Podcasts about Observability

Scientific research is the foundation of many innovative solutions in any field. Did you know that Dynatrace runs its own Research Lab within the Campus of the Johannes Kepler University (JKU) in Linz, Austria - just 2 kilometers away from our global engineering headquarter? What started in 2020 has grown to 20 full time researchers and many more students that do research on topics such as GenAI, Agentic AI, Log Analytics, Procesesing of Large Data Sets, Sampling Strategies, Cloud Native Security or Memory and Storage Optimizations.Tune in and hear from Otmar and Martin how they are researching on the N+2 generation of Observability and AI, how they are contributing to open source projects such as OpenTelemetry, and what their predictions are when AI is finally taking control of us humans!To learn more about their work check out these links:Martin's LinkedIn: https://www.linkedin.com/in/mflechl/Otmar's LinkedIn: https://www.linkedin.com/in/otmar-ertl/Dynatrace Research Lab: https://careers.dynatrace.com/locations/linz/#__researchLab

Highlights from this week's conversation include:Background of ClickHouse (1:14)PostgreSQL Data Replication Tool (3:19)Emerging Technologies Observations (7:25)Observability and Market Dynamics (11:26)Product Development Challenges (12:39)Challenges with PostgreSQL Performance (15:30)Philosophy of Open Source (18:01)Open Source Advantages (22:56)Simplified Stack Vision (24:48)End-to-End Use Cases (28:13)Migration Strategies (30:21)Final Thoughts and Takeaways (33:29)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we'll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.

Connect to John Gilroy on LinkedIn   https://www.linkedin.com/in/john-gilroy/ Want to listen to other episodes? www.Federaltechpodcast.com AFCEA'S TechNet Cyber conference held in Baltimore, Maryland was the perfect opportunity to sit down with Bryan Rosensteel, Head of Public Sector Marketing at Wiz.  Wiz is the “new kid on the block,” and it has had tremendous growth.  During the interview, Bryan Rosensteel shows how agentless approaches can improve visibility and assist with compliance.  We all know how complexity has infiltrated federal technology.  We have the usual suspect of Cloud Service Providers, hybrid clouds, private clouds, and, if that was not complicated enough, alt-clouds.  As a result, it is almost impossible to get a “bird's eye” visibility to provide cyber security. Two main ways have been proposed to secure this much-desired system's view. Agent.  One approach is to put a bit of code on each device, called an “agent” method.  It is good for granular control, but can slow down a scan and must be maintained Agentless.  Bryan Rosensteel from Wiz describes something called a “agentless” method to gain visibility into complex systems.  This method leverages infrastructure and protocols to accomplish the scanning objective much faster. Bryan Rosensteel states that in a world of constant attacks, this faster method allows for rapid updates to threats. Beyond better observation, an agentless method, like the one provided by Wiz, allows for compliance automation, continuous monitoring, and sets the groundwork for effective Zero Trust implementation.

In episode 81 of o11ycast, Charity Majors and Martin Thwaites dive into a lively discussion with Hazel Weakly and Matt Klein on the evolving landscape of observability. The guests explore the concept of observability versioning, the challenges of cost and ROI, and the future of observability tools, including the potential convergence with AI and business intelligence.

In this episode of the DevOps Toolchain podcast, Joe Colantonio sits down with Jacob Leverich, cofounder and Chief Product Officer at Observe, to explore how AI and cutting-edge data strategies are transforming the world of observability. With a career spanning heavyweight roles from Splunk to Google and Kuro Labs, Jacob shares his journey from banging out Perl scripts as a Linux sysadmin to building scalable, data-driven solutions that address the complex realities of today's digital infrastructure. Tune in as Joe and Jacob explore why traditional monitoring approaches are struggling with massive data volumes, how knowledge graphs and data lakes are breaking down tool silos, and what engineering leaders often get wrong when scaling visibility across teams. Whether you're a tester, developer, SRE, or team lead, get ready to discover actionable insights on maximizing the value of your data, the true role of AI in troubleshooting, and practical tips for leading your organization into the future of DevOps observability. Don't miss it! Try out Insight Hub free for 14 days now: https://testguild.me/insighthub. No credit card required.

In episode 81 of o11ycast, Charity Majors and Martin Thwaites dive into a lively discussion with Hazel Weakly and Matt Klein on the evolving landscape of observability. The guests explore the concept of observability versioning, the challenges of cost and ROI, and the future of observability tools, including the potential convergence with AI and business intelligence.

Access the podcast to hear Greg Reeder, Senior Director of Public Sector Marketing at Datadog, and Martha Dorris, Founder of DCI Consulting, discuss how agencies increase agility and efficiency with innovative customer experience strategies, digital transformation and proactive application monitoring tools. Listen to practical use cases from the State Department, IRS and CBP showcasing how human-centric design increases engagement and public trust.

Agentic AI is equally as daunting as it is dynamic. So…… how do you not screw it up? After all, the more robust and complex agentic AI becomes, the more room there is for error. Luckily, we've got Dr. Maryam Ashoori to guide our agentic ways. Maryam is the Senior Director of Product Management of watsonx at IBM. She joined us at IBM Think 2025 to break down agentic AI done right. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Have a question? Join the convo here.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Agentic AI Benefits for EnterprisesWatson X's New Features & AnnouncementsAI-Powered Enterprise Solutions at IBMResponsible Implementation of Agentic AILLMs in Enterprise Cost OptimizationDeployment and Scalability EnhancementsAI's Impact on Developer ProductivityProblem-Solving with Agentic AITimestamps:00:00 AI Agents: A Business Imperative06:14 "Optimizing Enterprise Agent Strategy"09:15 Enterprise Leaders' AI Mindset Shift09:58 Focus on Problem-Solving with Technology13:34 "Boost Business with LLMs"16:48 "Understanding and Managing AI Risks"Keywords:Agentic AI, AI agents, Agent lifecycle, LLMs taking actions, WatsonX.ai, Product management, IBM Think conference, Business leaders, Enterprise productivity, WatsonX platform, Custom AI solutions, Environmental Intelligence Suite, Granite Code models, AI-powered code assistant, Customer challenges, Responsible AI implementation, Transparency and traceability, Observability, Optimization, Larger compute, Cost performance optimization, Chain of thought reasoning, Inference time scaling, Deployment service, Scalability of enterprise, Access control, Security requirements, Non-technical users, AI-assisted coding, Developer time-saving, Function calling, Tool calling, Enterprise data integration, Solving enterprise problems, Responsible implementation, Human in the loop, Automation, IBM savings, Risk assessment, Empowering workforce.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

Apologies for the hiatus! Dave needed some time off to recover from burnout, and these episodes remained in the can. Thanks for Waiting for us

