At-least-once delivery
At-least-once delivery is a messaging or processing guarantee that each message or record is delivered or processed one or more times, so duplicates may occur.
Kafka Streams in Action, Second Edition
At-least-once delivery is a processing guarantee that prevents loss of records but permits a record to be processed more than once.
- How it is used
- Uses Kafka producer retries and consumer offset commits to prevent record loss during failures.
- How deep it goes
- Explains producer and consumer failure paths, commit timing, and Java implementation, but stops short of duplicate-handling strategies.
- Examples
- Uses producer acknowledgment timeouts, consumer restarts, committed offsets, and process-then-commit Java code.
- What you can do after
- Diagnose/debug with it by identifying duplicate processing after failed commits and unsafe commits during asynchronous work.
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Akka in Action, Second Edition
At-least-once delivery is a processing guarantee in which records may be delivered or processed more than once because retries can repeat work.
- How it is used
- Uses committable Kafka sources and sinks to commit offsets only after records are processed, preventing message loss.
- How deep it goes
- Explains offset-carrying messages, batch commit settings, and draining shutdown through concrete stream pipelines.
- Examples
- Uses a Kafka test3-to-test4 forwarding stream and a failed A-to-B-to-C batch to illustrate duplicates.
- What you can do after
- Apply it via Akka Kafka to consume, transform, produce, and commit offsets in an at-least-once stream.
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C# Concurrency: Asynchronous and multithreaded programming
At-least-once delivery is a message-delivery guarantee that permits duplicates but ensures a message is delivered one or more times.
- How it is used
- Uses persistent queues to favor retaining important work over preventing duplicate processing after crashes.
- How deep it goes
- Explains removal timing, crash windows, delivery trade-offs, and poison-message loops without detailing queue-provider implementations.
- Examples
- Uses a mail merge, a lost confirmation, and a crash between processing and queue removal as concrete failure scenarios.
- What you can do after
- Operate persistent queues by selecting at-least-once delivery and planning monitoring for messages that repeatedly crash processing.
Apache Kafka in Action
At-least-once delivery is a message delivery guarantee that prevents message loss but permits duplicate delivery.
- How it is used
- Uses replicated acknowledgements to prioritize preventing message loss in Kafka applications.
- How deep it goes
- Explains configuration, acknowledgement loss, retries, and duplicates, then contrasts at-most-once and exactly-once guarantees.
- Examples
- Uses a lost-acknowledgement banking transaction and contrasts it with continuously produced temperature readings.
- What you can do after
- Operate/configure Kafka producers with acks=all and sufficient minimum in-sync replicas when duplicates are preferable to loss.
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Related concepts
- at-most-once deliverycontrasts with · At-most-once delivery is a messaging guarantee that each message is delivered no more than once, so messages may be lost but are not duplicated.
- message brokerproduced by · A message broker is intermediary software that receives, routes, and delivers messages between communicating producers and consumers.
- Consumer.committableSourceproduced by · Consumer.committableSource is an Alpakka Kafka source that emits records together with committable offset information for at-least-once processing.
- retryproduced by · A retry is a subsequent attempt to perform an operation after an earlier attempt fails or does not complete successfully.
- idempotencyaddresses · Idempotency is the property of an operation whereby repeating it has the same effective result or externally observable effect as performing it once.
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