Scenario 01.1.2 · acks=1: leader-only ack

Kafka producer acks=1: acknowledged by the leader only

Producers & EOS · Intermediate · about 2 min · Apache Kafka 4.3

The producer is acked as soon as the leader appends - without waiting for the followers. Faster than acks=all; the record isn’t replicated yet.

What you start with

With acks=1 the producer is acknowledged the instant the leader writes the record to its own log, without waiting for the followers to replicate it. A deliberately slow replica fetch makes the gap visible: O1 is acked with LEO 1 while the high watermark still sits at 0, then advances once the followers catch up.

Step by step

1. Idle · producer ready (acks=1) t+0.000s Three replicas, a producer configured acks=1. Open at this step: step 1, Idle · producer ready (acks=1)
2. Acked on the leader · followers not caught up t+0.900s With acks=1 the producer is acknowledged (‘ok’) the moment the LEADER appends O1 - LEO is 1 but the high watermark is still 0 because the followers haven't fetched yet. acks=1 does not wait for replication. Open at this step: step 2, Acked on the leader · followers not caught up
3. Followers caught up · HW advances t+1.500s The followers replicated O1 and the high watermark advanced to 1. acks=1 didn't wait for this step - faster than acks=all, but if the leader had died first, O1 could have been lost (see acks=1 durability gap). Open at this step: step 3, Followers caught up · HW advances

The takeaway

acks=1 trades a window of durability for latency: at ack time the record lives only on the leader, so the high watermark (and any consumer) trails until the followers replicate it.

Configs in this scenario

• acks How many replicas must have a write before the producer counts it as sent: 0 (none), 1 (the leader only) or all (every in-sync replica, the default, and required for idempotence). How acks works

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Further reading

Apache Kafka documentation

More in Producers & EOS

• Kafka producer acks=0: fire and forget, silent data loss
• Kafka acks=0 vs acks=1 vs acks=all on a degraded ISR
• Kafka acks=1 data loss: min.insync.replicas does not help
• Kafka linger.ms vs batch.size: when the producer sends
• Kafka producer partitioners: keyed, round-robin and sticky
• Kafka compression.type: fewer, larger producer batches
• Kafka buffer.memory and max.block.ms: producer backpressure
• Kafka idempotent producer: retrying NOT_ENOUGH_REPLICAS
• Kafka enable.idempotence=false: a retry writes a duplicate
• Kafka idempotent producer dedup vs a plain producer
• Kafka max.in.flight.requests.per.connection and ordering

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