age 13 with memory limitations and out-of-memory exceptions, implementing caching mechanisms with cron jobs and MySQL databases, learning about SQL injection attacks and prepared statements, discovering connection pooling advantages over PHP approaches, appreciating type safety and Object-oriented programming principles in Java, the tendency to over-abstract and create unnecessary abstractions as junior developers, obsession with avoiding dependencies and implementing frameworks from scratch, building custom Model-View-Controller patterns and dependency injection systems, developing e-learning platform for aerospace industry using PHP Symfony framework, implementing time series forecasting in pure Java without external dependencies, internship and employment at AWS Dublin in Frontier Networking team, working on AWS Outposts and Ground Station hybrid cloud offerings, using python and rust for networking control plane development, learning to appreciate Python despite initial resistance to dynamically typed languages, joining AWS Lambda Powertools team as Java tech lead, maintaining open-source serverless development toolkit, providing utilities for observability including structured JSON logging with Lambda-specific information, implementing metrics and tracing for distributed event-driven architectures, mapping utilities to AWS Well-Architected Framework serverless lens recommendations, caching parameters and secrets to improve scalability and reduce costs, debate about AspectJ dependency and alternatives like Micronaut and quarkus approaches, providing both annotation-based and programmatic interfaces for utilities, newer utilities like Kafka consumer avoiding AspectJ dependency, comparing Micronaut's compiler-based approach and Quarkus extensions for bytecode generation, AspectJ losing popularity in enterprise Java projects, preferring Java standards over external dependencies for long-term maintainability, agents in electricity trading simulations for renewable energy scenarios, comparing on-premise Java capabilities versus cloud-native AWS features, default architecture pattern of Lambda with S3 for persistent storage, using AWS Calculator for cost analysis before architecture decisions, event-driven architectures being native to AWS versus artificially created in traditional Java projects, everything in AWS emitting events naturally through services like EventBridge, filtering events rather than creating them artificially, avoiding unnecessary microservices complexity when simple method calls suffice, directly wiring API Gateway to DynamoDB without Lambda for no-code solutions, using Java for CDK infrastructure as code while minimizing runtime dependencies, maximizing cloud-native features when in cloud versus on-premise optimization strategies, starting with simplest possible architecture and justifying complexity, blue-green deployments and load balancing handled automatically by Lambda, internal AWS teams using Lambda for orchestration and event interception, Lambda as foundational zero-level service across AWS infrastructure, preferring highest abstraction level services like Lambda and ECS Fargate, only dropping to EC2 when specific requirements demand lower-level control, contributing to Powertools for AWS Lambda Python repository before joining team, compile-time weaving avoiding Lambda cold start performance impacts, GraalVM compilation considerations for Quarkus and Micronaut approaches, customer references available on Powertools website, contrast between low-level networking and serverless development, LinkedIn as primary social media platform for professional connections, Powertools for AWS Lambda (Java) Philipp Page on twitter: @PagePhilipp

AWS Morning Brief for the week of October 6th, 2025, with Corey Quinn. Links:Deploying AI models for inference with AWS Lambda using zip packagingAnnouncing Amazon ECS Managed Instances Amazon EBS increases the maximum size and provisioned performance of General Purpose (gp3) volumes Accelerating AWS Infrastructure Deployment: A Practical Guide to Console-to-Code AWS Builder ID now supports Sign in with Google Build a dynamic workflow orchestration engine with Amazon DynamoDB and AWS LambdaAWS Transfer Family adds support for additional IAM condition keys AWS Compute Optimizer now supports 99 new Amazon EC2 instance types

An airhacks.fm conversation with Alvaro Hernandez (@ahachete) about: Framework laptop experience and build process with DIY edition, modular connectors and upgradability, running Ubuntu 25.10 beta with nix package manager, automating installation with YAML and Ansible, comparison with IBM AS/400 feature activation model, docker adoption history for server maintenance and documentation, PostgreSQL extensions, upgradability and security concerns, challenges with packing 1000+ extensions into container images, security concerns with large monolithic images containing unused extensions, dynamic extension injection using sidecar pod local controller in kubernetes, problems with mutating running containers and security tool compliance, traditional Docker build approach requiring users to become image maintainers, challenging assumptions about container image immutability and Merkle tree, container images as JSON manifests pointing to tar file layers, Dynamic OCI Registry concept for composing images on-the-fly, generating manifests dynamically in milliseconds without Docker build, interface-based approach for mapping user preferences to layer digests, PostgreSQL-specific implementation with extension URL patterns, metadata storage in PostgreSQL database for layer digest resolution, potential applications for quarkus and Java microservices, serverless deployment possibilities with AWS Lambda, comparison with Cloudflare's serverless OCI registry, enterprise use cases for automated patching and security updates, integration possibilities with AWS EventBridge for CI/CD pipelines, transparency to Docker clients with only registry change required, stackgres platform using 4 million lines of Java code, ongres company services including PostgreSQL training and Oracle migrations, Alvaro's website: aht.es Alvaro Hernandez on twitter: @ahachete

An airhacks.fm conversation with Ronald Dehuysser (@rdehuyss) about: JobRunner evolution from open source to processing 1 billion jobs daily, carbon-aware job processing using European energy grid data ( ENTSO-E ) for scheduling jobs during renewable energy peaks, correlation between CO2 emissions and energy prices for cost optimization, JobRunner Pro vs Open Source features including workflows and multi-tenancy support, bytecode analysis using ASM for lambda serialization, JSON serialization for job state persistence, support for relational databases and MongoDB with potential S3 and DynamoDB integration, distributed processing with master node coordination using heartbeat mechanism, scale-to-zero architecture possibilities using AWS EventBridge Scheduler, Java performance advantages showing 35x faster than python in benchmarks, cloud migration patterns from on-premise to serverless architectures, criticism of kubernetes complexity and lift-and-shift cloud migrations, cost-driven architecture approach using AWS Lambda and S3, quarkus as fastest Java runtime for cloud deployments, infrastructure as code using AWS CDK with Java, potential WebAssembly compilation for Edge Computing, automatic retry mechanisms with exponential backoff, dashboard and monitoring capabilities, medical industry use case with critical cancer result processing, professional liability insurance for software errors, comparison with executor service for non-critical tasks, scheduled and recurring job support, carbon footprint reduction through intelligent scheduling, spot instance integration for cost optimization, simplified developer experience with single JAR deployment, automatic table creation and data source detection in Quarkus, backwards compatibility requirements for distributed nodes, future serverless edition possibilities Ronald Dehuysser on twitter: @rdehuyss

An airhacks.fm conversation with Ingo Kegel (@IngoKegel) about: jprofiler Visual Studio Code integration using Kotlin Multiplatform, migrating Java code to Kotlin common code for cross-platform compatibility, transpiling to JavaScript for Node.js runtime, JClassLib bytecode viewer and manipulation library, Visual Studio Code's Language Server Protocol (LSP), profiling unit tests and performance regression testing, Java Flight Recorder (JFR) for production monitoring with custom business events, cost-driven development in cloud environments, serverless architecture with AWS Lambda and S3, performance optimization with parallelism in single-CPU environments, integrating profiling data with LLMs for automated optimization, MCP servers for AI agent integration, Gradle and Maven build system integration, cooperative window switching between JProfiler and VS Code, memory profiling and thread analysis, comparing streams vs for-loops performance, brokk AI's Swing-based LLM development tool, context-aware performance analysis, automated code optimization with AI agents, business event correlation with low-level JVM metrics, cost estimation based on cloud API calls, quarkus for fast startup times in serverless, performance assertions in System Tests, multi-monitor development workflow support Ingo Kegel on twitter: @IngoKegel

AWS Morning Brief for the week of September 2nd, 2025, with Corey Quinn. Links:How Ancestry optimizes a 100-billion-row Iceberg tableMastering Amazon Q Developer with Rules Bob's Used Books: Build a .NET Serverless Application on AWS – Part 2: ArchitectureHow Amazon Finance built an AI assistant using Amazon Bedrock and Amazon Kendra to support analysts for data discovery and business insights Building Your Open Source Commercial Strategy with AWSHow to optimize Amazon RDS and Amazon Aurora database costs/performance with AWS Compute OptimizerGracefully handle failed AWS Lambda events from Amazon DynamoDB StreamsAnnouncing the AWS Billing and Cost Management MCP serverAWS joins the DocumentDB project to build interoperable, open source document database technologyCount Tokens API supported for Anthropic's Claude models now in Amazon Bedrock

