Search the library

If processing exceeds max.poll.interval.ms, the group may consider the member failed and reassign its partitions; a later commit from the old generation is rejected. Reduce records per poll, process with bounded workers while preserving partition ordering, pause/resume appropriately, or adjust the interval based on measured worst-case work. Keep the fix from merely delaying failure detection indefinitely.

A database transaction writes both the business state and an outbox row. A separate publisher retries delivery from that durable row. This avoids the gap where a database commit succeeds but broker publication fails. Delivery can still be repeated, so consumers should deduplicate by a stable event ID.

Kafka commits represent when the consumer believes work has been finished. If the offset is committed before the business effect is truly durable, a crash can lose data. If it is committed only after a delay, the application may re-process messages when the consumer restarts. The correct strategy is to commit only after the state change is stored successfully and the work is idempotent enough to recover from retries.

Python 3 map is lazy: it returns an iterator and evaluates each mapped value as the iterator advances. Convert it to a list only when you need materialized results or repeated traversal. Lazy evaluation saves memory but exceptions may occur later when a consumer iterates.

A consumer can request one item at a time, but callback-backed sources still need an explicit capacity and overflow policy. Tie early iterator exit and cancellation to resource cleanup.