Operations | Monitoring | ITSM | DevOps | Cloud

An effective post-mortem can turn a security breach into a blueprint for lasting resilience. But too often, in the stress of an incident, documenting what happened takes a back seat to containment and recovery. The resulting analysis relies heavily on memory, scattered notes, and competing narratives. Valuable context gets lost, timelines blur, and lessons that could strengthen defenses never become institutional knowledge.

Infrastructure resilience is essential for any modern IT environment. Downtime is expensive. Beyond the stresses of day-to-day operations, you want to be confident that your IT systems will continue functioning during service disruptions, hardware failures, or natural disasters. Agentic ITOps can help ensure a reliable, resilient IT infrastructure environment. These systems use agentic AI to help IT teams minimize downtime, improve customer trust, and protect your business’s revenue and reputation.

Atlassian is shutting down OpsGenie. New sales stopped on June 4, 2025, and the platform will be completely offline by April 5, 2027. As an OpsGenie user, you now face a critical decision: Migrate to Jira Service Management (JSM), Atlassian’s recommended path, or choose a different solution. And if you’re not sure JSM is the right fit for your team’s alerting needs, this review will help you decide. I signed up for JSM and put it through real-world testing.

Over the last few months IncidentHub has added several new features to make it easier to fine tune your alerts. IncidentHub now also integrates with Microsoft Teams and supports custom domains for your public status pages. Let's take a comprehensive look at what's new.

At 2:07 a.m., one of the core production nodes went down. CPU usage spiked, latency shot through the roof, and requests began timing out across the cluster. Monitoring tools lit up instantly. Datadog dashboards turned red, Prometheus fired alerts, and a webhook pushed incident payloads into Jira. Everything worked exactly as designed. Except no one responded. The alert chain fired flawlessly through machines, but the right human never saw it because it was sent via an automated phone call.

Last week, I ordered a pizza on a food delivery app. And they promised the delivery in 30 minutes. Similarly, all digital services: Apps, websites, cloud platforms, etc, make promises about speed, uptime, and reliability. The difference is how they track and measure those promises. That’s where SLA, SLO, and SLI come in. These three metrics define what “reliable” actually means. They turn a vague claim like “99.9% uptime” into something you can measure, track, and act on.

ilert’s engineering team has developed an open Model Context Protocol (MCP) server that enables AI assistants to securely interact with your alerting and incident management workflows, from determining who is on call to creating incidents. In this article, we provide a simple explanation of MCP, outline the reasons behind our investment in it, describe the high-level architecture, and explain how to connect Claude, Cursor, and other MCP clients to ilert today.