Network monitoring, Internet monitoring, and observability are all key components of NetOps. We speak with sponsor Catchpoint to understand how Catchpoint can help network operators proactively identify and resolve issues before they impact customers. We discuss past and current network monitoring strategies and the challenges that operators face with both on-prem and cloud monitoring, along... Read more »

Network monitoring, Internet monitoring, and observability are all key components of NetOps. We speak with sponsor Catchpoint to understand how Catchpoint can help network operators proactively identify and resolve issues before they impact customers. We discuss past and current network monitoring strategies and the challenges that operators face with both on-prem and cloud monitoring, along... Read more »

Send us a textJustin Ryburn is the Field CTO at Kentik and works as a Limited Partner (LP) for Stage 2 Capital. Justin has 25 years of experience in network operations, engineering, sales, and marketing with service providers and vendors. In this conversation, we discuss startup funding,  the challenges that organizations face with hybrid and multi-cloud visibility, the impact of AI on network monitoring, and explore how companies can build more reliable systems through proper observability practices.Where to Find JustinLinkedIn: https://www.linkedin.com/in/justinryburn/Twitter: https://x.com/JustinRyburnBlog: http://ryburn.org/Talks: https://www.youtube.com/playlist?list=PLRrjaaisdWrYaue9KVLRdq5mlGE_2i0RTShow LinksKentik: https://www.kentik.com/Day One: Deploying BGP FlowSpec: https://www.juniper.net/documentation/en_US/day-one-books/DO_BGP_FLowspec.pdfStage 2 Capital: https://www.stage2.capital/Doug Madory's Internet Analysis: https://www.kentik.com/blog/author/doug-madory/Netflix Tech Blog: https://netflixtechblog.com/Multi-Region AWS: https://www.pluralsight.com/resources/blog/cloud/why-and-how-do-we-build-a-multi-region-active-active-architectureAutoCon: https://events.networktocode.com/autocon/Follow, Like, and Subscribe!Podcast: https://www.thecloudgambit.com/YouTube: https://www.youtube.com/@TheCloudGambitLinkedIn: https://www.linkedin.com/company/thecloudgambitTwitter: https://twitter.com/TheCloudGambitTikTok: https://www.tiktok.com/@thecloudgambit

Prequel is launching a new developer-focused service aimed at democratizing software error detection—an area typically dominated by large cloud providers. Co-founded by Lyndon Brown and Tony Meehan, both former NSA engineers, Prequel introduces a community-driven observability approach centered on Common Reliability Enumerations (CREs). CREs categorize recurring production issues, helping engineers detect, understand, and communicate problems without reinventing solutions or working in isolation. Their open-source tools, cre and prereq, allow teams to build and share detectors that catch bugs and anti-patterns in real time—without exposing sensitive data, thanks to edge processing using WebAssembly.The urgency behind Prequel's mission stems from the rapid pace of AI-driven development, increased third-party code usage, and rising infrastructure costs. Traditional observability tools may surface symptoms, but Prequel aims to provide precise problem definitions and actionable insights. While observability giants like Datadog and Splunk dominate the market, Brown and Meehan argue that engineers still feel overwhelmed by data and underpowered in diagnostics—something they believe CREs can finally change.Learn more from The New Stack about the latest Observability insights Why Consolidating Observability Tools Is a Smart MoveBuilding an Observability Culture: Getting Everyone Onboard Join our community of newsletter subscribers to stay on top of the news and at the top of your game. 

Su Milazzo talks about the role of operations in UX, especially where design and research operations overlap. She explains that operations work to reduce friction and improve workflows for internal teams, using empathy and change management to help them succeed.

"Having the insight and being able to stitch together your technical resources and business decisions together, is the prime place where observability can add value to you,” stated Manesh Tailor, EMEA Field CTO at New Relic.In this episode of the Tech Transformed podcast, Kevin Petrie, Vice President of Research at BARC, speaks with Manesh Tailor about the intersection of artificial intelligence (AI) and observability, and how this is positively changing business operations.Tailor emphasises how intelligent observability has changed beyond simple monitoring to provide real-time insights into customer experience and the entire technology stack. This enables informed decisions across engineering, operations, and business domains, directly linking technical performance to strategic business outcomes.He also discusses the different stages observability has been through and where it's leading to now. The current wave, Observability 3.0, takes advantage of AI to predict issues and even enable self-healing systems. New Relic has embraced this two-way street, using AI within its platform. This was in an ambition to help users and "AI monitoring" to track the performance of language models alongside traditional metrics. Such a platform provides a holistic view of system health and the cost implications of AI deployments.Alluding to the management of AI-powered applications, Tailor says collaboration is key between application and data science teams. Not only does it provide real time data but as a result leads to efficient decision making.Futuristically, the speedy proliferation of AI agents has both pros and cons for observability. This is where New Relic comes in. It addresses the challenges by constructing a platform-centric "AI orchestrator" with a growing library of AI-native agents. In essence, as AI-powered applications become increasingly integral to business operations, intelligent observability is no longer optional. TakeawaysObservability is crucial for understanding unknowns in systems.AI enhances observability by providing predictive insights.The evolution of observability includes intelligent monitoring.Collaboration between technical and business teams is essential.Cost efficiency is a key focus in modern observability.Real-time data is vital for effective decision-making.Self-healing systems represent the future of observability.AI and observability must work in tandem for success.The complexity of systems is increasing, requiring better tools.Observability is applicable across all organizational levels.Chapters00:00 Introduction to AI and Observability03:10 Defining Observability and Its Evolution05:49 The Role of AI in Observability08:46 Navigating AI-Driven Applications11:52 Target Users and Community for Observability14:57 Collaboration Across Teams17:55 Challenges and Opportunities in Observability20:47 The Future of Observability and AI23:54 Key Takeaways for CIOs and IT LeadersAbout New RelicThe New Relic Intelligent Observability Platform empowers businesses to proactively eliminate disruptions in their digital experiences. As the only AI-enhanced platform that unifies and correlates telemetry data, New...

Barr Moses, CEO & Co-Founder of Monte Carlo, challenges the notion that models alone create competitive advantage, arguing instead that the real moat lies in how organizations manage their proprietary data and ensure end-to-end reliability. Tim and Juan chat with Barr to get the Honest, No-BS scoop of what AI observability is (hint, it's really data + AI) and how organizations can build resilient AI applications.

Barr Moses, CEO & Co-Founder of Monte Carlo, challenges the notion that models alone create competitive advantage, arguing instead that the real moat lies in how organizations manage their proprietary data and ensure end-to-end reliability. Tim and Juan chat with Barr to get the Honest, No-BS scoop of what AI observability is (hint, it's really data + AI) and how organizations can build resilient AI applications.

