Watch an AI agent detect a live application failure, investigate the root cause across logs, metrics, and source code, and remediate it — all without human intervention.
It doesn't just alert you. It investigates, reasons, and acts.
The SRE Agent correlates Application Insights telemetry, Azure Monitor metrics, and deployment history to pinpoint root cause — in seconds, not hours.
Learn more →Connected to your GitHub repo, the agent traces failures back to the exact source code path using Deep Context — not just "something is 503-ing."
Learn more →Start in Review mode (propose & approve). Graduate to Autonomous for trusted patterns. You control the blast radius.
Learn more →Built-in: Azure Monitor, App Insights, Log Analytics. Plus Teams, Outlook, PagerDuty, ServiceNow, Kusto, and any API via MCP.
Learn more →Every investigation teaches the agent. It remembers root causes, resolution steps, and team patterns — institutional knowledge that never walks out the door.
Learn more →One-click GitHub Actions workflows break and restore checkout on demand. Run the demo as many times as you need — same story every time.
Learn more →Six steps from healthy to broken to automatically recovered.
The webstore is running. Customers browse, add to cart, check out. Telemetry flows to Application Insights.
One-click workflow sets DEMO_BROKEN_CHECKOUT=true. The checkout API returns 503 while the rest of the site stays up.
Azure SRE Agent sees the spike in 503 errors. It queries App Insights, examines traces, and correlates with recent changes.
The agent traces the failure to the DEMO_BROKEN_CHECKOUT flag in the source code. It forms a hypothesis and validates it with evidence.
In Review mode: proposes resetting the env var. In Autonomous mode: executes the fix immediately.
Checkout returns to 201. App Insights confirms the fix. The agent saves the investigation to memory for next time.
Follow the demo script for a step-by-step walkthrough with speaker notes.