In this episode of the AWS Podcast, we explore the evolving world of contact centers and Amazon Connect. The discussion covers why contact centers remain critical to both business and public sector operations, and how they're transforming from traditional cost centers into valuable sources of business intelligence. Key highlights include Amazon Connect's integration capabilities with AWS services, particularly through AWS Lambda functions, and the recent implementation of generative AI features including contact summarisation, agent evaluations, and Amazon Q in Connect. The conversation emphasizes how modern technology is helping organizations better understand customer needs, improve agent performance, and maintain human empathy in customer service while leveraging automation. The episode also touches on practical aspects of system integration and data management, demonstrating how Amazon Connect helps organizations overcome traditional barriers in contact center operations. https://aws.amazon.com/connect/ https://aws.amazon.com/blogs/contact-center/introducing-the-next-generation-of-amazon-connect/

An airhacks.fm conversation with Adam Dudczak (@maneo) about: early programming experiences with Commodore 64 and Pascal, demo scene participation through postal mail swapping of floppy disks, writing assembly code for 64K intros with music and graphics, developing digital library systems using Java Servlets and Hibernate, involvement in reactivating Poznan Java User Group in 2007, NetBeans Dream Team and NetBeans World Tour, appearing on Polish breakfast TV to discuss Java programming, working at Supercomputing Center on cultural heritage digitization projects, transitioning to EJB 3.0 and Glassfish based on conference inspirations, joining allegro in 2014 to rewrite search functionality from PHP to Java microservices, handling 14K requests per second with Solr-based search infrastructure, migrating big data stack from on-premise Hadoop to Google Cloud Platform, developing private banking application for children using Spring and Hibernate then migrating to Google Sheets with 70 lines of JavaScript, discussing public cloud cost optimization strategies, comparing AWS Lambda versus EC2 versus container services based on traffic patterns, emphasizing removal of code when moving to public cloud to leverage managed services, standardization benefits of Java EE for long-term maintenance and migration, quarkus as modern framework supporting old Jakarta EE code with fast startup times, importance of choosing appropriate persistence layer (S3 vs relational databases) based on cloud costs, serverless architectures for enterprise applications with predictable low traffic, differences between AWS Azure and GCP service offerings and pricing models, Turbo assembler project klatwa Adam Dudczak on twitter: @maneo

Episode Summary: AWS Morning Brief for the week of August 4th, 2025, with Corey Quinn. Amazon Aurora MySQL database clusters now support up to 256 TiB of storage volume Introducing v2 of Powertools for AWS Lambda (Java)Introducing Extended Support for Amazon ElastiCache version 4 and version 5 for Redis OSSAmazon DocumentDB Serverless is now available AWS Lambda response streaming now supports 200 MB response payloadsHow Zapier runs isolated tasks on AWS Lambda and upgrades functions at scaleAmazon Application Recovery Controller now supports Region switchAnnouncing general availability of Amazon EC2 G6f instances with fractional GPUsAmazon Promotes Malphas to Senior Vice President of Bad Decisions, Unveils 17th Leadership PrincipleAmazon CloudFront introduces new origin response timeout controlsOptimize traffic costs of Amazon MSK consumers on Amazon EKS with rack awarenessAmazon Bedrock now available in the US West (N. California) RegionNew AWS whitepaper: AWS User Guide to Financial Services Regulations and Guidelines in Australia Amazon EC2 Auto Scaling adds AWS Lambda functions as notification targets for lifecycle hooks

12 Factor Apps com Serverless na AWSComo os 12 Fatores se adaptam ao mundo serverless?Neste episódio do Sem Servidor, Evandro Pires conversa com Caio Pardal (Intuit) e Gabriel Oswaldo (Revolut) sobre como aplicar os princípios de apps modernos no universo da AWS Lambda, Step Functions, Secrets Manager, entre outros.Você vai entender:Por que o 12 Factor ainda importaComo lidar com granularidade, cold start e deploys contínuosBoas práticas e armadilhas no uso de serviços gerenciados

For memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinSummary:In this conversation, Kaivalya Apte and Rajesh Pandey talk about the engineering behind AWS Lambda, exploring its architecture, use cases, and best practices. They discuss the challenges of event handling, concurrency, and load balancing, as well as the importance of observability and testing in serverless environments. The conversation highlights the innovative solutions AWS Lambda provides for developers, emphasizing the balance between simplicity and complexity in cloud computing.Chapters:00:00 Introduction to AWS Lambda04:36 Use Cases and Best Practices for AWS Lambda09:34 Event Handling and Queue Management19:41 Idempotency and Event Duplication Challenges29:39 Cold Starts and Performance Optimization34:37 Statelessness and Resource Management in Lambda42:18 Understanding Micro-VMs and Cold Starts45:14 Resource Management and Recommendations for Developers47:04 Scaling and Back Pressure in Serverless Systems51:33 Cellular Architecture and Fairness in Resource Allocation55:23 Handling Problematic Events and Poison Pills01:01:03 Testing and Operational Readiness in Lambda01:14:11 Preparing for High Traffic EventsReferences:Handling Billions of invocations: https://aws.amazon.com/blogs/compute/handling-billions-of-invocations-best-practices-from-aws-lambda/Firecracker: https://firecracker-microvm.github.io/AWS Lambda: https://aws.amazon.com/lambda/Connect with Rajesh: https://x.com/RPandeyViewshttps://www.linkedin.com/in/rajeshpandeyiiit/Don't forget to like, share, and subscribe for more insights!=============================================================================Like building stuff? Try out CodeCrafters and build amazing real world systems like Redis, Kafka, Sqlite. Use the link below to signup and get 40% off on paid subscription.https://app.codecrafters.io/join?via=geeknarrator=============================================================================Database internals series: https://youtu.be/yV_Zp0Mi3xsPopular playlists:Realtime streaming systems: https://www.youtube.com/playlist?list=PLL7QpTxsA4se-mAKKoVOs3VcaP71X_LA-Software Engineering: https://www.youtube.com/playlist?list=PLL7QpTxsA4sf6By03bot5BhKoMgxDUU17Distributed systems and databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4sfLDUnjBJXJGFhhz94jDd_dModern databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4scSeZAsCUXijtnfW5ARlrsNStay Curios! Keep Learning!#aws #awslambda #serverless #distributedsystems #scalability #reliability

Cost is always top of mind when building in the cloud, and recently AWS has introduced some changes worth paying attention to. In this episode of AWS Bites, we explore a shift that caught many by surprise: the “free” INIT phase for Lambda's managed runtimes is going away. That cold start time that used to fly under the billing radar? It's now part of the cost. We dig into what this means for your workloads, who might feel the impact, and whether this gives languages like Rust and Go an extra edge. But it's not all bad news. AWS has also rolled out new pricing tiers for CloudWatch Logs, making it cheaper for high-volume accounts. On top of that, there are new options to send logs directly to S3 or Firehose, helping simplify pipelines and reduce costs. We close with a few tips to help you keep your Lambda and logging spend under control. If you're building on AWS and care about efficiency, this is one you won't want to miss.Big shoutout to fourTheorem for powering yet another episode of AWS Bites. At fourTheorem, we believe the cloud should be simple, scalable, and cost-effective, and we help teams do just that. Whether you're diving into containers, stepping into event-driven architecture, or scaling a global SaaS platform on AWS, or trying to keep cloud spend under control our team has your back. Visit https://fourTheorem.com to see how we can help you build faster, better, and with more confidence using AWS cloud!In this episode, we mentioned the following resources:AWS Blog – Tiered Pricing for AWS Lambda: https://aws.amazon.com/blogs/compute/introducing-tiered-pricing-for-aws-lambda/Luc van Donkersgoed – When is the Lambda INIT phase free and when is it billed?: https://lucvandonkersgoed.com/2022/04/09/when-is-the-lambda-init-phase-free-and-when-is-it-billed/AWS Bites – Explaining Lambda Runtimes (Episode 104): https://awsbites.com/104-explaining-lambda-runtimes/AWS Blog – Standardized Billing for Lambda INIT Phase: https://aws.amazon.com/blogs/compute/aws-lambda-standardizes-billing-for-init-phase/Lambda Cold Start Benchmarks by Maxim David: https://maxday.github.io/lambda-perf/Duckbill Group Blog – Lambda Logs Just Got Cheaper: https://www.duckbillgroup.com/blog/lambda-logs-just-got-cheaper/AWS Bites – Becoming a Logs Ninja with CloudWatch (Episode 35): https://awsbites.com/35-how-can-you-become-a-logs-ninja-with-cloudwatchDo you have any AWS questions you would like us to address?Leave a comment here or connect with us on X/Twitter, BlueSky or LinkedIn:- ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/eoins⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠https://bsky.app/profile/eoin.sh⁠⁠⁠⁠ | ⁠⁠⁠⁠https://www.linkedin.com/in/eoins/⁠⁠⁠⁠- ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/loige⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠https://bsky.app/profile/loige.co⁠⁠⁠⁠ | ⁠⁠⁠⁠https://www.linkedin.com/in/lucianomammino/

Ashley Peacock, the author of Serverless Apps on Cloudflare, speaks with host Jeremy Jung about content delivery networks (CDNs). Along the way, they examine dependency injection with bindings, local development, serverless, cold starts, the V8 runtime, AWS Lambda vs Cloudflare workers, WebAssembly limitations, and core services such as R2, D1, KV, and Pages. Ashley suggests why most users use an external database and discusses eventually consistent data stores, S3-to-R2 migration strategies, queues and workflows, inter-service communication, durable objects, and describes some example projects. Brought to you by IEEE Computer Society and IEEE Software magazine.

