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Turns a production-only role and payload failure into the smallest durable API regression test.
Checks health, authentication, and one critical read flow after deployment without creating persistent business data.
Compares rollback, roll-forward, feature kill switches, scaling, and degraded mode as incident mitigations.
Explains what belongs in runbooks, how on-call handoff preserves context, and how operational docs stay useful.
Explains health checks that prove an API can serve traffic without becoming fragile dependency probes.
Chooses safe cached, partial, pending, read-only, or unavailable behavior and makes degraded state explicit to clients and operators.
Explains initial incident triage: confirm impact, mitigate, assign roles, preserve evidence, and communicate.
Explains how to triage post-release 500 errors using deployment correlation, logs, traces, feature flags, and rollback safety.
Explains how to diagnose 401/403 spikes across token validation, identity provider issues, clock skew, deployment changes, and abuse.
Uses per-dependency concurrency limits, queues, pools, and workload partitions to stop one failing path from exhausting the whole API.
Classifies retryable outcomes and applies bounded attempts, exponential backoff, jitter, deadlines, and idempotency.
Sets bounded timeout and deadline policies across callers, APIs, databases, and external services without hiding unknown outcomes.
Explains how to diagnose and mitigate a downstream dependency slowing the API through timeouts, retries, and degraded behavior.
Explains how to investigate queue age, backlog, worker health, poison messages, dependency failures, and safe catch-up.
Explains post-incident review, root cause, contributing factors, action items, tests, alerts, runbooks, and ownership.
Explains closed, open, and half-open behavior, failure classification, recovery probes, and the limits of circuit breakers.
Explains saturation signals and how systems shed, queue, throttle, or degrade before cascading failure.