POLARIS

Engineering · Problem brief

Production Incidents Are Rising

DIRECT ANSWERNormalize incidents by traffic, services and production changes, then link each incident to detection, affected dependency, recent change, mitigation and recurrence. Separate more exposure from worse reliability. Prioritize one repeated failure path and test a small prevention or containment control without slowing every release indiscriminately.

Updated September 28, 2026Diagnosis · Evidence · First proof

Start with these five checks.

Ask for only what can change the answer.

Test one reversible move.

Choose one recurring incident class with a supported technical path. Add one reversible control—targeted test, canary, circuit breaker or alert change—to the affected service. Compare recurrence, detection, recovery and delivery delay; remove the control if noise or lead-time cost exceeds its prevention value.

A decision your team can use.

Common questions.

Does a higher incident count mean reliability worsened?

Not always. Better detection, more services or more traffic can raise counts; normalize exposure and severity.

Should more approvals be added?

Only if evidence shows the approval would catch the failure. Broad gates can slow recovery without preventing incidents.

What should a first test target?

A frequent, measurable and reversible failure path with clear operational ownership.

Authoritative references.

  1. DORA, Software delivery performance metrics
  2. Google, Site Reliability Engineering book
  3. CISA, Secure by Design

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