Today's guest is AJ Stuyvenberg, a Staff Engineer at Datadog working on their Serverless observability project. He had a great article recently about how they rewrote their AWS Lambda extension in Rust. It's a really interesting look at a big, hard project, from thinking about when it's a good idea to do a rewrite to talking about their focus on performance and reliability above all else and what he thinks about the Rust ecosystem. Beyond that, AJ is just a learning machine, so I got his thoughts on all kinds of software development topics, from underrated AWS services and our favorite databases to the AWS Free Tier and the annoyances of a new AWS account. Finally, AJ dishes out some career advice for curious, ambitious developers.

In this conversation, Krish Palaniappan discusses the intricacies of deploying an API gateway on AWS, focusing on the management of API usage, reporting, and the challenges faced with certificate management. He elaborates on the deployment strategies across different environments, the debugging process for certificate issues, and the importance of understanding endpoint types and SSL certificates. The conversation also highlights the resolution of certificate chain issues and the necessary code adjustments to ensure smooth operation. In this conversation, Krish Palaniappan discusses the intricacies of optimizing AWS Lambda layers, the transition from AWS SDK version 2 to version 3, and the importance of efficient deployment strategies. He emphasizes the need for local development and testing using Express to enhance productivity and streamline the onboarding process for customers, including API key management and usage plans. Snowpal Products Backends as Services on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AWS Marketplace⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Mobile Apps on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠App Store⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Play Store⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Web App⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Education Platform⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for Learners and Course Creators

Managing security for a device that can autonomously interact with third-party services presents unique orchestration challenges that go beyond traditional IoT security models. In this episode of Detection at Scale, Matthew Domko, Head of Security at Rabbit, gives Jack an in-depth look at building security programs for AI-powered hardware at scale.   He details how his team achieved 100% infrastructure-as-code coverage while maintaining the agility needed for rapid product iteration. Matt also challenges conventional approaches to scaling security operations, advocating for a serverless-first architecture that has fundamentally changed how they handle detection engineering. His insights on using private LLMs via Amazon Bedrock to analyze security events showcase a pragmatic approach to AI adoption, focusing on augmentation of existing workflows rather than wholesale replacement of human analysis.  Topics discussed: How transitioning from reactive SIEM operations to a data-first security approach using AWS Lambda and SQS enabled Rabbit's team to handle complex orchestration monitoring without maintaining persistent infrastructure.  The practical implementation of LLM-assisted detection engineering, using Amazon Bedrock to analyze 15-minute blocks of security telemetry across their stack.  A deep dive into security data lake architecture decisions, including how their team addressed the challenge of cost attribution when security telemetry becomes valuable to other engineering teams.  The evolution from traditional detection engineering to a "detection-as-code" pipeline that leverages infrastructure-as-code for security rules, enabling version control, peer review, and automated testing of detection logic while maintaining rapid deployment capabilities. Concrete examples of integrating security into the engineering workflow, including how they use LLMs to transform security tickets to match engineering team nomenclature and communication patterns. Technical details of their data ingestion architecture using AWS SQS and Lambda, showing how two well-documented core patterns enabled the team to rapidly onboard new data sources and detection capabilities without direct security team involvement. A pragmatic framework for evaluating where generative AI adds value in security operations, focusing on specific use cases like log analysis and detection engineering where the technology demonstrably improves existing workflows rather than attempting wholesale process automation.  Listen to more episodes:  Apple  Spotify  YouTube Website

In this episode, we explore DuckDB, an open-source analytical database known for its speed and simplicity. Discover how DuckDB stands out in various applications and compare it to other tools like SQLite, Athena, Pandas, and Polars. We also demonstrate integrating DuckDB with AWS Lambda and Step Functions for serverless analytics.AWS Bites is brought to you by fourTheorem. If you are looking for a partner to architect, develop and modernise on AWS, give fourTheorem a call. Check out ⁠fourtheorem.com⁠In this episode, we mentioned the following resources: Our `duck-query-lambda`, A Lambda runtime for DuckDB queries: https://github.com/fourTheorem/duck-query-lambda DuckDB's official website: https://duckdb.org/ LibSQL: https://github.com/tursodatabase/libsql Do you have any AWS questions you would like us to address?Leave a comment here or connect with us on X/Twitter, BlueSky or LinkedIn:- ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/eoins⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | https://bsky.app/profile/eoin.sh | https://www.linkedin.com/in/eoins/- ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/loige⁠⁠⁠⁠ | https://bsky.app/profile/loige.co | https://www.linkedin.com/in/lucianomammino/

In this episode, we discuss using AWS Lambda Powertools for Python to build serverless REST APIs with AWS Lambda. We cover the benefits of using Powertools for routing, validation, OpenAPI support, and more. Powertools provides an excellent framework for building APIs while maintaining Lambda best practices.In this episode, we mentioned the following resources: AWS Bites 41. How can Middy make writing Lambda functions easier? - ⁠https://awsbites.com/41-how-can-middy-make-writing-lambda-functions-easier⁠ AWS Bites 120. Lambda Best Practices - ⁠https://awsbites.com/120-lambda-best-practices/⁠ REST API - Powertools for AWS Lambda (Python) - ⁠https://docs.powertools.aws.dev/lambda/python/latest/core/event_handler/api_gateway/⁠ Hono - ⁠https://hono.dev/⁠ Fastify - ⁠https://fastify.dev/⁠ Axum - ⁠https://github.com/tokio-rs/axum⁠ FastAPI - ⁠https://fastapi.tiangolo.com/⁠Do you have any AWS questions you would like us to address?Leave a comment here or connect with us on BlueSky or LinkedIn: https://bsky.app/profile/eoin.sh | https://www.linkedin.com/in/eoins/ https://bsky.app/profile/loige.co | https://www.linkedin.com/in/lucianomammino/

AWS Community Builder and Software/Platform Engineer Ervin Szilágyi joins us today to talk about his project: creating a BlueSky Bot (for good, not evil

Join us on a serverless computing journey! Host Keith Townsend is with Amazon Web Services' Usman Khalid, Director, AWS Lambda on this episode of Six Five On The Road at AWS re:Invent. They look at a decade of evolution and what's in store for the future of serverless computing with AWS Lambda. Tune in for details

Sébastien Stormacq joins us to talk about AWS Lambda and Swift - what does "Serverless" mean, how deployment works, and how to get started.GuestSébastien ☁ Stormacq

