Reject Unmeasured AI Reviews Before Latency Breaks Your Pipeline

说明与用途

通过监控队列年龄和令牌使用，安全地在 CI 流水线中使用免费 AI 审核，避免延迟和合并阻塞。

问题

Free AI review capacity can silently drain a token budget while queue latency grows, risking pipeline stalls.

结果

By gating on queue age and monitoring token usage, teams can safely experiment with free AI reviewers without risking pipeline latency.

工作流

• 1. Configure webhook to receive PR events and route to local MonkeyCode server. 2. Set queue parameters: max_age_seconds=1800, retry_limit=3, dead_letter_topic='reviews-dead', gate reject_on_queue_age=2700, block_merge=true. 3. Run synthetic PR load (50 PRs/hour) and record metrics every minute. 4. Monitor p95_queue_age_s, tokens_per_review, retry_rate, dead_letter_count. 5. If p95_queue_age_s exceeds 70% of reject threshold, alert. 6. Perform failure drill: pause new submissions, read queue age, drain with lower concurrency, switch to paid gateway. 7. Clean up: delete test queue, reset gate, verify with canary PR.

证据

Free model access and a free server option make experiments cheap. They also hide utilization until the bucket empties.

来源

If a review waits longer than 2700 seconds, the gate rejects the PR.

来源