New Relic's Head of AI and ML Innovation, Camden Swita discusses their four-cornered AI strategy and envisions a future of "agentic orchestration" with specialized agents.Topics Include:Introduction of Camden Swita, Head of AI at New Relic.New Relic invented the observability space for monitoring applications.Started with Java workloads monitoring and APM.Evolved into full-stack observability with infrastructure and browser monitoring.Uses advanced query language (NRQL) with time series database.AI strategy focuses on AI ops for automation.First cornerstone: Intelligent detection capabilities with machine learning.Second cornerstone: Incident response with generative AI assistance.Third cornerstone: Problem management with root cause analysis.Fourth cornerstone: Knowledge management to improve future detection.Initially overwhelmed by "ocean of possibilities" with LLMs.Needed narrow scope and guardrails for measurable progress.Natural language to NRQL translation proved immensely complex.Selecting from thousands of possible events caused accuracy issues.Shifted from "one tool" approach to many specialized tools.Created routing layer to select right tool for each job.Evaluation of NRQL is challenging even when syntactically correct.Implemented multi-stage validation with user confirmation step.AWS partnership involves fine-tuning models for NRQL translation.Using Bedrock to select appropriate models for different tasks.Initially advised prototyping on biggest, best available models.Now recommends considering specialized, targeted models from start.Agent development platforms have improved significantly since beginning.Future focus: "Agentic orchestration" with specialized agents.Envisions agents communicating through APIs without human prompts.Integration with AWS tools like Amazon Q.Industry possibly plateauing in large language model improvements.Increasing focus on inference-time compute in newer models.Context and quality prompts remain crucial despite model advances.Potential pros and cons to inference-time compute approach.Participants:Camden Swita – Head of AI & ML Innovation, Product Management, New RelicSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

KubeCon Europe 2025 in London has wrapped up, and we're bringing you all the highlights, trends, and behind-the-scenes insights straight from the show floor!In this special recap episode, I'm joined by two CNCF Ambassadors and community powerhouses: Kasper Borg Nissen, the Co-Chair of this KubeCon as well as of the KubeCon 2024 editions, and a Developer Relations Engineer at Dash0; and William Rizzo, Consulting Architect at Mirantis and Linkerd Ambassador.Together, we unpack the major themes from the event—from platform engineering and internal developer platforms, to open source observability, and where Kubernetes is headed next. We also chat about the vibe of the community, emerging projects to watch, and important trends in European tech sphere.Whether you missed the conference or want to catch up on important updates you might have missed, this episode gives you a curated take straight from the experts who know the cloud-native space inside out.The episode was live-streamed on 22 April 2025 and the video is available at https://www.youtube.com/watch?v=JyxJOmOEBvQYou can read the recap post: https://medium.com/p/740258a5fa46OpenObservability Talks episodes are released monthly, on the last Thursday of each month and are available for listening on your favorite podcast app and on YouTube.We live-stream the episodes on Twitch and YouTube Live - tune in to see us live, and chime in with your comments and questions on the live chat.⁠⁠https://www.youtube.com/@openobservabilitytalks⁠  https://www.twitch.tv/openobservability⁠Show Notes:00:00 - intro03:28 - KubeCon impressions09:59 - Backstage turns 518:56 - CNCF turns 10 and CNCF annual survey27:22 - Sovereign cloud in Europe and the NeoNephos initiative33:55 - CI/CD use in production increases36:52 - OpenInfra joins the Linux Foundation40:16 - Cloud native local communities, DEI and the BIPOC initiative 51:11 - Observability query standardization SIG updates59:36 - outroResources:CNCF 2024 Annual Survey https://www.cncf.io/reports/cncf-annual-survey-2024/NeoNephos initiative for sovereign EU cloud: https://www.linkedin.com/feed/update/urn:li:share:7313115943075766273/ OpenInfra Foundation and OpenStack join The Linux Foundation: https://www.linkedin.com/feed/update/urn:li:share:7307839934072066048/ Backstage turns 5: https://www.linkedin.com/feed/update/urn:li:activity:7318163557206966272/ Kubernetes 1.33 release: https://www.linkedin.com/feed/update/urn:li:activity:7321054742174924800/Socials:Twitter:⁠ https://twitter.com/OpenObserv⁠YouTube: ⁠https://www.youtube.com/@openobservabilitytalks⁠Dotan Horovits============Twitter: @horovitsLinkedIn: www.linkedin.com/in/horovitsMastodon: @horovits@fosstodonBlueSky: @horovits.bsky.socialKasper Borg Nissen===============Twitter: https://www.twitter.com/phennexLinkedIn: https://www.linkedin.com/in/kaspernissen/BlueSky: https://bsky.app/profile/kaspernissen.xyz⁠William Rizzo===========Twitter: https://twitter.com/WilliamRizzo19LinkedIn: https://www.linkedin.com/in/william-rizzo/BlueSky: https://bsky.app/profile/williamrizzo.bsky.social

Cloud monitoring and security platform Datadog on Wednesday announced that it has acquired Metaplane, an AI-powered data observability startup, for an undisclosed amount. In a press release, Datadog said that the deal “accelerates” its expansion into data observability, building on the launch of related products. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Today on the Tech Bytes podcast we're talking AI readiness with sponsor Broadcom. More specifically, getting your network observability ready to support AI operations. This isn't just a hardware or software issue. It's also a data issue. We'll get some tips with our guest Jeremy Rossbach. Jeremy is Chief Technical Evangelist and Lead Product Marketing... Read more »

Modern content systems are complex and abstract, presenting problems for managers who want to understand how their content is performing. At Autogram, Jeff Eaton and Karen McGrane have developed a content observability framework to address this complexity.  Their framework evaluates the composition, quality, health, and effectiveness of content programs to help enterprises measure the return on their content investment. https://ellessmedia.com/csi/jeff-eaton-2/

Today on the Tech Bytes podcast we're talking AI readiness with sponsor Broadcom. More specifically, getting your network observability ready to support AI operations. This isn't just a hardware or software issue. It's also a data issue. We'll get some tips with our guest Jeremy Rossbach. Jeremy is Chief Technical Evangelist and Lead Product Marketing... Read more »

Modern cloud-native systems are highly dynamic and distributed, which makes it difficult to monitor cloud infrastructure using traditional tools designed for static environments. This has motivated the development and widespread adoption of dedicated observability platforms. Prometheus is an open-source observability tool designed for cloud-native environments. Its strong integration with Kubernetes and pull-based data collection model The post Prometheus and Open-Source Observability with Eric Schabell appeared first on Software Engineering Daily.

Modern cloud-native systems are highly dynamic and distributed, which makes it difficult to monitor cloud infrastructure using traditional tools designed for static environments. This has motivated the development and widespread adoption of dedicated observability platforms. Prometheus is an open-source observability tool designed for cloud-native environments. Its strong integration with Kubernetes and pull-based data collection model The post Prometheus and Open-Source Observability with Eric Schabell appeared first on Software Engineering Daily.

