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Explains early and late acknowledgement without promising exactly-once task execution.
Tunes worker pools and reservation behavior to task shape instead of maximizing a single concurrency number.
Uses Django cache configuration to control freshness, namespace sharing, and safe cache migrations.
Separates single scheduler ownership from task-level overlap and idempotency controls.
Uses expected versions and conditional writes so delayed or retried Python tasks cannot commit stale decisions.
Reuses bounded redis-py pools for the application lifetime and closes async resources deliberately.
Keeps Celery messages small, safe to deserialize, and compatible across rolling deployments.
Combines selective Celery retries with bounded backoff, idempotent effects, and a terminal failure path.
Distinguishes fewer network round trips from atomic execution and chooses the smallest correct Redis primitive.
Chooses between small in-process follow-up work and durable, independently operated background execution.