AI SRE workflows, from alert to reviewed recovery

This solution connects existing specialist workflows; it is not a separate claim of an always-on autonomous operator. Confirm the exact agents and connections available in your private-beta scope.

Agree an evidence contract before the pilot. Each observation should identify its source, time range and affected environment. Keep the service timeline, recent changes, known ownership and runbook references together. Missing telemetry must remain visible rather than becoming an invented healthy state.

For an illustrative error spike, examine whether it affects successful and failed requests differently and whether other dependencies changed. A recent deployment is one hypothesis among others. Require the reviewer to distinguish confirmed facts, plausible explanations and tests that have not been performed.

A recovery proposal should name the affected service, preconditions, action scope, approver and verification steps. Check that its rollback or recovery path is valid for the starting state. A denied approval, unavailable runbook or missing permission should stop the proposed action and produce a clear handoff.

O2 AI's approval-gated model keeps production movement behind the configured human or policy gate. Confirm which operations can execute in your environment. Do not assume that describing a remediation option means the connector can perform it, or that execution alone proves service recovery.

Replay a sanitized incident in a controlled environment with the starting configuration preserved. Include a misleading change, a missing signal and a denied action. Inspect the resulting timeline, reviewer corrections and escalation behavior. This is a proposed evaluation method, not a completed OrbOps benchmark.

Record time to a useful hypothesis, unsupported conclusions, manual corrections and verification quality. Compare like-for-like workloads before making any MTTR claim. Keep the existing incident process and responder ownership in place throughout the pilot.