New Relic's Chief Customer Officer Arnaldo (Arnie) Lopez details how their observability platform helps 70,000+ customers monitor cloud performance through AWS infrastructure while introducing AI capabilities that simplify operations.Topics Include:Arnie Lopez is SVP, Chief Customer Officer at New Relic.Oversees pre-sales, post-sales, technical support, and enablement teams.New Relic University offers customer certifications.Founded in 2008, pioneered application performance monitoring (APM).Now offers "Observability 3.0" for full-stack visibility.Prevents interruptions during cloud migration and operations.Serves 70,000+ customers across various industries.16,000 enterprise-level paying customers.Platform consolidates multiple monitoring tools into one solution.Helps detect issues before customers experience performance problems.Market challenge: customers using disparate observability solutions.Reduces TCO by eliminating multiple monitoring tools.Targets VPs, CTOs, CIOs, and sometimes CEOs.Decade-long partnership with AWS.Platform built on largest unified telemetry data cloud.Uses AWS Graviton instances and Amazon EKS.AWS partnership enables innovation and customer trust.Three AI approaches: user assistance, LLM monitoring, faster insights.New Relic AI helps write query language (NURCLs).Monitors LLMs in customer environments.Uses AI to accelerate incident resolution.Lesson learned: should have started AI implementation sooner.Many customers still cautiously adopting AI technologies.Goal: continue growth with AWS partnership.Offers compute-based pricing model.Customers only pay for what they use.Announced one-step AWS monitoring for enterprise scale.Amazon Q Business and New Relic AI integration.Agent-to-agent AI eliminates data silos.Embeds performance insights into business application workflows.Participants:Arnie Lopez – SVP Chief Customer Officer, New RelicSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Tyler Flint, CEO of qpoint.io, joins host Robert Blumen for a conversation about managing external vendor dependencies, including several best practices for adoption. They start with a look at internal versus external services, including details such as the footprint of external services within a micro-services application, and difficulties organizations have tracking their service consumption, quantifying service consumption, and auditing external services. Tyler also discusses the security implications of external services, including authentication and authorization. They examine metrics and monitoring, with recommendations on the key metrics to collect, as well as acceptable error rates for external services. From there they consider what can go wrong, how to respond to external service outages, and challenges related to testing external services. The episode wraps up with a discussion of qPoint's migration from a proxy-based solution to one based on eBPF kernel probes. Brought to you by IEEE Computer Society and IEEE Software magazine.

In this episode of SolarWinds TechPod, hosts Chrystal Taylor and Sean Sebring explore the key differences between monitoring and observability with guest Jeff Stewart, GVP of Product Management at SolarWinds. Observability goes beyond traditional monitoring, offering AI-driven insights and a holistic view of system health. Like understanding the anatomy of the body, observability reveals how IT systems are interconnected—where one issue can ripple across the entire environment. They discuss how businesses can leverage observability to reduce downtime, improve efficiency, and stay ahead in a rapidly evolving tech landscape. © 2025 SolarWinds Worldwide, LLC. All rights reserved

Definity is pioneering a new approach to data pipeline observability and optimization specifically designed for the Lakehouse and Spark ecosystem. With $4.5 million in funding, this startup aims to transform how enterprises manage their data pipelines by providing real-time observability from within the pipelines themselves. In a recent episode of Category Visionaries, I spoke with Roy Daniel, CEO and Co-Founder of Definity, about the company's journey from addressing his team's own data reliability challenges to creating a solution for enterprise teams managing mission-critical data pipelines at scale.   Topics Discussed: Definity's full-stack data observability solution designed specifically for the Lakehouse and Spark ecosystem How the product works inside data pipelines to provide real-time visibility on data quality, pipeline health, and performance The founding story rooted in the team's experience with data pipeline reliability challenges The gap in the market between application performance monitoring and data quality solutions Definity's "inside-out" approach versus traditional "outside-in" data monitoring How the company approaches marketing to enterprise customers while enabling engineers to experience the product Fundraising during the challenging market conditions of late 2023   GTM Lessons For B2B Founders: Build solutions for problems you've experienced firsthand: Roy and his co-founders created Definity to solve challenges they faced in their own careers. "We started by building the solution we always wanted to have," Roy explains. This authentic connection to the problem space enabled them to develop a product that resonates with users facing similar challenges. Position at the intersection of established categories: Definity identified that data engineering was about a decade behind software engineering in terms of observability tools. By taking elements from existing categories (data quality and application performance monitoring) but applying them with a completely new approach, they created a distinctive value proposition that stands out in a crowded market. Focus on high-value use cases and segments first: Rather than taking a broad approach, Definity targets "the tip of the sphere" - enterprise teams working with high-scale, mission-critical data pipelines. Roy notes, "We cater to teams that work at very high scale in terms of their data operation... feeding into ML models, feature stores, regulatory reporting, customer reporting." Deliver tangible value to cut through market noise: In a space filled with buzzwords, Definity focuses on demonstrating practical value. "To rise above it, you really need to deliver a unique approach," says Roy. The company launched a free assessment tool that helps teams evaluate the health and cost of their platforms, providing immediate value while showcasing their differentiated approach. Find investors who deeply understand your problem space: Roy emphasized that securing funding during the challenging 2023 market required connecting with investors who understood "the pain points of the customer with second and third degree and not just at the surface level." The right investors could appreciate the nuanced innovation they were bringing to market.   //   Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe.  www.GlobalTalent.co      

Did you know every time you order food, book a ride, or even check who viewed your profile, real-time analytics is powering your experience behind the scenes?In this episode of Great Things with Great Tech, we dive deep into the power of real-time analytics with Kishore Gopalakrishna, CEO and Co-founder of StarTree. StarTree leverages Apache Pinot, a high-performance real-time analytics database, revolutionizing how leading companies like Uber, LinkedIn, Walmart, and Etsy provide instant insights and personalized experiences at massive scale.Kishore shares his journey from a gaming enthusiast fascinated by distributed systems to building mission-critical platforms at Yahoo and LinkedIn, eventually creating Apache Pinot. Discover how StarTree is powering billions of real-time queries per week, enabling businesses to enhance customer interactions, optimize operational decisions, and supercharge modern AI and observability.Key Takeaways: How real-time analytics transform industries, enabling instantaneous insights and rapid decision-making. The evolution from traditional databases to highly efficient columnar, real-time analytics systems. Real-world applications of Apache Pinot, from consumer apps to enterprise observability and operational excellence. How real-time data is accelerating innovations in AI, specifically through Real-Time Retrieval-Augmented Generation (RAG). The future of analytics: seamless data ingestion, enhanced concurrency, and the growing demand for sub-second response times.Links & Resources: Web StarTree: https://startree.ai Kishore Gopalakrishna on LinkedIn: https://www.linkedin.com/in/kgopalak/Apache Pinot: https://pinot.apache.org☑️ Support the Channel: ⁠⁠⁠https://ko-fi.com/gtwgt⁠⁠⁠☑️ Be on #GTwGT: Contact via Twitter @GTwGTPodcast or ⁠⁠visit https://www.gtwgt.com⁠⁠☑️ Subscribe to YouTube: ⁠⁠https://www.youtube.com/@GTwGTPodcast?sub_confirmation=1⁠⁠Check out the full episode on our platforms:Spotify: ⁠⁠https://open.spotify.com/episode/2l9aZpvwhWcdmL0lErpUHC?si=x3YOQw_4Sp-vtdjyroMk3Q⁠⁠Apple Podcasts: ⁠⁠https://podcasts.apple.com/us/podcast/darknet-diaries-with-jack-rhysider-episode-83/id1519439787?i=1000654665731⁠⁠Follow Us:Website: https://gtwgt.comTwitter: https://twitter.com/GTwGTPodcastInstagram: https://instagram.com/GTwGTPodcast☑️ Music: https://www.bensound.com

For memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinSummary:In this conversation, Kaivalya Apte and Simon Eskildsen talk about vector databases, particularly focusing on TurboPuffer. They discuss the importance of vector search, embeddings, and the challenges associated with building efficient search engines. The conversation covers various aspects such as cost considerations, chunking strategies, multi-tenancy, and performance optimization. Simon shares insights on the future of vector search and the significance of observability and metrics in database performance. The discussion emphasizes the need for practical application and experimentation in understanding these technologies.Chapters:00:00 Introduction to Vector Databases10:34 Understanding Vectors and Embeddings15:03 Example: Designing a Search Engine for Podcasts27:53 Scaling Challenges in Vector Search36:46 Indexing and Querying in TurboPuffer38:12 Understanding Indexing and Query Planning45:45 Exploring Index Types and Their Performance50:27 Data Ingestion and Embedding Retrieval54:19 Use Cases and Challenges in Vector Search01:01:22 Metrics and Observability in Vector Databases01:03:52 Future Trends in Vector Search and DatabasesReferences:How do build a database on Object Storage? https://youtu.be/RFmajOeUKnETurbopuffer https://turbopuffer.com/Continous Recall measurement: https://turbopuffer.com/blog/continuous-recallTurbopuffer architecture: https://turbopuffer.com/architecture

This week, we discuss the shifting world of observability, the nightmare of “Configuration Hell,” and OpenAI's latest valuation. Plus, a surprise Broadway musical review! Runner-up Titles We say we're friends, but I don't really know them Observability 2025 I don't have any sympathy for anyone If you want to win observability, put on a musical Just is THE trigger word It's a well-known Hell The blog posts are making me angry Rundown CISO MUSICAL | Official Broadway Trailer (https://www.youtube.com/watch?v=4W17F9Ho_38) Monitoring is back Observability 3.0 - bitdrift Blog (https://blog.bitdrift.io/post/observability-3-0) Another observability 3.0 appears on the horizon (https://charity.wtf/2025/03/24/another-observability-3-0-appears-on-the-horizon/) ControlTheory Secures $5M Seed Funding to Bring Controllability to Observability (https://www.controltheory.com/blog/controltheory-secures-5m-seed-funding-to-bring-controllability-to-observability/) What is (https://www.controltheory.com/blog/what-is-controllability/) Cloud veterans launch ConfigHub to fix 'configuration hell' (https://techcrunch.com/2025/03/26/cloud-veterans-launch-confighub-to-fix-configuration-hell/) DOGE Plans to Rebuild SSA Codebase In Months, Risking Benefits and System Collapse (https://www.wired.com/story/doge-rebuild-social-security-administration-cobol-benefits/) OpenAI Exclusive | The Secrets and Misdirection Behind Sam Altman's Firing From OpenAI (https://www.wsj.com/tech/ai/the-real-story-behind-sam-altman-firing-from-openai-efd51a5d?st=GmdXEX&reflink=desktopwebshare_permalink) OpenAI closes $40 billion funding round, largest private tech deal on record (https://www.cnbc.com/2025/03/31/openai-closes-40-billion-in-funding-the-largest-private-fundraise-in-history-softbank-chatgpt.html) Relevant to your Interests How vibe coding will affect Engineering Managers (https://newsletter.manager.dev/p/effect-of-ai-on-engineering-managers) Mastering GitHub Copilot: When to use AI agent mode (https://github.blog/ai-and-ml/github-copilot/mastering-github-copilot-when-to-use-ai-agent-mode/) Using Spring AI 1.0.0-SNAPSHOT: Important Changes and Updates (https://spring.io/blog/2025/03/27/spring-ai-update-to-snapshots) Former Intel CEO Pat Gelsinger Makes a Few More Long-Shot Bets (https://www.wsj.com/articles/former-intel-ceo-pat-gelsinger-makes-a-few-more-long-shot-bets-01e7337f) Pat Gelsinger has joined VC firm Playground Global (https://www.axios.com/newsletters/axios-pro-rata-ad45da7c-2daa-4290-b379-bba556718155.html?chunk=2&utm_term=emshare#story2) Amazon Is Canceling a Major Alexa Privacy Feature on March 28: Should You Worry? (https://www.cnet.com/home/security/amazon-is-canceling-this-alexa-privacy-feature-on-march-28-should-you-worry/) oneAPI: A New Era of Heterogeneous Computing (https://www.intel.com/content/www/us/en/developer/tools/oneapi/overview.html#gs.kqodnv) Amazon unveils Nova Act, an AI agent that can control a web browser (https://techcrunch.com/2025/03/31/amazon-unveils-nova-act-an-ai-agent-that-uses-a-web-browser/) Ransomware Found in VSCode Extensions Raises Concerns Over Microsoft's Security Review (https://www.cysecurity.news/2025/03/ransomware-found-in-vscode-extensions.html?m=1) Lip-Bu Tan says Intel will spin off non-core units (https://techcrunch.com/2025/04/01/lip-bu-tan-says-intel-will-spin-off-non-core-units/) Announcing Chainguard VMs: Minimal, Zero-CVE Container Host Images (https://www.chainguard.dev/unchained/announcing-chainguard-vms-minimal-zero-cve-container-host-images) Andreessen Horowitz in talks to help buy out TikTok's Chinese owners (https://on.ft.com/4iXhAkG) Nonsense This couple is obsessed with Costco. Why do they love it so much? (https://www.deseret.com/2024/1/10/24031947/joy-of-costco-susan-and-david-schwartz-king-husein-utah/) CISO MUSICAL | Official Broadway Trailer (https://www.youtube.com/watch?v=4W17F9Ho_38) Conferences DevOps Days Atlanta (https://devopsdays.org/events/2025-atlanta/welcome/), April 29-30 Cloud Foundry Day US (https://events.linuxfoundation.org/cloud-foundry-day-north-america/), May 14th, Palo Alto, CA NDC Oslo (https://ndcoslo.com/), May 21-23, Coté speaking. 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: OrbStack · Fast, light, simple Docker & Linux (https://orbstack.dev/) Photo Credits Header (https://unsplash.com/photos/red-theater-curtain-WW1jsInXgwM)

