Operations | Monitoring | ITSM | DevOps | Cloud

If you’ve been using Icinga 2 for a while, you probably know the built-in checks cover a lot of ground: disk space, CPU, memory, ping. But sooner or later you’ll run into something specific to your setup that no existing plugin handles. That’s where writing your own plugin comes in. The good news? It’s simpler than it sounds. Icinga 2 doesn’t care what language your plugin is written in. It just runs the script, reads the exit code, and displays the output. That’s it.

Last week, we launched a major update to Canvas, our investigation workspace. The new Canvas has evolved from an AI co-pilot you chat with to a place where your whole team, human and agent, can work the same problem on the same surface. Auto-investigations begin the moment a trigger, SLO, or anomaly fires. Custom skills encode your team's runbooks so every agent investigates with your team's expertise built in.

Your logs know too much. Every debug statement, every traced request, every APM span can carry the risk of capturing something they shouldn't. A customer email. A JWT token. A credit card number. An API key that was never meant to leave your payment service. It doesn't look like a breach. There's no alert. Your observability platform just quietly accumulates sensitive data like indexed, replicated, and accessible to every engineer with log query access.

Without experiment infrastructure to help you test your LLM applications, every research session starts with the same questions: What have we tried previously? What were the numbers? Which prompt version produced that result? Why did we discard that approach? The answers live in scattered notes, terminal history, and half-remembered conversations. Each handoff between sessions loses context. In practice, iteration can slow down as teams get bogged down in testing and analysis.

Alert fatigue and blind spots develop together. Monitoring stacks that generate noise while missing critical issues may have incomplete coverage or poorly configured alerts. As they grow reactively and without structured coverage assessment, both issues worsen. Teams will often add monitors when something breaks and tune thresholds when alerts become unbearable, but rarely audit their overall setup to see if it works.

On May 18, 2026, organizations using Microsoft Fabric experienced a multi-hour outage that disrupted analytics workloads, reporting systems, and access to platform services across several regions. StatusGator detected the developing incident at 14:00 UTC using Early Warning Signals, 37 minutes before Microsoft officially acknowledged the outage at 14:37 UTC.