What metrics prove Consumer Groups and Rebalance is healthy in prod?

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Quick interview answer

Prove Consumer Groups and Rebalance is healthy with latency (p50/p95/p99), error/saturation rates, and queue/event-loop lag — not just CPU. Context: Baseline: Each partition consumed by one consumer in group. Rebalance on member join/leave — can cause duplicate processing if offsets not committed carefully.

Detailed answer

Production health signals for Consumer Groups and Rebalance: • Latency: p50/p95/p99 of the critical path that uses Consumer Groups and Rebalance. • Errors: failure rate, timeouts, and retry storms. • Saturation: queue depth, event-loop delay, thread/pool utilization. • Business SLIs: request success and user-visible freshness where relevant. Trade-off lens: Pros: Elastic scale-out; at-least-once default with offset commit. Cons: Rebalance pauses consumption; sticky assign reduces churn. Explain thresholds + alerts, then how you triage. Parent context: Baseline: Each partition consumed by one consumer in group. Rebalance on member join/leave — can cause duplicate processing if offsets not committed carefully.

Full explanation

Good answers name measurable signals and what “bad” looks like for Consumer Groups and Rebalance. Each partition consumed by one consumer in group. Rebalance on member join/leave — can cause duplicate processing if offsets not committed carefully.

Follow-up questions

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Parent context — Consumer Groups and Rebalance

Baseline: Each partition consumed by one consumer in group. Rebalance on member join/leave — can cause duplicate processing if offsets not committed carefully.

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