This week, we discuss the relationship between DevOps and Platform Engineering, Gartner's take on Distributed Hybrid Infrastructure, and Nvidia's search for new use cases. Plus, a listener chimes in to clear up some Podman misconceptions. Watch the YouTube Live Recording of Episode (https://www.youtube.com/watch?v=DyjB-jmL0QQ) 495 (https://www.youtube.com/watch?v=DyjB-jmL0QQ) Runner-up Titles Prove me wrong AWS, prove me wrong Please turn off the lights Who's googling for “shift left”? I realized what they were talking about, it's computers They're talking but you're not listening Piling on the dead horse We gave this guy $5 billion dollars, check him out Podman is Pepsi Nobody's paying for that Niche Player Rundown Platform Engineering Is The New DevOps (https://www.forbes.com/sites/justinwarren/2024/11/21/platform-engineering-is-the-new-devops/) SRE Books (https://sre.google/books/) Magic Quadrant for Distributed Hybrid Infrastructure (https://www.gartner.com/doc/reprints?id=1-2J0PN9ZJ&ct=241007&st=sb&trk=0da8abef-e59d-40d4-b66b-ba96c755768b&sc_channel=el) AWS named as a leader again in the Gartner Magic Quadrant for Distributed Hybrid Infrastructure (https://aws.amazon.com/blogs/aws/aws-named-as-a-leader-again-in-the-gartner-magic-quadrant-for-distributed-hybrid-infrastructure/) Nvidia AI Easts the World — Benedict Evans (https://www.ben-evans.com/presentations) Nvidia revenue almost doubles on the year even as growth slows from previous quarter (https://on.ft.com/3Vpw2Z1) Nvidia's Huang Spreads the Gospel of AI in Search of More Customers (https://www.bloomberg.com/news/newsletters/2024-11-21/nvidia-s-huang-spreads-the-gospel-of-ai-in-search-of-more-customers?srnd=undefined) Amazon Updates Homegrown Chips, Even as It Grows Nvidia Ties (https://links.message.bloomberg.com/a/click?_t=f574328d4d0c4c359b90d8e49b10e21d&_m=e253c47d1776426cada2b989eb51ef3d&_e=BISdgjckKJ39RYZ5axUkOu4DkhEzj_0CzmZEdaLS3niAwih7Lch-yccqByy-SKSB_PawXlFTeOpypVo4aikKnrEHKgvZ1v2TyAeErFN65ZsdRhzpsl63CY7Ia4-4Y_AmaM8n0A6iEaAPInfkiRKNT3xf8OE6NLeC4L7EavGfLanwRXXmv773517sL7d2HT-Rcewoj4Ilv2S4WBW0l3E797KSeKHwZmNv3h9g8B7rUMFKXg8gnlDDRuYjGkBMn8m9-4yP3laYhYAwEeaW3arWkc1bzZFYO_N0fzB31aRoEEvMjvCyXvrv-fg1yhLbDHFZFK5xDr2cgqT8uxPoHajG8qPT7nzRt_56WNcg30HnKZ2OwDxnLJkIDzw47BuHXtk-BMsx5WG7Gn51NdUiPqUTAV5YHattNV9B5gmGwXtVZubp-eOJfFuCVKrLgVwrMLLqGMLEFhgI00D0RHwpXFbHDg%3D%3D) Nvidia Earnings, Strawberry and Video, The Networking Question (https://stratechery.com/2024/nvidia-earnings-strawberry-and-video-the-networking-question/) Podman: Podman in Action | Red Hat Developer (https://developers.redhat.com/e-books/podman-action) Kubernetes Podcast from Google: Episode 164 - Podman, with Daniel Walsh and Brent Baude (https://kubernetespodcast.com/episode/164-podman/) DevOps and Docker Talk: Cloud Native Interviews and Tooling | Podman In Action: Desktop, Machine, and more (https://podcast.bretfisher.com/episodes/podman-in-action-desktop-machine-and-more) Relevant to your Interests Microsoft Ignite 2024: Everything Revealed in 15 Minutes (https://www.youtube.com/watch?v=_4qsQ6OWZsM) Microsoft Ignite 2024: all the news from Microsoft's IT pro event (https://www.theverge.com/2024/11/19/24300001/microsoft-ignite-2024-news-ai-announcements-copilot-windows-azure-office) AWS Lambda turns ten – looking back and looking ahead | Amazon Web Services (https://aws.amazon.com/blogs/aws/aws-lambda-turns-ten-the-first-decade-of-serverless-innovation/) Kyndryl insiders claim new business is scarce (https://www.theregister.com/2024/11/20/kyndryl_little_new_business/) Snowflake snaps up data management company Datavolo (https://techcrunch.com/2024/11/20/snowflake-snaps-up-data-management-company-datavolo/) Northflank raises $22M to make Kubernetes work for your developers (https://northflank.com/blog/northflank-raises-22m-to-make-kubernetes-work-for-your-developers-ship-workloads-not-infrastructure) Overcast adds new listening stats and 48-hour undo features (https://9to5mac.com/2024/11/20/overcast-listening-history-undo-features/) Reddit was down — latest updates on major outage (https://www.tomsguide.com/news/live/reddit-down-live-updates-on-outage) Wiz acquires Dazz for $450M to expand its cybersecurity platform (https://techcrunch.com/2024/11/21/wiz-acquires-dazz-for-450m-to-expand-its-cybersecurity-platform/) Comcast is spinning off its cable TV business (https://www.theverge.com/2024/11/20/24301310/comcast-spinning-off-nbcuniversal-cable-tv-business) Snowflake's shares surge higher on blowout earnings, (https://t.co/alQ7p57V3y) Clouded Judgement 11.22.24 - Is Software Back? 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DevOpsDayLA (https://www.socallinuxexpo.org/scale/22x/events/devopsday-la) at SCALE22x (https://www.socallinuxexpo.org/scale/22x), March 6-9, 2025, discount code DEVOP SDT News & Community Join our Slack community (https://softwaredefinedtalk.slack.com/join/shared_invite/zt-1hn55iv5d-UTfN7mVX1D9D5ExRt3ZJYQ#/shared-invite/email) Email the show: questions@softwaredefinedtalk.com (mailto:questions@softwaredefinedtalk.com) Free stickers: Email your address to stickers@softwaredefinedtalk.com (mailto:stickers@softwaredefinedtalk.com) Follow us on social media: Twitter (https://twitter.com/softwaredeftalk), Threads (https://www.threads.net/@softwaredefinedtalk), Mastodon (https://hachyderm.io/@softwaredefinedtalk), LinkedIn (https://www.linkedin.com/company/software-defined-talk/), BlueSky (https://bsky.app/profile/softwaredefinedtalk.com) Watch us on: Twitch (https://www.twitch.tv/sdtpodcast), YouTube (https://www.youtube.com/channel/UCi3OJPV6h9tp-hbsGBLGsDQ/featured), Instagram (https://www.instagram.com/softwaredefinedtalk/), TikTok (https://www.tiktok.com/@softwaredefinedtalk) Book offer: Use code SDT for $20 off "Digital WTF" by Coté (https://leanpub.com/digitalwtf/c/sdt) Sponsor the show (https://www.softwaredefinedtalk.com/ads): ads@softwaredefinedtalk.com (mailto:ads@softwaredefinedtalk.com) Recommendations Brandon: Cursor (https://www.cursor.com/) Matt: iPhone Mirroring in macOS (https://www.google.com/search?client=safari&rls=en&q=iPhone+Mirroring+in+macOS+15&ie=UTF-8&oe=UTF-8) (https://www.google.com/search?client=safari&rls=en&q=iPhone+Mirroring+in+macOS+15&ie=UTF-8&oe=UTF-8)15 (https://www.google.com/search?client=safari&rls=en&q=iPhone+Mirroring+in+macOS+15&ie=UTF-8&oe=UTF-8) Coté: Insta360 Flow Pro gimbal (https://amzn.to/4g7t9UA) Photo Credits Header (https://unsplash.com/photos/clear-light-bulb-lot-PIrOQrqewLE) Artwork (https://unsplash.com/s/photos/grade-evaluation) Web 2.0 2FA Life Hacks (https://www.troyhunt.com/beyond-passwords-2fa-u2f-and-google-advanced-protection/)

Bret and Nirmal Mehta are joined by Ken Collins to dig into using AI for more than coding, and if we can build an AI assistant that knows us.They touch on a lot of tools and platforms. "We're bit all over the place on this one, from talking about AI features in our favorite note taking apps like Notion, to my journey of making an open AI assistant with all of my Q&A from my courses, thousands of questions and answers, to coding agents and more." Ken is a local friend in Virginia Beach and was on the show last year talking about AWS Lambda, and we've both been trying to find value in all of these AI tools for our day to day work.Be sure to check out the live recording of the complete show from October 24, 2024 on YouTube (Stream 279).★Topics★The Lifestyle Copilot Blog PostServerless AI Inference with Gemma 2 Blog Post Creators & Guests Cristi Cotovan - Editor Beth Fisher - Producer Bret Fisher - Host Ken Collins - Guest Nirmal Mehta - Host (00:00) - Intro (01:26) - AI in Recruitment at Torc (03:25) - AI for Day to Day Workflows (04:44) - Notion AI and RAG (07:20) - Creating Your Own AI Search Solution (13:59) - Choosing the Right LLM for the Job (20:55) - Personal AI and Long Context Windows (25:10) - Future of Personal Fine-Tuned Models (25:52) - AI Assistants in Meetings (27:34) - Temperature and AI Hallucinations (32:07) - Agents and Tool Integration (39:31) - Apple Intelligence and Personal AI (44:56) - AI Apps on Mobile (50:00) - LoRA You can also support my free material by subscribing to my YouTube channel and my weekly newsletter at bret.news!Grab the best coupons for my Docker and Kubernetes courses.Join my cloud native DevOps community on Discord.Grab some merch at Bret's Loot BoxHomepage bretfisher.com

An airhacks.fm conversation with Vadym Kazulkin (@VKazulkin) about: journey as a Java developer from the late 1990s to present, early experiences with Java and J2EE development, transition to cloud and serverless technologies, particularly AWS Lambda, discussion of Java performance on lambda compared to node.js, detailed explanation of AWS SnapStart technology for improving Java cold starts, pros and cons of "fat" Lambda functions versus microservices, challenges of using GraalVM with Lambda, importance of optimizing Lambda package size and dependencies, comparison of quarkus and Spring Boot on Lambda, benefits of serverless architecture for business logic focus, involvement with Java User Group Bonn and AWS Community Builder program, brief mention of asynchronous patterns in serverless architectures, importance of staying technically hands-on as a manager in the rapidly evolving cloud world Vadym Kazulkin on twitter: @VKazulkin

