PurePerformance

How many people have you met that implemented distributed tracing in the early 2000s? Make it one more after you have tuned into our latest podcast with William Louth. William, who can't seem to escape the observability space even though he keeps trying, has a track record in the space. He is an innovator and tool builder and is currently reimagining intelligent systems by shifting the focus from data collection to meaning-making. In our conversation we learn about situational awareness and how systems should use symbols to show their current state by also taking into account everything they are aware of happening in their ecosystem.This podcast episode has been long overdue and opens a fascinating new world beyond metrics, logs and traces!Links discussedWilliams LinkedIn: https://www.linkedin.com/in/william-david-louth/Humainary Research: https://humainary.io/research/Humainary GitHub: https://github.com/humainary-ioServentis Signs: https://raw.githubusercontent.com/humainary-io/substrates-api-java/refs/heads/main/ext/serventis/SIGNS.md

It started with the prompt: "Create an Uber Clone"! Several iterations and some months later Abhi presents his lessons learned when vibing a Ride Share Platform for RoboTaxis at Cloud Native Days Austria!"Commit to one tool and go deep. Don't get distracted by all the options you have. Treat your agent like a human! Get better in expressing what you really want!", those are the many lessons learned in Abhi's journey applying the potential of the latest AI agents that are available for software engineers.Tune into our latest episode and understand what Abhi means when he says: Context is important! Give it Macro Context and do Micro Incremental Improvements!Links we discussedAbhi's LinkedIn: https://www.linkedin.com/in/abhimanyuselvan/Cloud Native Austria Talk: https://www.youtube.com/watch?v=VjMPHWjawxM&list=PLtLBTEzR4SqU9GwgWiaDt10-yOVIN0nzM&index=9Cursor AI: https://cursor.com/OpenSpec: https://openspec.dev/

Chaos Engineering is the practice to introduced controlled failures into a system with the goal to improve the overall resiliency! What started with "lets see what happens when we unplug that server" to "lets simulate network latency issues" or "lets kill critical pods and see if the system recovers gracefully" is now seeing new experiments being conducted that are identified by a new companion: AI In this episode we have invited Bartek Pisulak, Dir of Cloud Quality Engineering at Pegasystems, who has been educating quality engineers on AI-Augmented Chaos Testing in Practice. Tune in and learn about the how AI can improve efficiency in the 5 critical phases of a chaos experiment: Steady State, Hypothesis, Run Experiment, Verify, Improve!To learn more about the foundational principles make sure to watch some of the conference talks from Bartek listed below:Links discussedBartek's LinkedIn: https://www.linkedin.com/in/bart%C5%82omiej-pisulak-82b94036/Talk at Cloud Native Days Austria: https://www.youtube.com/watch?v=xUVCKNpMEz8&list=PLtLBTEzR4SqU9GwgWiaDt10-yOVIN0nzM&index=10Talk at Porto Tech Hub: https://www.youtube.com/watch?v=-ZuEaA2PoToKraken: https://github.com/krkn-chaos/krknChasoEater: https://github.com/ntt-dkiku/chaos-eater

There is only one successful way to adopt new technology, and that is transformational! Sounds like a high-level consulting pitch but our industry has a track record to validate this statement. Just look at the recent web or cloud-native transformations!Pini Reznik has been helping organizations along the current AI-Native transformational journey. And what a timing: He just published his book on From Cloud Native to AI-Native where he provides a pragmatic approach to leveraging AI from Pioneering to Gradually Scaling!Tune in and hear from Pini why he thinks that AI projects are not failing because of bad AI, but because they approaching the problem the old and wrong way!And, stay until the end to hear how it was to write a book about AI using AI!Links we discussedPini's LinkedIn: https://www.linkedin.com/in/pinireznik/Link to Book: https://re-cinq.com/bookOur previous episode: https://www.spreaker.com/episode/ai-native-the-next-revolution-after-cloud-native-with-pini-reznik--67692567Prompt Engineering Conference Talk: https://www.youtube.com/watch?v=W7z5XMnvYt8

