Show Notes
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.
More from Arrested DevOps
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.