So you think Distributed Tracing is the new thing? Well - its not! But its never been as exciting as today!In this episode we combine 50 years of Distributed Tracing experience across our guests and hosts. We invited Christoph Neumueller and Thomas Rothschaedl who have seen the early days of agent-based instrumentation, how global standards like the W3C Trace Context allowed tracing to connect large enterprise systems and how OpenTelemetry is commoditizing data collection across all tech stacks.Tune in and learn about the difference between spans and traces, why collecting the data is only part of the story, how to combat the challenge when dealing with too much data and how traces relate and connect to logs, metrics and events.Links we discussedYouTube with Christoph: LINK WILL FOLLOW ONCE VIDEO IS POSTEDChristoph's LinkedIn: https://www.linkedin.com/in/christophneumueller/Thomas's LinkedIn: https://www.linkedin.com/in/rothschaedl/

Join us as we sit down with Austin Parker, Director of Open Source at Honeycomb.io to discuss observability with OpenTelemetry, explaining its importance in cloud native software and discussing the OpenTelemetry project's growth and community contributions. He shares insights on the evolution and adoption of Open Telemetry, its impact on the software industry, and the collaborative nature of its development.  00:00 Introduction 00:45 Understanding OpenTelemetry 02:48 The Importance of Observability 05:01 Challenges and Innovations in Observability 09:36 The OpenTelemetry Community 12:12 Challenges with Vendor Lock-In 14:29 Encouraging New Contributions 18:07 Recognizing Community Contributions 20:24 Final Thoughts   Guest: Austin Parker is Director of Open Source at honeycomb.io, an OpenTelemetry maintainer and governance member, author of several books, and all around great person.  

Observability into mobile native applications presents unique challenges, from capturing real user interactions to dealing with network constraints and battery efficiency. In this episode of OpenObservability Talks, we explore the special characteristics of client-side telemetry, and how OpenTelemetry helps generate mobile client telemetry for real user monitoring (RUM), enabling deeper insights into performance and user experience. We host Hanson Ho, Android architect at Embrace and an approver on the OpenTelemetry Android SDK. Hanson brings a wealth of experience from Twitter, Salesforce and SAP. He will share his expertise on instrumenting mobile apps, the evolution of OpenTelemetry for Android, and best practices for collecting and analyzing mobile telemetry. Tune in to learn how to bring OpenTelemetry-powered observability to your mobile applications!The episode was live-streamed on 17 March 2025 and the video is available at https://www.youtube.com/watch?v=kIid85wO8gcOpenObservability Talks episodes are released monthly, on the last Thursday of each month and are available for listening on your favorite podcast app and on YouTube.We live-stream the episodes on Twitch and YouTube Live - tune in to see us live, and chime in with your comments and questions on the live chat.⁠⁠https://www.youtube.com/@openobservabilitytalks⁠  https://www.twitch.tv/openobservability⁠Show Notes:00:00 - Intro01:42 - the unique characteristics of mobile env03:39 - Android presents additional challenges05:41 - observability in everyday frontend dev12:01 - observability for business metrics in mobile apps18:28 - collecting telemetry in constrained mobile devices23:03 - Twitter scale observability into mobile apps 29:01 - how mobile monitoring used to work before OpenTelemetry33:37 - OpenTelemetry expansion from server-side into client-side telemetry 44:09 - OpenTelemetry Android SDK working group50:53 - Embrace's journey into OpenTelemetry1:00:04 - Outro Resources:OpenTelemetry Android SDK: https://github.com/open-telemetry/opentelemetry-androidOpenTelemetry Client SDK and Instrumentation SIG board: https://github.com/orgs/open-telemetry/projects/19/views/1 Adding client-side support to OpenTelemetry: https://medium.com/p/a389144f3812#2fcf  Socials:Twitter:⁠ https://twitter.com/OpenObserv⁠YouTube: ⁠https://www.youtube.com/@openobservabilitytalks⁠Dotan Horovits============Twitter: @horovitsLinkedIn: www.linkedin.com/in/horovitsMastodon: @horovits@fosstodonBlueSky: @horovits.bsky.socialHanson Ho==========LinkedIn: https://www.linkedin.com/in/hanson-ho/BlueSky: https://bsky.app/profile/bidetofevil.wtf

Digital transformation has been a federal buzzword for years, but what's the first step in making it a reality? It all starts with knowing what's on your network and being able to monitor it before and during a transition.     This week on Feds At the Edge, our expert guests take a deep dive into the future of network monitoring and digital transformation.     Tom Gilmore, Enterprise Data Architect in the USMC, drops a staggering statistic: in just 2.5 years, over 15,000 applications were built and deployed across the Marine Corps—many of which are likely duplicates. This explosion of tools raises the question: how do we manage this sprawl effectively?     Joshua Stageberg, Vice President of Product at SolarWind, dives into the exponential growth of network monitoring tools, cautioning against "tool sprawl" and the siloed observability it creates. Instead, he advocates for a unified, single-pane view as the key to true modernization, offering not just insights into apps and data, but a roadmap for optimizing computing and operational efficiency.     Tune in on your favorite podcasting platform today for valuable lessons on collaborating with operations teams, addressing their pain points, and using observability to drive more effective and efficient digital transformation.    

CEO Joe Kim shares how Sumo Logic has implemented generative AI to democratize data analytics, leveraging AWS Bedrock's multi-agent capabilities to dramatically improve accuracy.Topics Include:Introduction of Joe Kim, CEO of Sumo Logic.Question: Overview of Sumo Logic's products and customers?Sumo Logic specializes in observability and security markets.Company leverages industry-leading log management and analytics capabilities.Question: How has generative AI entered this space?Kim's background is in product, strategy and engineering.Non-experts struggle to extract value from complex telemetry data.Generative AI provides easier interface for interacting with data.Question: How do you measure success of AI initiatives?Focus on customer problems, not retrofitting AI everywhere.Launched "Mo, the co-pilot" at AWS re:Invent.Mo enables natural language queries of complex data.Mo suggests visualizations and follow-up questions during incidents.Question: What challenges did you face implementing AI?Team knew competitors would eventually implement similar capabilities.Single model approach topped out at 80% accuracy.Multi-agent approach with AWS Bedrock achieved mid-90% accuracy.Bedrock offered security benefits and multiple model capabilities.Question: How was working with the AWS team?Partnered with Bedrock team and tribe.ai for implementation.Partners helped avoid pitfalls from thousands of prior projects.Question: What advice for other software leaders?Don't implement AI just to satisfy board pressure.Identify problems without mentioning generative AI first.Innovation should come from listening to customers.Question: Future plans with AWS partnership?Moving toward automated remediation beyond just analysis.Question: Has Sumo Logic monetized generative AI?Changed pricing from data ingestion to data usage.New model encourages more data sharing without cost barriers.Participants:Joe Kim – Chief Executive Officer, Sumo LogicSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

