DevOps Speakeasy Podcast

In this episode we talked with Thomas Andolf is a developer with a passion in understanding how things work, some of Thomas special skills are security in code, authentication/authorization, automation of processes and development in high transaction environments.

In this episode we talked with David Ahlbeck, an enthusiastic and innovative software developer with 25+ years of experience. He has worked in networking, online gaming and the automotive industry.

In this episode we talked with Dylan Beattie a consultant, software developer and international keynote speaker. He’s the director of Ursatile, an independent consultancy based in London that specialises in helping organisations bridge the knowledge gap between software development and business strategy.

Valarie Regas spoke to us about how opening up, showing vulnerability, and using inclusive language help write better software and be better people.

In this episode, Heather VanCura, Chair of the JCP, spoke to us about how we can make sure Java retains its dominance as the programming language of choice and what Oracle is doing to attract and retain the next generation of developers.

In this episode, Roberto Cotrez of RedHat tells us about what's new in Quarkus 2.0 and shares details about the developer conference he organizes in Portugal (spoiler: #DevOpsSpeakeasy will be there!)

Emily Jiang speaks about IBM's implementation of JakartaEE's Microprofile, OpenLiberty, and her book on the subject.

Ken Kousen shares the news on his new book on Mockito, the mocking framework, mocking in general, and his life as an author.

In this episode Alex and Mykyta of Netflix Engineering explained why debugging GRPC might be hard, whom to ask and where to look when you have the need (spoiler: RTFM), and what are the differences between HTTP 2 and HTTP 3. Special appearances by a promising next-generation developer (maybe?) and Glory to Ukraine.

Eric Wendelin, head of analytics at Gradle explains how AI models in Gradle Enterprise can reduce your build time by only running the tests worth running based on prediction models developed at Meta.