Part II of two. See Part I for the recipe.
In Part I we've discussed how you can plug mirrord into your AI-SRE so it can autonomously test its fix in the real cluster. In this post, we'll show this running end-to-end on a real GKE cluster against HolmesGPT, the only OSS AI-SRE we found that is self-hostable. We planted two bugs to test both possible verdicts: PASS when the patched run clears the alert's SLO without any regressions, REJECT when it doesn't (the patched run still violates the alert's SLO, or cleared the SLO but added a regression).
Setup: HolmesGPT investigates an alert and returns a markdown report. A small Claude wrapper turns the report into a code patch. The verifier runs that patch under mirrord exec, compares against an unpatched baseline, and returns a verdict tied to the alert's actual SLO.
What's HolmesGPT? A prebuilt LLM-backed agent tailored for on-call work: it can run kubectl commands, fetch logs from the cluster, and read the runbooks you've already written (in Notion, Confluence, or markdown files) to ground its investigation. Without it, you'd be building this scaffolding around Claude yourself.
The demo cluster