AWS Morning Brief for the week of November 4, with Corey Quinn. Links:Amazon CloudWatch now monitors EBS volumes exceeding provisioned performanceAmazon Q Developer announces support for inline chat to streamline the developer experienceAmazon Route 53 announces HTTPS, SSHFP, SVCB, and TLSA DNS resource record supportAmazon Virtual Private Cloud launches new security group sharing featuresAWS now accepts partial card paymentsAnnouncing AWS Amplify integration with Amazon S3 for static website hostingAWS CodeBuild now supports retrying builds automaticallyAWS Trust & Safety Center is now available on AWS re:Post2024 re:Invent Know Before You Go – Cloud Financial Management SessionsIntroducing an enhanced local IDE experience for AWS Lambda developers

AWS Morning Brief for the week of October 28, with Corey Quinn. Links:Amazon Aurora launches Global Database writer endpointAmazon Connect now offers screen sharingAmazon EKS endpoints now support connectivity over Internet Protocol version 6 (IPv6)AWS IAM Identity Center simplifies calls to AWS services with single identity contextEC2 Image Builder now supports building and testing macOS imagesIntroducing an enhanced in-console editing experience for AWS Lambda

De Java 23 à WebAssembly, en passant par l'IA et les design patterns, on a tout passé au crible #java #swift #webassembly #wordpress #webcomponents #llm #mongodb #keycloak #fairsource Enregistré le 18 octobre 2024 Téléchargement de l'épisode LesCastCodeurs-Episode–317.mp3 News Langages Java 23 est sorti ! InfoQ liste toutes les JEPs intégrées à la nouvelle version https://www.infoq.com/news/2024/09/java23-released/ Et FooJay plonge dans le détail https://foojay.io/today/java–23-has-arrived-and-it-brings-a-truckload-of-changes/ JEP 455: Primitive Types in Patterns, instanceof, and switch (Preview) JEP 466: Class-File API (Second Preview) JEP 467: Markdown Documentation Comments JEP 469: Vector API (Eighth Incubator) JEP 471: Deprecate the Memory-Access Methods in sun.misc.Unsafe for Removal JEP 473: Stream Gatherers (Second Preview) JEP 474: ZGC: Generational Mode by Default JEP 476: Module Import Declarations (Preview) JEP 477: Implicitly Declared Classes and Instance Main Methods (Third Preview) JEP 480: Structured Concurrency (Third Preview) JEP 481: Scoped Values (Third Preview) JEP 482: Flexible Constructor Bodies (Second Preview) StringTemplate s'en va Un article sur l'API ClassFile qui sera un standard dans le JDK pour manipuler des classes (ala ASM) https://www.unlogged.io/post/class-file-api-not-your-everyday-java-api article long mais qui revient sur les raisons notamment parce que ASM est dans le JDK et qu'ils sont un problème de poule et d'oeuf et sur la forme de l'API a des exemples d'usage tout cela reste en preview dans le JDK des optimisation comme le lazy parsing et le constant pool sharing (en gros faire de la reference sur ce qui n'a pas changé Tip and Tail is back: cette fois une JEP https://openjdk.org/jeps/14 plus qu'une keynote provocative au language summit maintenant une JEP dite informative le language est un pu flou sur l'objectif entre regarder tip and tail pour vos librairies c'est bien et adoptons tous le meme tip du JDK jusqu'aux stack applicatives Apple annonce la sortie de son language Swift en version 6 https://www.swift.org/blog/announcing-swift–6/ Nouvelles plateformes : Swift 6 s'étend à de nouvelles plateformes (tous les grands OS déjà supportés), y compris les systèmes embarqués (sous ARM et Risc V). Swift Testing : Swift 6 introduit Swift Testing, une nouvelle bibliothèque de tests conçue pour Swift. Concurrence : Détection de data race en tant qu'erreur de compilation. Apple annonce travailler sur l'interopérabilité Swift / Java https://github.com/swiftlang/swift-java comme jextract mais dans l'autre sens The news Java https://www.infoq.com/news/2024/10/java-news-roundup-oct07–2024/ JDK 24 : Un calendrier pour la sortie de JDK 24 a été proposé. La première phase de réduction des fonctionnalités commencera le 5 décembre 2024. La version finale sera disponible le 18 mars 2025. JDK 24 introduira des mises à jour avec deux nouvelles API. La Vector API (JEP 489) facilitera les opérations sur des vecteurs, tandis que la Class-File API (JEP 484) permettra une manipulation plus efficace des fichiers de classes Java. Un changement de sécurité important est proposé avec JEP 486. Il prévoit de désactiver définitivement le Security Manager, qui a été déprécié. Cette décision signifie que cette fonctionnalité ne sera plus disponible dans les futures versions, car elle est considérée comme obsolète. Apache Tomcat et Cassandra : Les nouvelles versions de Tomcat (11.0.0) et de Cassandra (5.0.0) sont sorties. Elles incluent des améliorations et des corrections de bogues. Spring Framework : Des mises à jour pour Spring Framework (versions 3.4.0-M2, 3.3.3 et 3.2.8) ont été publiées. Elles intègrent le support d'une nouvelle API qui aide à la gestion de la mémoire. Quarkus : Red Hat a sorti la version 3.15 de Quarkus, qui apporte des corrections et des améliorations. Une nouvelle version, la 3.16, est prévue pour la fin octobre. Commonhaus Foundation : Une nouvelle organisation, la Commonhaus Foundation, a été créée pour aider les projets open source à être durables. Quarkus a rejoint cette fondation. Cassandra, Camel, Lamgchain, Micronaut, OpenLibery, JHipster, Ktor etc. Design patterns revisited: https://www.youtube.com/watch?v=kE5M6bwruhw Design and design patterns. Optional: patterns and anti-patterns. Iterator pattern. Lightweight Strategy. Factory Method using default methods. Laziness using Lambda Expressions. Decorator using Lambda Expressions. Creating Fluent interfaces. Execute Around Method Pattern. Creating a Closed Hierarchy with sealed classes. Popularité des langages de programmation https://www.techspot.com/news/105157-python-most-popular-coding-language-but-challengers-gaining.html Python reste le langage de programmation le plus populaire, surtout dans des domaines comme la science des données et le développement web. Il est apprécié pour sa simplicité et le grand nombre de bibliothèques disponibles, ce qui le rend facile à apprendre et à utiliser. De nombreuses entreprises, y compris des startups, utilisent Python pour diverses applications. Malgré sa dominance, d'autres langages comme JavaScript, Java et Go gagnent en popularité et pourraient défier la position de leader de Python. (Java est monté du poste 4 au 3, en 1 an) Les développeurs qui codent occasionnellement préfèrent Python, montrant ainsi son attrait au-delà des programmeurs professionnels. L'émergence d'outils comme ChatGPT facilite l'accès à la programmation, ce qui pourrait influencer les tendances futures en matière de langages de programmation. Librairies Paramétrer ses tests JUnit 5 avec @CsvSource https://mikemybytes.com/2021/10/19/parameterize-like-a-pro-with-junit–5-csvsource/ l'annotation permet d'avoir ses données de test au plus près de la méthode on écrit les données de test sous forme de CSV (éventuellement avec des délimiteurs de son choix pour plus de lisibilité, pour bien séparer les valeurs) par exemple -> ou maps to les valeurs peut être les paramètres de la method mai aussi les valeur de description du test Infrastructure Turbocharged Development: The Speed and Efficiency of WebAssembly par Danielle Lancashire https://devsummit.infoq.com/presentation/munich2024/turbocharged-development-speed-and-efficiency-webassembly L'utilisation de WebAssembly avec Serverless. Faire tourner des applications plus facilement dans le cloud.WebAssembly est rapide et sûr pour exécuter du code. Cela aide à déployer les applications plus rapidement et à utiliser moins de ressources. De nombreuses entreprises utilisent WebAssembly pour des tâches comme le traitement d'images et de données. Des plateformes comme Cloudflare Workers et AWS Lambda. La communauté autour de WebAssembly granèit. De nouveaux outils et bibliothèques sont créés. Cependant, il y a encore des défis à relever, comme la compatibilité et les performances. Malgré cela, l'avenir de WebAssembly est prometteur. Web C'est la guerre chez Wordpress https://techcrunch.com/2024/09/26/wordpress-vs-wp-engine-drama-explained/ une boite nommée WP Engine fait du hosting de WordPress mais ne contribue pas Automatic, les gens derrière WordPress leur onbt demandé de résoudre ce probleme, soit en payant des droits de trademark soit en contribuant de l'engineering upstream à auteur de 8% de leurs revenus WP Engine dit non Automatic coupe l'accès aux mises a jours de thèmes et de plugins à WP Engine mettant des sites à risque (securité) WP Engine dit que c'est un abus de position du CEO d'Automatic sur les accès WordPress.org Bref c'est le drame le CEO d'automatic propose à ses employés 6 mois de salaire si ils ne sont pas d'accord avec la stratégie https://www.cio.com/article/3550331/one-twelfth-of-automattic-staff-leave-over-wordpress-wp-engine-spat.html 8% ont pris l'offre Les WebComposants ne sont pas le fuitur https://dev.to/ryansolid/web-components-are-not-the-future–48bh un article