Keep systems running while AI handles the repetitive parts.
Get the Site Reliability Engineer briefIn 2026, AI is changing day-to-day SRE work by summarizing incidents in real time, correlating logs and traces during outages, and drafting postmortems before the on-call engineer finishes their coffee. It now writes first-pass Terraform and Kubernetes manifests, suggests alert threshold changes from historical data, and explains unfamiliar stack traces. The result is less time spent on toil and more time on capacity planning and reliability design.
Paste these into Claude or ChatGPT and replace the bracketed parts with your own details.
Write a blameless postmortem from these notes: [incident timeline, impact, root cause, remediation]. Include sections for summary, impact, timeline, root cause, what went well, and action items with owners.Here is an alert definition and 30 days of firing history: [alert config and stats]. Tell me if this alert is too sensitive, suggest a better threshold or window, and explain the tradeoff.Create a step-by-step runbook for responding to [failure scenario] on [service/stack]. Include detection steps, immediate mitigations, rollback procedure, and escalation criteria.Review this Terraform for reliability and security issues: [code]. Flag missing health checks, single points of failure, and resources without retry or timeout settings.Explain this error and give three likely root causes ranked by probability, plus the command or query I should run to confirm each: [stack trace or log excerpt].One AI tool, one prompt, and one trick for Site Reliability Engineers, every weekday morning. Free.