Don't get stuck using AI to build faster horses. Instead, find the opportunities and rethink your software delivery processes! That, and only that, will help you increase Developer Experience and Efficiency!This episode is all about how to measure and improve DevEx in the age of Artificial Intelligence. And with Laura Tacho, CTO at DX, we think we found a perfect guest!Laura has been working in the dev tooling space for the past 15 years. In her current role at DX she is working on the evolution of DORA and SPACE into DX Core 4 and the DXI Measurement Framework.In our episode we learn about those frameworks but also how tech leaders need to rethink where and how to apply AI to improve overall efficiency, quality and effectiveness! The key takeaways from this conversation areDevEx is all about the identifying and reducing friction in the end-2-end development processTech Leaders need to become better in articulating technical change requirements to businessAs of today only 22% of code in git is really AI generated. Don't get fooled into believing AI is already betterBack to Basics makes companies successful with AI. That is: proper CI/CD, testing, documentation, observability!Here the links we discussedLaura's LinkedIn: https://www.linkedin.com/in/lauratacho/DX: https://getdx.com/Cloud Native Days Austria Talk: https://www.youtube.com/watch?v=kZ1F0-XS1l4Engineering Leadership Community: https://www.engineeringleaders.io/

The AWS US-East problems on Oct 27th was a good reminder how depending we are on globally shared services. Built-in Resiliency is not guaranteed if systems have a hard dependency on a single region of a single vendor. Many of us have experienced systems being impacted that we use on a daily basis - some critical - some not so critical as Andi will tell you when he found out that is beloved Leberkas Pepi App didnt work!Besides this outage we discuss lessons learned from Cloud Native Days Austria, Observability and Platform Engineering Meetups in Gdansk and Tallinn as well as giving an outline to the upcoming Cloud and AI-Native US Tour from Henrik Rexed and Andi GrabnerAll the links we discussed are hereLeberkas Pepi: https://www.leberkaspepi.at/Cloud Native Austria: https://www.linkedin.com/company/cndaustria/Observability Meetup: https://www.meetup.com/observability-tech-community-meetup-group/US Tour from Henrik and Andi: https://events.dynatrace.com/noram-all-de-engineering-efficiency-tour-2025-28225/

Thomas Natschlaeger, Principal Data Scientist at Dynatrace, brings nearly 30 years of AI experience to the table. He shares fascinating insights into the historical milestones that made AI mainstream, emphasizing the importance of hardware and recent breakthroughs. The discussion dives into how LLMs can validate outputs, reducing hallucinations while boosting accuracy. Thomas also explores the trend towards specialized agents and the rethinking of roles within AI-native systems, making for a thought-provoking conversation on the future of technology.

Constanze Roedig, a key researcher at SBA Research, dives into the innovative concept of the Software Bill of Behaviors (SBoB). This approach provides a dynamic runtime behavior profile of software, enhancing cybersecurity practices. She explains the critical differences between static SBOMs and dynamic SBoBs, emphasizing the importance of real-time monitoring for detecting malicious behavior. Constanze also discusses how vendors can create their own SBoBs for better trust and security, while advocating for community engagement to strengthen this emerging framework.

Defining AI-Native in 2025 is like trying to define Cloud Native back in 2014! We are in the early stages of understanding what AI really means to us. The ecosystem is just evolving, and many organizations are still struggling with re-architecting their digital systems to cloud native patterns!To learn more about the current transformational wave—the AI-Native Wave—we have invited Pini Reznik, CEO and Co-Founder of re:cinq. We will discuss what we can learn from previous "waves of innovation," why the business must care, and why the primary AI use case should not be just cost-cutting! Make sure to get a copy of his book or catch his talk from Cloud Native Munich. All links we discussed here:Pini's LinkedIn: https://www.linkedin.com/in/pinireznik/The Next Transformation Mini Book: https://re-cinq.com/mini-bookCloud Native Munich Talk: https://www.youtube.com/watch?v=CHb3TLEV8ZU

Most AI projects still fail, are too costly, or don't provide the value they hoped to gain. The root cause is nothing new: it's non-optimized models or code that runs the logic behind your AI Apps. The solution is also not new: tuning the system based on insights from Observability!To learn more about the state of AI Observability, we invited back Nir Gazit, CEO and Co-Founder of traceloop, the company behind OpenLLMetry, the open source observability standard that is seeing exponential adoption growth!Tune in and learn how OpenLLMetry became such a successful open source project, which problems it solves, and what we can learn from other AI project implementations that successfully launched their AI Apps and AgentsLinks we discussedNir's LinkedIn: https://www.linkedin.com/in/nirga/OpenLLMetry: https://github.com/traceloop/openllmetryTraceloop Hub LLM Gateway: https://www.traceloop.com/docs/hub