PurePerformance

Todd DeCapua has been a performance evangelist for many years. In his recent work and publications, which includes Effective Performance Engineering ( http://www.effectiveperformanceengineering.com/ ) as well as several publications on outlets such as TechBeacon ( https://techbeacon.com/contributors/todd-decapua ), he introduces DevOps best practices to improve the 5 S-Dimensions: Speed, Stability, Scalability, Security and Savings.In our discussion with Todd we focused a lot on Security as it has been a more prominent topic in our industry recently. How to bake Security into the delivery pipeline and why it is such an important aspect. Automation seems to be the key which also includes automating functional checks, performance checks and – as we said: Security!Related Links:Follow Todd on Twitter ( https://twitter.com/AppPerfEng )Follow Todd on LinkedIn ( http://www.linkedin.com/in/todddecapua )Blog: How to build performance into your user stories ( https://techbeacon.com/how-build-performance-your-user-stories )

For our one year anniversary episode, we go “back to basics”, or, better said, “back problem patterns”.We picked three patterns that have come up frequently in recent “Share Your PurePath” sessions from our global user base and try to give some advice on how to identify, analyze and mitigate them:· Bad Multi-threading: Multi-threading is not a bad thing – but if done wrong it doesn’t allow your application to scale. We discuss key server metrics and how to correctly read multi-threaded asynchronous PurePaths. Also see the following blog: https://www.dynatrace.com/blog/how-to-analyze-problems-in-multi-threaded-applications/ · When Micro Service become Nano Services. This was inspired by a blog from Steven Ledoux ( https://www.dynatrace.com/blog/micro-services-when-micro-becomes-nano/ ). It's important to keep a constant eye on your micro-service architecture to avoid too tightly coupled or too fine grained architectures· Garbage Collection Impact: GC is important but bad memory management and heavy GC can potentially impact your critical transactions. We discuss different approaches on how to correctly measure the impact of garbage collection suspension. If you want to learn more check out the Java Memory Management secton of our online performance book: https://www.dynatrace.com/resources/ebooks/javabook/impact-of-garbage-collection-on-performance/

In this second episode with Goranka Bjedov from Facebook, we learn details about how Facebook monitors their infrastructure, services, applications and end users. Why they built certain tooling, and how & who analyzes that data. We then shifted gears to development where we learned how the onboarding process of developers works and that Goranka herself made her first production deployment within the first week of employment. Join us and learn a lot about the culture that drives Facebook Engineering

Goranka Bjedov ( https://www.linkedin.com/in/goranka-bjedov-5969a6/ ) has an eye over the performance of thousands of servers spread across the data centers of Facebook. Her infrastructure supports applications such as Facebook Social Network, WhatsApp, Instagram and Messenger. We wanted to learn from her how to manage performance in such scale, how Facebook engineers bring new ideas to the market and what role performance and monitoring plays.

In the second episode with Rick Boyd (check out his GitHub repo - https://github.com/DJRickyB ) we talk about how performance engineering evolved over time – especially in an agile and DevOps setting. It’s about how to evolve your traditional performance testing towards injecting performance engineering into your organizational DNA, providing performance engineering as a service. Making it easy accessible to developers whenever they need performance feedback. Rick gives us insights on how he is currently transforming performance engineering at IBM Watson. We also gave a couple of shout outs to Mark Tomlinson and his take on Performance in a DevOps world!

We got Rick Boyd ( https://www.linkedin.com/in/richardjboyd/ ) – Application Performance Engineer at IBM Watson – and elaborated what Continuous Performance Testing is all about. We all concluded its about Faster Feedback in the development cycle back to the developers – integrated into your delivery pipeline. As compared to delivering performance feedback only at the end of a release cycle. We discussed different approaches on how to “shift left performance” with the benefit of continuous performance feedback!

Brett Hofer (@brett_solarch) has been engaged in numerous DevOps Transformation projects mainly for very large enterprises. We got to talk with him on this episode to learn more about how he assesses the status quo when he walks into an organization, what the top blocking items for a successful transformation are and what the best approaches are to implement the recommended changes. Spoiler alert: we talked a lot about IT Ops Automation, building cross functional teams and understanding and defining responsibilities and roles. If you want to learn more about what Brett is doing check out his blogs about DevOps on https://www.dynatrace.com/blog/author/brett-hofer/.

Thomas McGonagle just had his 10 years DevOps anniversary at it was 10 years ago when he got first exposed to Infrastructure as Code through Puppet. He is currently working with F5, helping Big IP Network Teams around the world automate the Network as part of their DevOps transformation.We met Tom at a recent DevOps meetup in Boston which sparked this conversation on what “Metrics Driven Continuous Delivery” could mean for Network Operations Engineers. What are the metrics to look at? How to engage with the application teams to provision better and automated network resources? How to bake this into the Continues Delivery Cycle?Besides NetOps Thomas is also passionate about CI/CD. He runs the largest Jenkins User Group in the World out of Boston, MA. If you happen to be around check out their next meetups and DoJo’s: https://www.meetup.com/Boston-Jenkins-Area-Meetup/

Mike Horwitz (https://www.linkedin.com/in/mike-horwitz-a40a139 ) has been working with Mainframe since the mid 80s. In this podcast he explains basic terminology and the challenges that come with the interaction to the distributed and cloud native world. Monitoring end-to-end is a critical capability especially when it comes to cost savings and including the mainframe components in a CI/CD/DevOps environment.If you want to learn more about common mainframe performance and monitoring challenges check out our YouTube Performance Clinic: https://www.youtube.com/watch?v=8eodOw3gnMA&list=PLqt2rd0eew1bmDn54E2_M2uvbhm_WxY_6&index=55

INFO COMMENTSWe take time out chat with Jason Suss and Dynatrace RUM on RUM, we search for Richard Bentley at the nightclub, Vikram survived the performance puzzlers, Rick Boyd from IBM Watson and Stefan Baumgartner tells us all about his work at Dynatrace and podcasting at http://workingdraft.de