Operations | Monitoring | ITSM | DevOps | Cloud

"Show me all critical incidents from the last week." "Create an incident for the payment API being down." "What was the root cause of that database incident last Tuesday?" If you've ever wished you could just ask Claude (or any MCP client) to handle incident management tasks instead of context-switching between chat and your incident management dashboard, you're going to like what we built.

The Quest For The Five Minute Deploy Speed is everything at incident.io. The faster we can test and ship code, the faster we can get new products and features out to customers. Over the last three years, as our codebase grew and our test suite expanded, we drifted away from our own goals: "We aim for less than 5 minutes between merging a PR and getting it into production." This is the story of how we got back on track.

At incident.io, we are building a product that our users rely on 24/7, all year round. This means it is crucial that it is always working, and that is where our on-call rotation comes in. We believe that everyone should be on-call because it tightens the feedback loop between shipping new features and maintaining what we have, leading to more pragmatic engineering decisions.

Four months ago, Claude Code was announced and we were requesting invites to its "Research Preview." Now? We've gone from no Claude Code to simultaneously running four or five Claude agents, each working on different features in parallel. It sounds chaotic, but it's been a natural progression as we've learned to trust AI more and as the tools have dramatically improved.

Let’s start with the obvious: we’d like to have Anthropic as a customer. We greatly admire the work they are doing at the intersection of frontier models + safety. We use lots of different AI tooling at incident.io. We’re all-in at AI at incident.io, both to improve the productivity of our internal team and, more importantly, to provide our customers with superpowers in the form of an AI incident responder.

If you've been in earshot of tech leadership lately, you've probably heard the words 'EU,' 'AI,' and 'compliance' in conversation. The EU AI Act is officially upon us, and with it comes a whole new set of incident response and reporting requirements that might feel like a yet another bureaucratic set of requirements to worry about. But there's a different way to look at this legislation.

As much as you try to prevent it, your product will break sometimes. While you hope it would have the decency to do so while you are awake and already working, sometimes the product is inconsiderate and decides to break outside your office hours. Being woken up from a page at 3 am sucks, and being woken up again two hours later (when you get pinged for a follow-up issue you missed the first time) sucks even more.

Picture the scene: a high‑severity alert fires, Slack lights up, and dashboards scream red. You’re juggling Datadog, PagerDuty, Jira, and status pages while trying to coordinate fixes. The problem isn’t a lack of tools; it’s that they aren’t talking to each other. This guide explains why incident management tool integration matters, how it cuts response times, and where to start.

We're often asked: "How does incident.io help reduce alert noise?" And it’s a fair question. It’s typically much easier to add new alerts than to remove existing ones, which means most organizations slow-march into a world where noisy, un-actionable alerts completely overshadow the high-signal ones that indicate a real problem.

When an incident wakes your team early in the morning, the last thing you want is confusion about who’s responding or how help will arrive. An effective on-call schedule doesn’t just get the right person online. It helps them stay calm, confident, and capable of solving problems quickly. Done right, your on-call setup becomes a powerful lever for reducing Mean Time to Acknowledge (MTTA), Mean Time to Resolve (MTTR), and the overall stress that incidents place on your team.