Batch API lab

Mastery: ship checklist

Batch API lab is production work only when one frozen failure can be reproduced, one measurable gate can stop a release, and one operator can safely reverse it.

~14 minMastery check

Before you start

Why this matters

Read this incident aloud: a provider partially completes a batch, retries callbacks, and returns results out of input order. In two minutes, write the earliest deterministic check that should fail, the telemetry signal you would inspect, and the action that must not happen automatically. Compare your answer with this chapter's boundary: batch payloads exclude restricted documents; signed result URLs expire and workers have write access only to the staging index.

1Learn the idea

Read

Ship with evidence and rollback controls

Shipping is a decision backed by artifacts, not the moment a command succeeds. The candidate release must show a clean fixture run, aggregate successful unique chunks per dollar meeting at least 99.5% completion, zero duplicate vectors, and reconciliation within 30 minutes, a security regression run, telemetry from a staging probe, and a named rollback target. Record model, prompt or policy, data, fixture, and price versions so the evidence can be reproduced after dependencies change.

Use a canary or shadow path when live behavior can differ from fixtures. Compare the candidate with the baseline on identical slices. Promotion should be automatic only for reversible, low-risk changes; security boundary changes and outbound actions need human approval. Define rollback triggers before rollout. A dashboard turning red is not enough—write the exact query, evaluation window, minimum sample, and command or alias swap that restores service.

After promotion, watch the short-term burn rate and the slow quality signal. Verify that embedding_batch_completion_ratio receives candidate traffic, traces resolve, logs are redacted, and budget limits work. Close the release by linking evidence and assigning follow-up owners. If an incident occurs, reconcile by custom_id, retry only failed items, verify the staging index, then atomically swap its alias. The lesson is mastered when another engineer can operate the system from the repository and runbook without oral history.

For mastery, assemble the release evidence and rehearse rollback. A teammate should be able to answer “what changed, what passed, what will page us, and how do we undo it?” from committed artifacts.

Read

Focused implementation artifact

release: candidate
baseline: stable
gates:
  primary_metric: "successful unique chunks per dollar"
  required: "at least 99.5% completion, zero duplicate vectors, and reconciliation within 30 minutes"
  security_regression: pass
  staging_probe: pass
  telemetry_signal: "embedding_batch_completion_ratio"
rollout:
  canary_percent: 5
  rollback_on: "critical failure or sustained SLO breach"
owner: on-call-ai-platform

Read

Rehearse promotion and rollback

Assemble a release record containing candidate and baseline versions, fixture hash, policy and model versions, evaluation report, security result, staging probe trace, budget result, owner, and rollback target. Re-run the known regression a retried completion webhook inserts the same chunk twice and silently increases index size from a clean checkout or equivalent isolated environment. The evidence must show successful unique chunks per dollar satisfies at least 99.5% completion, zero duplicate vectors, and reconciliation within 30 minutes without suppressing failed slices.

Send a canary or shadow request and follow its trace from entry to final decision. Confirm embedding_batch_completion_ratio receives candidate traffic, redaction remains effective, and the alert points to an actionable runbook. State the rollback trigger with metric, threshold, window, and minimum sample. Then rehearse rollback using a fake alias, feature flag, or action adapter and prove the stable version resumes service.

Promotion requires a named approver for irreversible actions or authority changes. After release, watch fast reliability signals and slower quality/cost signals for the declared period. If the gate or live SLO fails, reconcile by custom_id, retry only failed items, verify the staging index, then atomically swap its alias. Close only when another engineer can reproduce the evidence and execute rollback without oral instructions.

Checking tutor…

Continue learning · glossary & guides

Can the release evidence be reproduced independently?
Are promotion and rollback criteria executable?
Do canary telemetry, ownership, and post-release checks work?
Local references: Glossary: embedding batch · Glossary: batching · Snippet: batch embed pattern
Previous