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Python Queues: How At-Least-Once Delivery Impacts Reliability of Logistics User Reminders

Short answer: at-least-once delivery makes a reminder system safer against lost work, but it makes duplicate work an expected outcome. For a logistics worker pool, I treat the queue as a delivery attempt, not as proof that a notification was sent. The durable reminder record owns identity, the notification boundary enforces idempotency, and draining workers stop accepting new work before they…

At-least-once delivery in a logistics reminder system increases reliability by preventing lost work, but it also leads to duplicate attempts. The system treats the queue as an attempt, not confirmation of delivery. A durable reminder record owns the identity, while the notification boundary enforces idempotency. Workers stop accepting new work before finishing in-flight attempts to avoid duplicate notifications.

The decision favors a bounded increase in storage and coordination over duplicate SMS or email messages, keeping latency versus cost visible. Teams should be cautious of rate limits, spam filters, and OTP delivery gaps when implementing this system. The system maintains four invariants: a stable identity for scheduled reminders, repeatable delivery attempts, successful sends recorded before worker acknowledgments, and draining workers not accepting new messages after their stop deadline.

Failures can occur before acknowledgement, redelivery of delayed messages, acceptance of requests while clients timeout, or creation of duplicate logical reminders. To ensure safety, the queue message is not considered unique. The risk of duplicate work is high, while the risk of lost work is high if not handled correctly. The latency and cost trade-off is improved by acknowledging before sending.

The recommended approach is to send through an idempotency record, then acknowledge, with a bounded increase in storage and coordination. This approach has low failure rates, with one durable lookup and write per logical reminder.

Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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