Production monitoring lab
Mastery: ship checklist
A second person can reproduce inject 5% 500s for 10m → Alert AnswerErrorBurn fires; recovery clears within 15m from a clean checkout and name the owner for MON-TENANT-BLIND-9.
1Learn the idea
Read
Clean-room demo
From a fresh clone/directory, run the commands that prove inject 5% 500s for 10m → Alert AnswerErrorBurn fires; recovery clears within 15m. A second person plays SRE watching error budget during a model bump and follows your script without coaching. The demo includes limitations: what Prometheus+Grafana board for AI answer API golden signals still will not do.
Read
Evidence pack
Bundle: contract snippet, passing tests, metric snapshot for alert_precision on game-day ≥ 0.9 and scrape_up == 1, security negative probe, rollback note, owner name. Reference MON-TENANT-BLIND-9 as the drill you rehearsed. If any item is missing, the ship gate fails even if the happy path dazzles.
Read
Implementation artifact
./scripts/gameday_inject_errors.sh --rate 0.05 --minutes 10 --expect-alert AnswerErrorBurn
Read
Ownership and next review
For Production monitoring lab, name the human who gets paged, the review date for thresholds, and the condition that triggers reevaluation. Endpoint GET /metrics remains the production surface you operate for Prometheus+Grafana board for AI answer API golden signals — not a slide. Keep MON-TENANT-BLIND-9 in the handoff template so the next owner inherits the drill.
Read
Stage depth
After the peer demo, schedule the next threshold review date. File a short changelog that mentions MON-TENANT-BLIND-9 and the control that addresses it. Archive the evidence pack where your team already stores launch records. Resist rewriting everything “for real production” in one weekend — operate this slice until the metrics bore you, then widen. Final self-check: if telemetry vanished, would you still know to hold? If yes, you learned the operating posture this lane teaches.
Read
Field notes for `production-monitoring-lab` / `mastery-ship`
Trim the demo script until every command is necessary. Record a peer signature line: name, date UTC, pass/fail. File known limitations as bullets, not apologies. Link the evidence pack from the README. Schedule the next game day on a calendar, even if it is solo. Archive the branch tag or release digest you actually shipped. In this chapter the product is Prometheus+Grafana board for AI answer API golden signals, the human stakeholder is SRE watching error budget during a model bump, and the incident id you design against is MON-TENANT-BLIND-9. Re-state the oracle in your notes — inject 5% 500s for 10m → Alert AnswerErrorBurn fires; recovery clears within 15m — and keep the invariant visible: alerts require multi-window evidence; missing scrape ≠ healthy silence. Track alert_precision on game-day ≥ 0.9 and scrape_up == 1 as the scoreboard. Surface under change control: GET /metrics. If you only have forty minutes, finish the fixture for dashboard averages hide tenant Acme 40% error rate before polishing UI. Promotion language stays ternary: promote, hold, or roll back based on evidence, not hope.
Go deeper
Before you start
Why this matters
Draft a two-minute demo script that proves inject 5% 500s for 10m → Alert AnswerErrorBurn fires; recovery clears within 15m from a clean directory. Include the failure rehearsal for dashboard averages hide tenant Acme 40% error rate and the rollback/owner line. If the script needs tribal knowledge, the lab is not shipped.
In the wild
See how this idea shows up as a product and a company — then come back to the lesson. Skills transfer across vendors.
Related lessons
Check your understanding
Page assessment
Answer from memory. Completion is saved from this evidence, not from opening the next page.
All responses are required.