d'un auteur proéminent de framework JavaScript Discute les avantages et les inconvenients de la standardisation qui permet d'élever le débat mais aussi bloque des avenues d'optimisations beaucoup d'exemples d'inovations en frameworks JS qui auraient été bloqués Les commentaires apres l'article sont interessants aussi (en contre perspective) mais tout le monde n'est pas d'accord avec cet article https://www.abeautifulsite.net/posts/web-components-are-not-the-future-they-re-the-present/ Data et Intelligence Artificielle Conseils et bonnes pratiques lors de l'intégration de LLM dans une application https://glaforge.dev/posts/2024/09/23/some-good-practices-when-integrating-an-llm-in-your-application/ management de prompt effectif versionnage et externalisation des prompts fixer la version des modèles optimisation et caching mettre en place des rails de sécurité évaluer et monitorer le comportement et la performance prioriser la sécurité des données privées Encore une nouvelle version de LangChain4j, avec la version 0.35 ! Guillaume couvre les nouveautés côté Gemini et Google Cloud https://glaforge.dev/posts/2024/09/29/lots-of-new-cool-gemini-stuff-in-langchain4j/ Support des toutes nouvelles versions de Gemini 1.5 (version 002) Un “document loader” pour charger des documents à partir de Google Cloud Storage Un “scoring model” qui permet de faire du “reranking” de résultat, pour trouver les résultats les plus pertinents pour une requête donnée Support de nouveaux paramètres des embedding models (choix de la dimensionalité des vecteurs, du troncage des textes en entrée) Ajout d'un “embedding model” pour le module Google AI Gemini Un estimateur de token pour Google AI Gemini Support des chat listeners Support des enums pour la sortie structurée JSON Et plein de mise à jour de la documentation pour refleter tous ces changements et aditions Self Correction Algo LLM https://www.infoq.com/news/2024/10/google-deepmind-score/ Google DeepMind a récemment publié SCoRe, une nouvelle méthode d'auto-correction pour les modèles de langage (LLM). Elle améliore la capacité des LLM à corriger leurs erreurs lorsqu'ils résolvent des problèmes de mathématiques ou de programmation. Contrairement aux méthodes antérieures, SCoRe utilise des données générées par le modèle lui-même pour créer des dialogues d'auto-correction. Cela permet au modèle de s'améliorer via un processus d'apprentissage par renforcement (RL) en deux étapes. Les modèles ajustés avec cette technique ont montré des améliorations significatives, surpassant les performances des modèles de base. Cette méthode pourrait ouvrir de nouvelles pistes pour rendre les LLM plus précis et robustes dans leurs réponses. MongoDB 8 est sorti https://www.mongodb.com/products/updates/version-release La version 8.0 est plus rapide, avec des lectures plus rapides, une meilleure gestion des mises à jour et des agrégations de séries temporelles jusqu'à 60 % plus rapides. De nouvelles fonctionnalités incluent le support des Query pour les données chiffrées, rendant le traitement des données sensibles plus facile. Beaucoup d'ameliorations pour la performance et scalabilité Guillaume explore les techniques avancées de Retrieval Augmented Generation pour améliorer la qualité des résultats de recherche dans ses propres documents, avec les LLMs https://glaforge.dev/talks/2024/10/14/advanced-rag-techniques/ Présentations et vidéos données lors de la conférence Devoxx Belgique Code des exemples disponibles sur Github Techniques de chunking : sliding window, hypothetical questions, semantic chunking, context retrieval chunking Techniques de retrieval : hypothetical document embedding, query compression, metadata filtering Outillage Article sur les cache alias en Infinispan https://infinispan.org/blog/2024/10/07/cache-aliases-redis-databases Explique comment on peut utiliser Infinispan pour remplacer Redis Explique la différence entre les database de Redis et les caches d'Infinispan Explique l'utilité des alias en général Explique comment on peut avoir un mapping des databases de Redis vers des caches d'Infinispan Sécurité Keycloak 26 est sorti: https://www.keycloak.org/2024/10/keycloak–2600-released Organizations feature: permet aux administrateurs de créer et gérer des structures organisationnelles, facilitant la gestion des rôles et des permissions. Persistent user sessions: Les sessions des utilisateurs sont maintenant stockées par default dans la base de donnée ce qui améliore la cohérence, surtout avec plusieurs instances. Login Theme: Offre un design plus propre et une option de mode sombre qui s'adapte aux préférences des utilisateurs. L'amélioration du déploiement multi-sites renforce la fiabilité et réduit le temps d'arrêt lors des demandes des utilisateurs. Admin recovery: une méthode simple pour récupérer l'accès administrateur si tous les comptes sont bloqués, en créant un compte temporaire via des variables d'environnement. Pour les utilisateurs qui migrent vers cette version, il est important de prêter attention aux changements liés à la gestion des caches et aux sessions persistantes. Loi, société et organisation Introduction des licences fair source https://techcrunch.com/2024/09/22/some-startups-are-going-fair-source-to-avoid-the-pitfalls-of-open-source-licensing/ Certaines startups utilisent des licences “fair source” pour partager leur code tout en protégeant leurs intérêts commerciaux. Les licences FSL (Functional Source License) et BUSL (Business Source License) permettent d'ouvrir le code après 2 ou 4 ans. Ces licences empêchent les concurrents de vendre des produits similaires tout de suite, offrant une protection temporaire. Certains critiques pensent que ces licences sont compliquées et pourraient limiter l'innovation, car elles ne sont pas totalement ouvertes. Le “fair source” est encore un concept nouveau, mais il pourrait devenir un bon compromis entre open source et logiciel privé. definition de fair source: code lisible publique, peut etre utilise et modifié avec des “restrictions minimales” pour proteger le business modele du producteur ; et devient open source de maniere deferée “any purpose other than a Competing Use. A Competing Use means use of the Software in or for a commercial product or service that competes with the Software or any other product or service we offer using the Software as of the date we make the Software available” Outils de l'épisode Un petit outil sympa pour les utilisateurs de Macs avec un écran “wide”, pour partager un écran virtuel : https://github.com/Stengo/DeskPad les écrans larges sont partagés entierement et ceui fait un rendu 16:9 pour les gens qui le voient cet écran acte comme un écran mais il est virtuel et on peut mettre les applications que l'on veut dedans on ne l'a pas testé Conférences La liste des conférences provenant de Developers Conferences Agenda/List par Aurélie Vache et contributeurs : 17–18 octobre 2024 : DevFest Nantes - Nantes (France) 17–18 octobre 2024 : DotAI - Paris (France) 30–31 octobre 2024 : Agile Tour Nantais 2024 - Nantes (France) 30–31 octobre 2024 : Agile Tour Bordeaux 2024 - Bordeaux (France) 31 octobre 2024–3 novembre 2024 : PyCon.FR - Strasbourg (France) 6 novembre 2024 : Master Dev De France - Paris (France) 7 novembre 2024 : DevFest Toulouse - Toulouse (France) 8 novembre 2024 : BDX I/O - Bordeaux (France) 13–14 novembre 2024 : Agile Tour Rennes 2024 - Rennes (France) 16–17 novembre 2024 : Capitole Du Libre - Toulouse (France) 20–22 novembre 2024 : Agile Grenoble 2024 - Grenoble (France) 21 novembre 2024 : DevFest Strasbourg - Strasbourg (France) 21 novembre 2024 : Codeurs en Seine - Rouen (France) 27–28 novembre 2024 : Cloud Expo Europe - Paris (France) 28 novembre 2024 : Who Run The Tech ? - Rennes (France) 2–3 décembre 2024 : Tech Rocks Summit - Paris (France) 3 décembre 2024 : Generation AI - Paris (France) 3–5 décembre 2024 : APIdays Paris - Paris (France) 4–5 décembre 2024 : DevOpsRex - Paris (France) 4–5 décembre 2024 : Open Source Experience - Paris (France) 5 décembre 2024 : GraphQL Day Europe - Paris (France) 6 décembre 2024 : DevFest Dijon - Dijon (France) 22–25 janvier 2025 : SnowCamp 2025 - Grenoble (France) 30 janvier 2025 : DevOps D-Day #9 - Marseille (France) 6–7 février 2025 : Touraine Tech - Tours (France) 25 mars 2025 : ParisTestConf - Paris (France) 3 avril 2025 : DotJS - Paris (France) 10–12 avril 2025 : Devoxx Greece - Athens (Greece) 16–18 avril 2025 : Devoxx France - Paris (France) 7–9 mai 2025 : Devoxx UK - London (UK) 12–13 juin 2025 : DevLille - Lille (France) 24 juin 2025 : WAX 2025 - Aix-en-Provence (France) 18–19 septembre 2025 : API Platform Conference - Lille (France) & Online 9–10 octobre 2025 : Volcamp - Clermont-Ferrand (France) Nous contacter Pour réagir à cet épisode, venez discuter sur le groupe Google https://groups.google.com/group/lescastcodeurs Contactez-nous via twitter https://twitter.com/lescastcodeurs Faire un crowdcast ou une crowdquestion Soutenez Les Cast Codeurs sur Patreon https://www.patreon.com/LesCastCodeurs Tous les épisodes et toutes les infos sur https://lescastcodeurs.com/