In today's episode, we're diving into proactive observability and testing with our special guest, Anam Hira, cofounder of Reveal.ai. Anam, who also has experience working at Uber AI, shares an intriguing journey where he developed "Dragon Crawl," an innovative project aimed at tackling challenges Uber faced with its end-to-end testing across multiple cities. We explore how Dragon Crawl utilized LLMs to enhance testing reliability, making tests less flaky across varied UIs. Anam's journey didn't stop there. He co-founded Reveal, a platform that takes testing and observability to a new level by connecting end-to-end tests with telemetry data. This modern approach, termed proactive observability, allows for detecting bugs before they hit production, saving companies significant time and cost. Join us as we explore the principles of proactive observability, how Reveal leverages telemetry for seamless integration, and its impact on testing efficiency. Whether you're a startup or an enterprise, if you're keen to ship faster without sacrificing quality, this is an episode you won't want to miss!

AI agents are set to transform software development, but software itself isn't going anywhere—despite the dramatic predictions. On this episode of The New Stack Makers, Mark Hinkle, CEO and Founder of Peripety Labs, discusses how AI agents relate to serverless technologies, infrastructure-as-code (IaC), and configuration management. Hinkle envisions AI agents as “dumb robots” handling tasks like querying APIs and exchanging data, while the real intelligence remains in large language models (LLMs). These agents, likely implemented as serverless functions in Python or JavaScript, will automate software development processes dynamically. LLMs, leveraging vast amounts of open-source code, will enable AI agents to generate bespoke, task-specific tools on the fly—unlike traditional cloud tools from HashiCorp or configuration management tools like Chef and Puppet. As AI-generated tooling becomes more prevalent, managing and optimizing these agents will require strong observability and evaluation practices. According to Hinkle, this shift marks the future of software, where AI agents dynamically create, call, and manage tools for CI/CD, monitoring, and beyond. Check out the full episode for more insights. Learn more from The New Stack about emerging trends in AI agents: Lessons From Kubernetes and the Cloud Should Steer the AI RevolutionAI Agents: Why Workflows Are the LLM Use Case to Watch Join our community of newsletter subscribers to stay on top of the news and at the top of your game. 

Ben Sigelman is the Co-Founder & CEO of observability platform Lightstep as well as Co-Creator of open source observability frameworks OpenTracing and OpenTelemetry. Lightstep was acquired by ServiceNow in 2021 and OpenTelemetry was released in 2019 and has since become the standard observability framework. In this episode, we dig into:The founding story for Lightstep - including the initial pivot into the ideaThe benefits Lightstep got from open sourcing OpenTracing The OpenTracing and OpenCensus merger into OpenTelemetryWhy OpenTelemetry has been so widely adopted Ben's perspective on the many companies building with OpenTelemetry todayHow their team made the decision to take the ServiceNow acquisition Company building learnings around team building (& more!)

The infusion of compute-heavy AI across enterprise applications and work flows, growing appetite for real-time business intelligence and more digitization calls for an expansion of compute, storage and networking resources. The growing dependency on digital services and tools likely necessitates ongoing monitoring of the IT value chain to prevent business disruption and reduce time to remediate. These shifts will likely drive demand for platforms like Grafana Labs. In this episode of the Tech Disruptors podcast, Raj Dutt, co-founder and CEO at Grafana, joins Sunil Rajgopal, Bloomberg Intelligence's senior software analyst, to discuss the impact of DeepSeek, emerging data and large language model-focused observability solutions. They also talk about implications from agentic work flows, future growth paths and competition.

Fiddler is pioneering AI observability technology to help enterprises deploy trustworthy artificial intelligence. With $68 million in funding, Fiddler provides a "watchdog" platform that continuously monitors AI models, enabling companies to maximize ROI while minimizing risks. In a recent episode of Category Visionaries, I sat down with Krishna Gade, CEO and Founder of Fiddler, to discuss the critical importance of transparency in AI systems and how businesses can safely operationalize AI capabilities in an era where AI applications are rapidly proliferating across industries. Topics Discussed: The evolution of AI from classical machine learning to generative AI and agentic systems The transparency challenges associated with increasingly complex "black box" AI models How Fiddler's observability platform provides insights into AI model performance and trustworthiness The emergence of "AI observability" as a defined category in enterprise tech The tension between maximizing AI's business value while minimizing associated risks The ongoing transformation of enterprise software as AI becomes central to every application Major AI trends including decreasing model training costs and the rise of automation through AI agents //   Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. www.FrontLines.io The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe.  www.GlobalTalent.co  

This is a bonus episode of Real Talks, and it's all about Perform. Perform isn't just a conference held by Dynatrace in LA every year—it's where innovation in observability & security, customers' success, and community come to light. I sit down with Michelle Vaughan, VP of Growth Marketing, to unpack her impressions and takeaways from this year's flagship event. You'll hear some stories about the software you use daily powered by Dynatrace (and you likely don't know about it). With 2,000+ in-person attendees, 25,000+ virtual, 50+ customer stories, and groundbreaking insights in AI, security, and observability, there's plenty to dive into. Tune in to hear what made Perform an unforgettable experience, from inspiring customer stories to hands-on learning—and yes, even the legendary Dynatrace socks. Enjoying the episode? Leave us a comment on Spotify or YouTube, or rate it on Spotify or Apple Podcasts.  Where to find us:     Connect with Sue Quackenbush on LinkedIn Connect with Michelle Vaughan on LinkedIn  Discover the opportunities at Dynatrace and take your career to the next level: careers.dynatrace.com

Matthew Bonig, chief cloud architect at Defiance Digital, and co-author of the AWS CDK book, joins the vBrownBag crew to talk about leveraging observability & AI in software development. Chapters: 00:00 Roger, Damian, and Matthew have a bit of a chit-chat 03:27 Introducing Matthew

