Self-Healing Infrastructure with Agentic AI: From Monitoring to Autonomous Resolution

The Night I Stopped Being On-Call I've been on-call for production systems more times than I can count. You know the pattern: alert fires at 2 AM, you wake up, SSH into a server, run diagnostics, apply a fix, document it, and go back to bed knowing you'll be useless tomorrow. The fix itself? Usually something you've done a dozen times before — restart a service, clear a cache, adjust a configuration value. Here's what clicked for me recently: most production incidents aren't novel problems requiring human creativity. They're known failure modes that we've already solved, just manifesting in slightly different ways. And if that's true, why are humans still the ones resolving them at 2 AM? Over the past few months, I've been experimenting with something different: agentic AI that monitors infrastructure, detects anomalies, and applies fixes autonomously. Not just alerting me to problems — actually fixing them. Using tools like GitHub Copilot , Claude Code , and the Azure MCP server , I'v