How does Consumer Groups and Rebalance change at 10× traffic?

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Quick interview answer

At 10× traffic, Consumer Groups and Rebalance usually hits queueing and CPU/I/O saturation first — mitigate with concurrency limits, batching, caching, and offloading. 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

At 10× traffic for Consumer Groups and Rebalance: 1) Bottleneck shifts from “works on my laptop” to queue delay and resource saturation. 2) Protect the loop/path: timeouts, bulkheads, backpressure, worker offload for CPU work. 3) Scale out carefully: sticky vs stateless, connection pools, cache hit ratio. 4) Prove with load tests that p99 stays inside SLO. Example to cite: 6 partitions, 3 consumers → each gets 2 partitions; add 4th consumer triggers rebalance. 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

Focus on what breaks first and how you keep Consumer Groups and Rebalance correct under load. 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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