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Jacquie Capur, a senior developer advocate at Nebius, joins Matty to talk about keeping meaningful control over the tools you depend on: knowing what they're tied to, verifying they do the job, and having a realistic way out. The conversation runs from configuration management's first magic moment to data residency rules in healthcare, tools that change every two weeks, and the case for open models.

Marino Wijay joins Matty to ask the question everyone in tech is quietly panicking about: what the hell is actually going on right now. They dig into the pace of change since the zero interest rate era, the collapse of infrastructure roles into a human-plus-AI layer, and why most of what looks like a bubble is really just an accounting hack that goes back decades.

Naga Sujitha Vummaneni and Sundeep Bobba join Matty to talk about their book, which reframes CI/CD pipelines as control systems: actuators, feedback signals, and constraints. They dig into what that model demands once AI agents start shipping code at machine speed, and why a bypassed control is a design signal, not a compliance failure.

Doug Pagnutti spent fifteen years as an automation engineer caught between the IT and OT worlds inside manufacturing plants. The friction sounds a lot like what's been happening in DevOps for over a decade. Matty and Doug dig into why industrial operations never got the memo, and what OT and IT could still learn from each other now that the wall between them is collapsing.

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 returns to talk with Matty about why security stays in the news, why most CVEs never get fixed, and which tools belong in every production environment. The conversation ends on burnout and the case for touching grass.

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 of Mattermost and Matty talk about what makes an open-first developer community hard to run: the echo chamber, the pull of the paid staff, what can stay closed, and how to get more people advocating than just the ones with the title.

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

Grant Fritchey returns after almost ten years to talk about databases and DevOps, and why treating the database like code is still the most useful message.