Machine Learning Ops With Chelsea Troy

The software industry is experiencing another seismic shift. After decades of agile transformations, cloud migrations, and DevOps revolutions, we're now navigating the integration of AI into the software development lifecycle. But this time feels different—the pace is faster, the technology less mature, and the stakes feel higher. Matty Stratton sat down with Hannah Foxwell and Robert Werner to explore what this transformation means for developers, operations teams, and the organizations they serve.

Kat Cosgrove is back to talk about everyone’s favorite party topic: security. From container vulnerabilities to the chaos of patching, Matty and Kat dig into why “never not hot” feels like security’s permanent brand. Tune in for equal parts practical insight and DevOps-flavored sarcasm.

In this episode of Arrested DevOps, Matty and guest Kat Morgan discuss the ethical, practical, and technical implications of AI. They explore how AI can assist with coding, improve efficiency, and handle tasks, while emphasizing the importance of good practices and staying informed about the impact of AI.

Andrew Zigler (Mattermost) delves into the world of open-source development and the unique challenges faced by an "open-first" developer community. Andrew shares his deep insights into fostering collaboration, building trust, and navigating the intricate dynamics of open-source projects.

Jessitron is joined by Chelsea Troy, Staff Data Engineer at Mozilla, and one of the all-around most interesting people in software today, to discuss staff engineering, machine learning operations, and maybe also surfing.

It's been ten years of Arrested DevOps! Joe, Matty, Bridget, Jess, and Trevor spend some time (quite a lot of time!) reminiscing over stories and history of the podcast.

What happens when you suddenly are In Management? Matty is joined by Ben Greenberg to talk through the challenges of first-time management.

DevOps is not a department. It's a set of concepts and ideas that are human-centric and driven through Agile practices. It's applying Big A Agile to operations: fast feedback loops, deeper collaboration with stakeholders (which is the engineering team), and invoking people over process and tools. A current problem hamstringing organizations is that they treat DevOps like a commoditized department: one that writes shell scripts and deploys Jenkins servers, and not the value engine that those teams could be. They took the tools team, applied a light version of DevOps ideology, and said, "Hey, that's it. That's DevOps. Hashtag winning."

Most developers are familiar with two sources of data about their applications: 1) static code analysis, and 2) observability tools monitoring their system in production. However, a new data source is gaining popularity: Runtime analysis. Runtime analysis is a technique where an application's dynamic behavior is recorded and analyzed during development time, allowing flaws and other insights to be revealed before that code is deployed to production.

It's a complex world! Matty and Michael Stahnke wax philosophical about whether our systems need to be as complicated as we have made them