Instrument metrics and rollout decisions

Instrument containerized answer API releasing image v2 at 5%→25%→100% weights so release commander watching revision-sliced error rate can answer: demand, errors, latency/age, saturation. Emit fields needed by canary_weight, error_rate_by_revision, grounded_rate_by_revision with bounded labels. Sample successful high-volume traces; keep errors and rollout transitions denser within policy.

Define at least one alert that would fire for CANARY-PROMOTE-BLIND-6, with a for/pending window that survives deploy blips. Missing scrape or missing revision labels must not look like health. Include a trace/log example id format you will actually search.

Add a unit/integration check that metrics increment on the happy path and on the automation promotes while scrape_up{revision=v2}==0 branch. Store machine-readable output in CI artifacts when practical.

Cardinality discipline: tenant and revision are usually enough; raw question text is not a label. Exemplars or trace links beat screenshots alone when debugging CANARY-PROMOTE-BLIND-6. Define who owns alert fatigue review. If you export to a vendor, record retention and access. Synthetic probes should use non-sensitive fixtures and still exercise POST /answer. Practice the query you will type at 2am once, while calm.

Document the exact PromQL or log query in the runbook stub for this service. Verify histograms have buckets around your SLO target. Add a canary synthetic check that exercises the oracle path every few minutes in staging. Confirm that PII redaction happens before export. Track build/version as a label on the golden signals. Delete noisy debug logs before they become accidental product dependencies. In this chapter the product is containerized answer API releasing image v2 at 5%→25%→100% weights, the human stakeholder is release commander watching revision-sliced error rate, and the incident id you design against is CANARY-PROMOTE-BLIND-6. Re-state the oracle in your notes — 5% canary healthy 20m → promote to 25%; guardrail breach → weight 0 in < 2m — and keep the invariant visible: promote only if canary error_rate ≤ baseline+0.5pp and groundedness ≥ baseline−1pp for two 10m windows. Track canary_weight, error_rate_by_revision, grounded_rate_by_revision as the scoreboard. Surface under change control: POST /answer. If you only have forty minutes, finish the fixture for automation promotes while scrape_up{revision=v2}==0 before polishing UI. Promotion language stays ternary: promote, hold, or roll back based on evidence, not hope.

Set a timer for twelve minutes and attempt only the observability concerns for Canary deploy lab. Speak aloud what release commander watching revision-sliced error rate would see on success versus on automation promotes while scrape_up{revision=v2}==0. Write three bullet artifacts you must keep: a fixture name tied to CANARY-PROMOTE-BLIND-6, a metric query for canary_weight, error_rate_by_revision, grounded_rate_by_revision, and the rollback or refuse command for POST /answer. Then extend the notes with one sentence on how promote only if canary error_rate ≤ baseline+0.5pp and groundedness ≥ baseline−1pp for two 10m windows would be violated if you skipped this page. Close by restating the oracle in your own words without looking: 5% canary healthy 20m → promote to 25%; guardrail breach → weight 0 in < 2m.