In this episode of the vBrownBag, Damian does a deep dive on getting started with PowerShell on AWS Lambda. He covers setting up a development environment, packaging & publishing PowerShell on Lambda, lessons learned, and more! 00:28 A quick overview of PowerShell & AWS Lambda

We'll explore 3 use cases for monitoring data. They are:* Analyzing long-term trends* Comparing over time or experiment groups* Conducting ad hoc retrospective analysis Analyzing long-term trends You can ask yourself a couple of simple questions as a starting point:* How big is my database?* How fast is the database growing? * How quickly is my user count growing?As you get comfortable with analyzing data for the simpler questions, you can start to analyze trends for less straightforward questions like:* How is the database performance evolving? Are there signs of degradation?* Is there consistent growth in data volume that may require future infrastructure adjustments?* How is overall resource utilization trending over time across different services?* How is the cost of cloud resources evolving, and what does that mean for budget forecasting?* Are there recurring patterns in downtime or service degradation, and what can be done to mitigate them?Sebastian mentioned that it's a part of observability he enjoys doing. I can understand why. It's exciting to see how components are changing over a period and working out solutions before you end up in an incident response nightmare.Getting to effectively analyze the trends requires the right level of data retention settings. Because if you're throwing out your logs, traces, and metrics too early, you will not have enough historical data to do this kind of work.Doing this right means having the right amount of data in place to be able to analyze those trends over time, and that will of course depend on your desired period. Comparing over time or experiment groupsGoogle's definitionYou're comparing the data results for different groups that you want to compare and contrast. Using a few examples from the SRE (2016) book:* Are your queries faster in this version of this database or this version of that database? * How much better is my memcache hit rate with an extra node and is my site slower than it was last week? You're comparing it to different buckets of time and different types of products.A proper use case for comparing groupsSebastian did this particular use case recently because he had to compare two different technologies for deploying code: AWS Lambda vs AWS Fargate ECS. He took those two services and played around with different memories and different virtual CPUs. Then he ran different amounts of requests against those settings and tried to figure out which one was the better technology option most cost-effectively.His need for this went beyond engineering work but enabling product teams with the right decision-making data. He wrote out a knowledge base article to give them guidance for a more educated decision on the right AWS service.Having the data to compare the two services allowed him to answer questions like:* When should you be using either of these technologies? * What use cases would either technology be more suitable for?This data-based decision support is based mainly on monitoring or observability data. The idea of using the monitoring data to compare tools and technologies for guiding product teams is something I think reliability folk can gain a lot of value from doing. Conducting ad hoc retrospective analysis (debugging)Debugging is a bread-and-butter responsibility for anyone who is a software engineer of any level. It's something that everybody should know a little bit more about than other tasks because there are very effective and also very ineffective ways of going about debugging. Monitoring data can help make the debugging process fall into the effective side.There are organizations where you have 10 different systems. In one system, you might get one fragmented piece of information. In another, you'll get another fragment. And so on for all the different systems. And then you have to correlate these pieces of information in your head and hopefully, you get some clarity out of the fragments to form some kind of insight. Monitoring data that are brought together into one datastream can help correlate and combine all these pieces of information. With it, you can:* Pinpoint slow-running queries or functions by analyzing execution times and resource usage, helping you identify inefficiencies in your code* Correlate application logs with infrastructure metrics to determine if a performance issue is due to code errors or underlying infrastructure problems* Track memory leaks or CPU spikes by monitoring resource usage trends, which can help you identify faulty code or services* Set up detailed error tracking that automatically flags code exceptions and matches them with infrastructure events, to get to the root cause faster* Monitor system load alongside application performance to see if scaling issues are related to traffic spikes or inefficient code pathsBeing able to do all this makes the insight part easier for you. And so your debugging approach becomes very different. It becomes much more effective. It becomes much less time-consuming. It potentially makes the debugging task fun.Because you get to the root cause of the thing that is not working much faster. Your monitoring/observability data setup can make it nice and fun to a certain degree, or it can make it downright miserable. If it's done well, it's just one of those things you don't even have to think about. It's just part of your job. You do it. It's very effective and you move on. Wrapping upSo we've covered three more use cases for monitoring data, other than the usual alerts and dashboards.They are once again:* analyzing long-term trends* comparing over time or experiment groups and* conducting ad hoc retrospective analysis, aka debuggingNext time your boss asks you what all these systems do, you now have three more reasons that you need to focus on your monitoring and be able to use it more effectively. Until next time, happy monitoring. This is a public episode. 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Thank you to Hookdeck for sponsoring this episode. If you're looking to level-up your event-driven architecture, then check out their serverless event gateway at hookdeck.com/theburningmonk and help support this channel.AWS Serverless Hero Luciano Mammino shares the history of Middy, the popular middleware engine for AWS Lambda functions; why he's sold on writing Lambda functions in Rust and why you should too!Links from the episode:AWS Bites channelMiddyHow to sponsor MiddyCrafting Lambda Functions in RustEasy mode RustUsing Node.js ES modules and top-level await in AWS LambdaUsing Middy with TypescriptEp97 on LLRT (the superfast JavaScript runtime for Lambda)Opening theme song:Cheery Monday by Kevin MacLeodLink: https://incompetech.filmmusic.io/song/3495-cheery-mondayLicense: http://creativecommons.org/licenses/by/4.0

What are you doing differently today that you're stopping tomorrow's legacy? In this episode Ashish spoke to Adrian Asher, CISO and Cloud Architect at Checkout.com, to explore the journey from monolithic architecture to cloud-native solutions in a regulated fintech environment. Adrian shared his perspective on why there "aren't enough lambdas" and how embracing cloud-native technologies like AWS Lambda and Fargate can enhance security, scalability, and efficiency. Guest Socials:⁠ ⁠⁠Adrian's Linkedin ⁠ Podcast Twitter - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@CloudSecPod⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels: - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security Podcast- Youtube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security Newsletter ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security BootCamp Questions asked: (00:00) Introduction (01:59) A bit about Adrian (02:47) Cloud Naive vs Cloud Native (03:54) Checkout's Cloud Native Journey (05:44) What is AWS Fargate? (06:52) There are not enough Lambdas (09:52) The evolution of the Security Function (12:15) Culture change for being more cloud native (15:23) Getting security teams ready for Gen AI (18:16) Where to start with Cloud Native? (19:14) Where you can connect with Adrian? (19:39) The Fun Section

How to secure AWS cloud using AWS Lambda? We spoke to Lily Chau from Roku at BSidesSF about her experience and innovative approach to tackling security issues in AWS environments. From deploying IAM roles to creating impactful playbooks with AWS Lambda, Lily shared her take on automating remediation processes. We spoke about the challenges of managing cloud security with tools like CSPM and CNAPP, and how Lily and her team took a different approach that goes beyond traditional methods to achieve real-time remediation. Guest Socials:⁠ ⁠⁠Lily Twitter Podcast Twitter - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@CloudSecPod⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ If you want to watch videos of this LIVE STREAMED episode and past episodes - Check out our other Cloud Security Social Channels: - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security Podcast- Youtube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security Newsletter ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cloud Security BootCamp Questions asked: (00:00) Introduction (01:56) A bit about Lily (02:27) What is Auto Remediation? (03:56) Example of Auto Remediation (05:19) CSPMs and Auto Remediation (06:58) Make Auto Remediation in Cloud work for you (09:49) Where to get started with Auto Remediation? (11:52) What defines a High Impact Playbook? (12:58) Auto Remediation for Lateral Movement (14:35) What is running in the background? (16:41) What skillset is required? (19:08) The Fun Section Resources for the episode: Lily's talk at BsidesSF

Scott and Wes chat with Richard Davison from AWS about LLRT, a new runtime tailored specifically for Lambda. They dive into the benefits of using LLRT, challenges with JavaScript in serverless, and why Rust was chosen for its development. Show Notes 00:00 Welcome to Syntax! 01:07 Who is Richard Davison? 05:11 What is LLRT and what's the motivation for building it? 08:25 AWS Lambda example. 11:20 What makes LLRT specifically tailored to Lambda? 14:55 Brought to you by Sentry.io. 15:22 Node.js in Lambda. 16:00 What are some challenges that people have with JavaScript in serverless? 17:20 Lambda memory configuration. 19:23 Managing cost of compute. 21:29 Simpler and faster than Node, Bun, Dino, but not a replacement. 22:31 The benchmarks. 27:00 Quick.js, the main reason for the performance gains. Fabrice Bellard QuickJS. 28:03 The Quick.js engine. 30:35 What was the reason behind creating Quick.js? 33:46 What made you pick Rust for LLRT? 36:34 Abstractions and the value of speed. 39:08 The JIT Compiler. 42:38 Compile cache. 43:27 De-optimizations. 44:59 Node.js Compat, what to use and avoid with LLRT. GitHub AWS Labs Compatibility Chart. 47:52 Will you target with WinterCG spec? 50:22 Streams API. 52:06 What about WebSockets? 53:10 Is this going to be promoted from a labs project? 54:49 Sick Picks + Shameless Plugs. Sick Picks Richard: QuickJS Engine, JSLinux. Shameless Plugs Richard: Javascript Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott: X Instagram Tiktok LinkedIn Threads Randy: X Instagram YouTube Threads

