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Financial Services / PaymentsConsultingCloud / Kubernetes

Kafka-compatible is not the same as identical — test the clients before you cut over

GP
Global Payments Processor

Overview

Redpanda speaks the Kafka protocol without ZooKeeper or a JVM, which removes a significant operational burden. The migration is usually straightforward, but the parts that are not — older client libraries, admin tooling, and Kafka-internal assumptions in existing code — are worth finding in a test harness rather than in production.

Challenge

Every producer and consumer in the estate is a compatibility question. Older client library versions negotiate protocol features differently, admin tooling may depend on JMX metrics or ZooKeeper paths that no longer exist, and Kafka Connect workers, Streams applications, and monitoring agents each have their own expectations. Broker-side configuration does not map one-to-one, and consumer group offsets must be carried across so no message is reprocessed or skipped.

Environment

Apache Kafka clusters on Kubernetes or VMs with mixed client languages and versions, Schema Registry, Kafka Connect, and existing ACLs, migrating to Redpanda.

Approach

AceMQ inventories every client by library and version, then exercises each one against a Redpanda cluster in a test harness covering the protocol features it actually uses — transactions, idempotent produce, consumer group protocol, and admin operations. Topics migrate in waves using MirrorMaker or Redpanda's migration tooling with offset translation, dual-consuming until each consumer is validated.

Solution

  • Client inventory by language, library, and version, with a compatibility test matrix per protocol feature in use
  • Test-harness validation of transactions, idempotent produce, consumer group rebalancing, and admin API calls against Redpanda
  • Broker configuration translation, including partition, retention, and compaction settings that do not map one-to-one
  • ACL and Schema Registry migration with authentication mechanism verification per client
  • Topic-by-topic replication with consumer group offset translation and dual-consume validation before cutover
  • Monitoring and alerting rebuilt against Redpanda's metrics, replacing JMX-based Kafka dashboards

Outcome

Customers cut over topic by topic with client compatibility verified in advance, and retire the ZooKeeper or KRaft operational layer along with the JVM tuning that went with it. Compatibility issues surface in the test harness rather than during a production cutover.

Technologies

RedpandaApache KafkaKubernetesApache Flink

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