One bad Kafka record shouldn't crash a Flink Stateful Functions job

What was broken

In Apache Stateful Functions, the routable Kafka ingress had no policy for malformed records. A record with a null key (there's no function instance to route to) threw inside the deserializer. A tombstone (null value, normal on compacted topics) blew up as a bare NullPointerException from deep inside protobuf - no topic, no offset, no hint which record did it.

Either way the whole Flink job died - every ingress, every topic, every function, not just the pipeline that read the record. And it looped: the poison record's offset is never committed, so each restart re-reads it and dies again until the job parks at terminal FAILED.

A Flink job runs many pipelines together and fails as a unit, so one producer bug on one topic takes down all of them - order tracking, notifications, billing - not just the pipeline that read the record.

What ships in 3.4.0-KZM-3.5

StateFun Actors 3.4.0-KZM-3.5 adds invalidRecordHandling to io.statefun.kafka.v1/ingress:

kind: io.statefun.kafka.v1/ingress
spec:
  id: example/orders
  address: kafka.svc:9092
  invalidRecordHandling:
    type: skip              # default when omitted
    logLevel: warn          # debug | info | warn | error
  topics:
    - topic: example.orders
      valueType: example/Order
      targets:
        - example/order-handler
    - topic: payments.commands
      valueType: example/PaymentCommand
      invalidRecordHandling:
        type: fail          # per-topic override: strict contract here
      targets:
        - example/payment-handler

type: skip - the new default. The invalid record is dropped and the job keeps running. Nothing is silently lost:

• one log line per skipped record, with full coordinates:
  

  Skipping invalid record: defect [NULL_KEY], topic [orders], partition [0], offset [42], timestamp [1690000000123], key [null], value size [17]
  

• counters on the source operator: numInvalidRecordsSkipped (total) and topic.<topic>.defect.<NULL_KEY|NULL_VALUE>.numInvalidRecordsSkipped - with the Prometheus reporter, topic and defect arrive as labels, so the alert names the misbehaving producer and the kind of corruption directly. Ready-made rules: Alerting guide.

type: fail - the strict contract. The job still halts on the first invalid record - right for ledgers and payment commands, where a processing gap is worse than downtime - but the exception now carries the full record coordinates, tombstones included. No more forensic hunt.

Flexibility

• Policy per ingress (default for all its topics) with a wholesale per-topic override - one ingress can run lenient telemetry topics next to a strict billing topic.
• Skip log level per ingress or per topic: debug | info | warn (default) | error.
• Deliberately no rate limiting on skip logs: when a producer misbehaves, "which records exactly?" must be answerable from the log. Alerting load belongs to the labeled counters.

Upgrading

• Behavioral break: the default flips from crash-the-job to skip-with-log+metric. If your team alerts on job restarts as the bad-data signal, move that alert to numInvalidRecordsSkipped - or pin type: fail to keep the old behavior.
• Custom KafkaIngressDeserializer implementations: a null return now skips the record (the long-documented javadoc contract is finally enforced) instead of crashing the job.
• Coordinates: Maven io.github.kzmlabs.flinkstatefun:*:3.4.0-KZM-3.5, image ghcr.io/kzmlabs/flink-statefun:3.4.0-KZM-3.5.

What's next

type: forward - delivering invalid records to a dead-letter function with provenance metadata (topic, partition, offset, defect) so pipelines can quarantine or replay them - is designed in ADR-0008 and is the next stage.

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Docs: Kafka I/O - invalid records · Metrics · Alerting. Repo: github.com/kzmlabs/flink-statefun - StateFun Actors is the maintained fork of Apache Stateful Functions on Flink 2.2 / Java 21 (why we forked).