On this episode of the Six Five Webcast - AWS Serverless Series, Keith Townsend is joined by Amazon Web Services' AWS Lambda Usman Khalid and Spencer Dillard for a conversation on leveraging AWS Serverless technologies to achieve rapid innovation without compromising security. Their discussion covers: The advantages of the Serverless operating model versus traditional application development Common security challenges in modern application development and how AWS addresses these The shared responsibility model for securing Serverless applications on AWS Built-in protections provided by AWS Serverless services like AWS Lambda and Amazon ECS with AWS Fargate How the ephemeral nature of Serverless resources contributes to security  

Poor air quality is a major global issue causing around 7 million premature deaths per year, disproportionately affecting low and middle income countries. OpenAQ is an organization dedicated to identifying solutions to this large issue. OpenAQ uses Amazon Web Services (AWS) to collect and harmonize open air quality data from government sources and low-cost sensors around the world, ingesting around 10-12 million measurements daily. To learn more, the Fix This team sat down with Russ Biggs, director of technology at OpenAQ. Russ shared how AWS Lambda helps OpenAQ scale its data collection and harmonization pipeline in a serverless manner. And helps scientists, environmental justice groups, and community organizations access OpenAQ's data to study air pollution impacts, advocate for regulations, and raise awareness.

What is the state of serverless computing and Python in 2024? What are some of the new tools and best practices? We are lucky to have Tony Sherman who has a lot of practical experience with serverless programming on the show. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Mailtrap Talk Python Courses Links from the show Tony Sherman on Twitter: twitter.com Tony Sherman: linkedin.com PyCon serverless talk: youtube.com AWS re:Invent talk: youtube.com Powertools for AWS Lambda: docs.powertools.aws.dev Pantsbuild: The ergonomic build system: pantsbuild.org aws-lambda-power-tuning: github.com import-profiler: github.com AWS Fargate: aws.amazon.com Run functions on demand. Scale automatically.: digitalocean.com Vercel: vercel.com Deft: deft.com 37 Signals We stand to save $7m over five years from our cloud exit: world.hey.com The Global Content Delivery Platform That Truly Hops: bunny.net Watch this episode on YouTube: youtube.com --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy

In this episode, I spoke with Ian Griffiths, a Technical Fellow at Endjin, a Microsoft MVP, and the author of O'Reilly's Programming C# 10.0.In this episode, we took a deep dive into Azure Functions, how it works and how it differs (significantly) from AWS Lambda.Links from the episode:Bye bye Azure Functions, hello Azure Container AppsWASI (WebAssembly system interface)EndjinIntroductions to Reactive Extensions for .NetOpening theme song:Cheery Monday by Kevin MacLeodLink: https://incompetech.filmmusic.io/song/3495-cheery-mondayLicense: http://creativecommons.org/licenses/by/4.0

Many people are using serverless these days, often without even really thinking about it because they are the default mode of operation for many popular services like NextJS with Vercel. But what is it? Should you use it? Join Richard and I as we discuss serverless, how it works, and how we consider using it.Join The Reactors! thereactshow.com/the-reactors-communityJoin our Discord! https://discord.gg/zXYggKUBC2My book: Foundations of High-Performance React https://www.thereactshow.com/bookMusic by DRKST DWN: https://soundcloud.com/drkstdwnSupport the show

Summary Building a data platform that is enjoyable and accessible for all of its end users is a substantial challenge. One of the core complexities that needs to be addressed is the fractal set of integrations that need to be managed across the individual components. In this episode Tobias Macey shares his thoughts on the challenges that he is facing as he prepares to build the next set of architectural layers for his data platform to enable a larger audience to start accessing the data being managed by his team. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles. RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team. You specify the customer traits, then Profiles runs the joins and computations for you to create complete customer profiles. Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack (https://www.dataengineeringpodcast.com/rudderstack) You shouldn't have to throw away the database to build with fast-changing data. You should be able to keep the familiarity of SQL and the proven architecture of cloud warehouses, but swap the decades-old batch computation model for an efficient incremental engine to get complex queries that are always up-to-date. With Materialize, you can! It's the only true SQL streaming database built from the ground up to meet the needs of modern data products. Whether it's real-time dashboarding and analytics, personalization and segmentation or automation and alerting, Materialize gives you the ability to work with fresh, correct, and scalable results — all in a familiar SQL interface. Go to dataengineeringpodcast.com/materialize (https://www.dataengineeringpodcast.com/materialize) today to get 2 weeks free! Developing event-driven pipelines is going to be a lot easier - Meet Functions! Memphis functions enable developers and data engineers to build an organizational toolbox of functions to process, transform, and enrich ingested events “on the fly” in a serverless manner using AWS Lambda syntax, without boilerplate, orchestration, error handling, and infrastructure in almost any language, including Go, Python, JS, .NET, Java, SQL, and more. Go to dataengineeringpodcast.com/memphis (https://www.dataengineeringpodcast.com/memphis) today to get started! Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics. Trusted by teams of all sizes, including Comcast and Doordash, Starburst is a data lake analytics platform that delivers the adaptability and flexibility a lakehouse ecosystem promises. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data. Want to see Starburst in action? Go to dataengineeringpodcast.com/starburst (https://www.dataengineeringpodcast.com/starburst) and get $500 in credits to try Starburst Galaxy today, the easiest and fastest way to get started using Trino. Your host is Tobias Macey and today I'll be sharing an update on my own journey of building a data platform, with a particular focus on the challenges of tool integration and maintaining a single source of truth Interview Introduction How did you get involved in the area of data management? data sharing weight of history existing integrations with dbt switching cost for e.g. SQLMesh de facto standard of Airflow Single source of truth permissions management across application layers Database engine Storage layer in a lakehouse Presentation/access layer (BI) Data flows dbt -> table level lineage orchestration engine -> pipeline flows task based vs. asset based Metadata platform as the logical place for horizontal view Contact Info LinkedIn (https://linkedin.com/in/tmacey) Website (https://www.dataengineeringpodcast.com) Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ (https://www.pythonpodcast.com) covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast (https://www.themachinelearningpodcast.com) helps you go from idea to production with machine learning. Visit the site (https://www.dataengineeringpodcast.com) to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com (mailto:hosts@dataengineeringpodcast.com)) with your story. To help other people find the show please leave a review on Apple Podcasts (https://podcasts.apple.com/us/podcast/data-engineering-podcast/id1193040557) and tell your friends and co-workers Links Monologue Episode On Data Platform Design (https://www.dataengineeringpodcast.com/data-platform-design-episode-268) Monologue Episode On Leaky Abstractions (https://www.dataengineeringpodcast.com/abstractions-and-technical-debt-episode-374) Airbyte (https://airbyte.com/) Podcast Episode (https://www.dataengineeringpodcast.com/airbyte-open-source-data-integration-episode-173/) Trino (https://trino.io/) Dagster (https://dagster.io/) dbt (https://www.getdbt.com/) Snowflake (https://www.snowflake.com/en/) BigQuery (https://cloud.google.com/bigquery) OpenMetadata (https://open-metadata.org/) OpenLineage (https://openlineage.io/) Data Platform Shadow IT Episode (https://www.dataengineeringpodcast.com/shadow-it-data-analytics-episode-121) Preset (https://preset.io/) LightDash (https://www.lightdash.com/) Podcast Episode (https://www.dataengineeringpodcast.com/lightdash-exploratory-business-intelligence-episode-232/) SQLMesh (https://sqlmesh.readthedocs.io/) Podcast Episode (https://www.dataengineeringpodcast.com/sqlmesh-open-source-dataops-episode-380) Airflow (https://airflow.apache.org/) Spark (https://spark.apache.org/) Flink (https://flink.apache.org/) Tabular (https://tabular.io/) Iceberg (https://iceberg.apache.org/) Open Policy Agent (https://www.openpolicyagent.org/) The intro and outro music is from The Hug (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/Love_death_and_a_drunken_monkey/04_-_The_Hug) by The Freak Fandango Orchestra (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/) / CC BY-SA (http://creativecommons.org/licenses/by-sa/3.0/)