When agents can change production
Define the action, contain its scope, and verify what changed at the destination.
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Define the action, contain its scope, and verify what changed at the destination.
Use instrumentation and context propagation to connect the evidence in an investigation.
When inference slows without obvious application errors, test physical constraints alongside queueing, workload changes, and software regressions.
Test evidence retrieval, long-session consistency, tool boundaries, and cost before letting a model influence production changes.
Connect on-call interruptions, specialist demand, and recovery work to a concrete capacity decision using an on-call workload worksheet.
Turn reliability policy into a release decision with fresh evidence, limited exceptions, and a clear path to resuming normal changes.
Read validated architectures as a starting point for workload, recovery, and support testing, not a promise of automatic reliability.
Connect an SLO’s allowance to planning and release behavior, with explicit ownership, exceptions, and treatment of measurement gaps.
Adapt a complete SLO record, worked budget examples, and an exception log without confusing bad requests with minutes of downtime.
Measure a representative workload, identify the limiting resource, and test one reversible change instead of applying a universal sysctl recipe.
Compare detection, correlation, investigation, and automation using your incidents, review costs, and failure paths.
Decide which alerts earn an interruption using urgency, reachable authority, coverage evidence, and a practical alert acceptance record.