Daniel Roth is a Principal Product Manager on the ASP.NET team working on ASP.NET Core, Blazor, and other web features. He has previously worked on various parts of .NET, including System.Net, WCF, XAML, and ASP.NET. His passions include building frameworks for modern Web frameworks that are simple and easy to use.   Topics of Discussion: [3:15] Daniel shares his journey from back-end services to front-end development and his role in making .NET open-source and cross-platform. [6:10] Blazor and its impact on development. [8:32] A few of the strengths we get with .NET. [9:24] .NET 9 and performance improvements. [12:45] .NET 10 Preview 1 and new features. [17:32] Architectural guidance for Blazor applications. [30:17] The importance of handling state persistence to avoid memory bloat and security issues. [32:32] Observability and telemetry in Blazor. [36:28] Is the nature of the UI web user interface changing as we integrate AI technology and large language models and agents? [37:12] Integration of AI and Generative AI in Blazor. [37:38] The new Microsoft Extensions AI library for interfacing with chat services in .NET applications.   Mentioned in this Episode: Clear Measure Way Architect Forum Software Engineer Forum Programming with Palermo — New Video Podcast! Email us at programming@palermo.net. Clear Measure, Inc. (Sponsor) .NET DevOps for Azure: A Developer's Guide to DevOps Architecture the Right Way, by Jeffrey Palermo Ep 274 with Daniel Roth Daniel Roth LinkedIn What's New for ASP.NET Core Blazor in .NET9 Daniel Roth — Author in .NET Blog Performance Improvements in .NET9 .NET Preview 1 is now available! ASP.NET Core in .NET 10 Preview 1 — Release Notes ASP.NET Core Roadmap for .NET 10 #59443   Want to Learn More? Visit AzureDevOps.Show for show notes and additional episodes.

In this episode, Derric sits down with Mike Amundsen, a leader in the API ecosystem, to explore the evolving role of observability in API design and customer experience. They break down the differences between machine vs. customer observability, best practices for tracking key metrics, and the importance of designing observability into APIs from the start. Mike also shares insights on API product management, the lifecycle of APIs, and how organizations can adapt to AI-driven changes in observability. Whether you're a developer, product manager, or business leader, this episode is packed with valuable takeaways on optimizing API-driven businesses.

In this episode of MongoDB TV, join Shane McAllister along with MongoDB experts Sabina Friden and Frank Sun as they explore the powerful observability suite within MongoDB Atlas. Discover how these tools can help you optimize database performance, reduce costs, and ensure reliability for your applications. From customizable alerts and query insights to performance advisors and seamless integrations with enterprise tools like Datadog and Prometheus, this episode covers it all. Whether you're a developer, database administrator, or just getting started with MongoDB, learn how to leverage these observability tools to gain deep insights into your database operations and improve your application's efficiency. Tune in for a live demo showcasing how MongoDB's observability suite can transform your database management experience. Perfect for anyone looking to enhance their MongoDB skills and take their database performance to the next level.

This is the Engineering Culture Podcast, from the people behind InfoQ.com and the QCon conferences. In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Courtney Nash about her research on the unintended consequences of automation in software systems, the importance of learning from incidents and maintaining human expertise in complex systems. Read a transcript of this interview: https://bit.ly/4gY9ZjZ Subscribe to the Software Architects' Newsletter for your monthly guide to the essential news and experience from industry peers on emerging patterns and technologies: https://www.infoq.com/software-architects-newsletter Upcoming Events: QCon London (April 7-10, 2025) Discover new ideas and insights from senior practitioners driving change and innovation in software development. https://qconlondon.com/ InfoQ Dev Summit Boston (June 9-10, 2025) Actionable insights on today's critical dev priorities. devsummit.infoq.com/conference/boston2025 InfoQ Dev Summit Munich (October 15-16, 2025) Essential insights on critical software development priorities. https://devsummit.infoq.com/ QCon San Francisco 2025 (17-21, 2025) Get practical inspiration and best practices on emerging software trends directly from senior software developers at early adopter companies. https://qconsf.com/ InfoQ Dev Summit New York (Save the date - December 2025) https://devsummit.infoq.com/ The InfoQ Podcasts: Weekly inspiration to drive innovation and build great teams from senior software leaders. Listen to all our podcasts and read interview transcripts: - The InfoQ Podcast https://www.infoq.com/podcasts/ - Engineering Culture Podcast by InfoQ https://www.infoq.com/podcasts/#engineering_culture - Generally AI: https://www.infoq.com/generally-ai-podcast/ Follow InfoQ: - Mastodon: https://techhub.social/@infoq - Twitter: twitter.com/InfoQ - LinkedIn: www.linkedin.com/company/infoq - Facebook: bit.ly/2jmlyG8 - Instagram: @infoqdotcom - Youtube: www.youtube.com/infoq Write for InfoQ: Learn and share the changes and innovations in professional software development. - Join a community of experts. - Increase your visibility. - Grow your career. https://www.infoq.com/write-for-infoq

In today's fast-moving digital landscape, IT teams are under immense pressure to maintain performance, security, and reliability while managing increasingly complex cloud-native environments. But as traditional monitoring tools struggle to keep pace, AI-driven observability is emerging as a game-changer. In this episode, I sit down with Alois Reitbauer, Chief Technology Strategist at Dynatrace, to explore how AI and automation are redefining enterprise IT. Alois shares his insights on the role of predictive AI, AIOps, and automated observability in helping organizations proactively detect and resolve issues before they impact users. We also dive into how Dynatrace is integrating AI-powered solutions to enhance performance monitoring, security, and cloud automation, making IT operations more efficient and resilient. Alois breaks down the latest innovations, including how AI observability supports large-scale cloud environments, reduces alert fatigue, and enables self-healing IT ecosystems. As AI continues to transform enterprise technology, what does the future hold for IT teams? Can AI-powered observability help businesses scale without adding complexity? And how can companies harness Dynatrace's advanced AI insights to drive greater efficiency and security? Join us as we explore these questions and uncover the latest breakthroughs shaping the future of IT operations. I'd love to hear your thoughts—how do you see AI observability changing the way businesses manage their digital ecosystems?

What does the future of observability, AI, and security look like in an increasingly complex digital world? In this episode, I'm joined by Steve Tack, Chief Product Officer at Dynatrace, live from Dynatrace Perform in Las Vegas. Steve has been a frequent guest on the show, but this time, we're finally sitting down in person at one of the industry's most anticipated events. Steve shares insights into how Dynatrace is expanding its AI-driven observability and automation capabilities to help businesses move from a reactive to a proactive IT strategy. We discuss the company's latest product announcements, including advancements in AIOps, cloud security posture management, and predictive AI for optimizing enterprise performance. With AI dominating conversations in every industry, Steve explains how enterprises are evolving their IT operations to harness AI-powered automation while ensuring security and scalability. He also shares key trends from the conference floor, including how businesses are restructuring teams for agility and resilience in the era of cloud-native and AI-driven services. Tune in to hear how AI, observability, and security are converging to shape the future of enterprise IT—and what it means for your business. Are we truly on the verge of fully autonomous IT operations? Join the conversation and share your thoughts.