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At incident.io, we've spent the last two years building Investigations, our AI SRE. When you get paged, it starts investigating straight away, looking across your telemetry, recent deploys, past incidents, docs and code, and posts what it's found in your incident channel (or on your phone, if it's 2am and you're still deciding whether you need to get out of bed). By the time you open your laptop, you're starting at step six of triage rather than step one.

Most of what people mean when they ask "how does this actually work" comes down to three words used precisely: workflow, run, and gate. This is what each one is, and how they fit together.

You get a Slack message from the VP of Sales: They have asked an AI agent connected to Snowflake for the past quarter’s revenue and the numbers look wrong. First, you verify the agent’s query and, when that looks fine, check the pipelines that populate the underlying table. All jobs completed, the data is recently refreshed. Then it’s time to check the logs for errors. Nothing.

How on-demand Android environments turn validation into a repeatable pipeline stage In the first article, we looked at automation: how Android environments can be created and managed programmatically. In the second, we looked at scaling: how shared infrastructure can make those environments available to more developers, tests, and workloads. This third article looks at the next step: integrating those environments directly into CI/CD.

What happens when a software engineer who has put their entire identity into being the resident expert of an obscure technology or language with ten years of experience and who knows the codebase like the back of their hand now has to compete with AI? Psychologically speaking, according to Dr. Cat Hicks, author of The Psychology of Software Teams and founder of Catharsis, that's called identity threat, and it's a surefire way to feel unsafe. We were honored Dr.

It's been a while since I last updated you on what's new in OnlineOrNot. For the most part, I've continued making it useful for software teams: there's now an MCP server, I've improved the terraform provider significantly, and there's a new TypeScript SDK. You can also (finally?) monitor DNS/TCP with it.

Here’s everything you need to know about incident management.

TL;DR Have you ever set out to push an allegedly 15-minute fix that ended up taking multiple weeks, without even a guarantee that it would actually work? It’s happened to the best of us during our professional journeys, but this time, the story is about Apache Kafka.

Network changes often stall after the design is done. See how Megaport Advanced Services helps teams move from planning to implementation and support. Ask a network team where their last big network change got stuck and you’ll rarely hear “we couldn’t work out the design.” The completed design is usually sitting in a document somewhere, reviewed and signed off. What stalls is everything needed after that. Somebody has to write the runbook. Somebody has to sit in the 2 a.m.

Your AI coding agent can read your code, run your tests, and open a pull request. Until recently it could not see what that code does in production. MCP servers from monitoring vendors close that gap. Connect one, and Claude Code, Cursor, or Copilot can pull the error, the trace, and the slow query behind a bug report without you copying anything out of a dashboard. Most major monitoring vendors now offer an official MCP server. But they aren’t interchangeable. Some only expose errors.