With the growing demand for multi-tenancy, geo-replication, and separation of compute and storage, many organizations are exploring a migration from Apache Kafka to Apache Pulsar. While Pulsar offers architectural advantages — including built-in multi-tenancy and better scaling — migration from an established Kafka setup involves careful planning and execution.

This guide outlines the challenges, compatibility concerns, and strategic approaches required to transition smoothly from Kafka to Pulsar without disrupting production systems.

Why Migrate from Kafka to Pulsar?

Organizations consider migrating due to:

  • Decoupled architecture (compute vs. storage)
  • Built-in multi-tenancy and RBAC
  • Geo-replication support out-of-the-box
  • Tiered storage for cost-effective long-term retention
  • Native support for stream + queue models

However, Kafka has a mature ecosystem. Migrating away requires ensuring feature parity, data continuity, and minimal downtime.

Key Migration Challenges

1. Topic and Partition Mapping

Kafka topics are partitioned log files; Pulsar topics are partitioned at the namespace level.

  • Challenge: Kafka’s topic partition layout may not map directly to Pulsar
  • Strategy: Match Kafka partition counts using Pulsar’s numPartitions config
2. Data Format Compatibility

Kafka messages may be in Avro, JSON, or Protobuf with Kafka-specific schemas.

  • Challenge: Pulsar uses its own schema registry
  • Strategy: Use schema translation tools or flatten messages during migration
3. Consumer Semantics

Kafka consumers rely on offset tracking; Pulsar uses cursor positions.

  • Challenge: Aligning offset-based tracking with Pulsar cursors
  • Strategy: Use Kafka-on-Pulsar (KoP) for compatibility during transition
4. Ordering Guarantees

Kafka provides partition-level ordering; Pulsar supports this with Key_Shared subscription.

  • Challenge: Matching ordering guarantees for critical consumers
  • Strategy: Use Key_Shared or ensure consistent hashing in producer key assignment
5. Rewriting Clients and APIs

Kafka APIs differ from Pulsar APIs.

  • Challenge: Client migration can be time-intensive
  • Strategy: Use KoP or Pulsar Kafka Wrapper for step-by-step migration

Migration Strategies

Strategy 1: Kafka-on-Pulsar (KoP) for Incremental Migration

KoP is a Pulsar protocol handler that allows Kafka clients to interact with Pulsar brokers as if they were Kafka brokers.

  • Kafka clients work without modification
  • Enables hybrid deployments
  • Ideal for brownfield migrations
bin/pulsar-daemon start protocol-handler kafka
# Then configure listeners on port 9092
Strategy 2: Dual Writes (Kafka → Pulsar)

Write to both Kafka and Pulsar during a cutover period.

  • Allows testing Pulsar consumers without disrupting Kafka
  • Ensures data consistency validation
  • Eventually, cut off Kafka ingestion

Tools:

  • Kafka Connect → Pulsar Sink
  • MirrorMaker → Pulsar Sink Connectors
Strategy 3: Mirror Kafka Topics to Pulsar

Use connectors to mirror Kafka topics to Pulsar:

  • Pulsar IO Kafka source
  • Kafka Connect Pulsar Sink

Sample config for Kafka → Pulsar:

{
"tenant": "public",
"namespace": "default",
"topicName": "mirrored-topic",
"kafkaConsumerConfigs": {
"bootstrap.servers": "kafka-broker:9092",
"group.id": "kafka-mirror-group"
}
}
Strategy 4: Full Cutover (Lift-and-Shift)

Move entire producer/consumer applications to Pulsar APIs and infrastructure.

  • High risk, but clean migration
  • Use when Kafka is no longer required
  • Requires significant refactoring

Testing and Validation

Before go-live:

  • Validate message volume, latency, and ordering
  • Compare message lag, throughput, and error rates
  • Use end-to-end checksum tagging for data consistency
  • Monitor using Prometheus, Grafana, or Pulsar Manager

Operational Considerations

  • Set up topic partitions and namespaces equivalent to Kafka layout
  • Apply appropriate retention, TTL, and compaction policies
  • Use TLS and token-based authentication for secure migration
  • Implement alerts for lag, failures, and broker overload

Best Practices

  • Start with non-critical topics to test migration flow
  • Run in dual-write mode until consumer reliability is verified
  • Use schema validation tools to ensure cross-system compatibility
  • Enable debug logging in consumers to trace mismatches or delays
  • Document offset-to-cursor mapping for rollback purposes

Conclusion

Migrating from Kafka to Pulsar is a strategic shift that unlocks modern capabilities like tiered storage, native multi-tenancy, and protocol unification. However, success depends on thoughtful planning, hybrid strategies like KoP or dual writes, and robust testing.

By understanding the architectural differences and using tools like Pulsar IO connectors, Kafka-on-Pulsar, and schema translators, teams can minimize risk and move confidently toward a more scalable and flexible event streaming infrastructure.