Docs Connect Cookbooks Kafka Migrator Kafka Migrator With Kafka Migrator, you can move your workloads from any Kafka system to Redpanda using a single command. It lets you migrate Kafka messages, schemas, and ACLs quickly and efficiently. Redpanda Connect’s Kafka Migrator uses functionality from the following components: kafka_migrator input kafka_migrator output kafka_franz input kafka_migrator_offsets output schema_registry input schema_registry output For convenience, these components are bundled together into the following: kafka_migrator_bundle input kafka_migrator_bundle output This cookbook shows how to use the bundled components. Create the Docker containers First, you’ll need two clusters. To keep it simple, you can run the Bitnami Kafka and Schema Registry Docker containers for the source cluster and a Redpanda Docker container for the destination cluster via Docker Compose. docker-compose.yml services: source: image: bitnami/kafka environment: KAFKA_CFG_NODE_ID: 0 KAFKA_CFG_PROCESS_ROLES: controller,broker KAFKA_CFG_CONTROLLER_QUORUM_VOTERS: 0@localhost:9093 KAFKA_CFG_CONTROLLER_LISTENER_NAMES: CONTROLLER KAFKA_CFG_LISTENER_SECURITY_PROTOCOL_MAP: CONTROLLER:PLAINTEXT,PLAINTEXT:PLAINTEXT,PLAINTEXT_DOCKER:PLAINTEXT KAFKA_CFG_LISTENERS: PLAINTEXT://0.0.0.0:9092,PLAINTEXT_DOCKER://0.0.0.0:19092,CONTROLLER://:9093 KAFKA_CFG_ADVERTISED_LISTENERS: PLAINTEXT://localhost:9092,PLAINTEXT_DOCKER://source:19092 KAFKA_CFG_AUTHORIZER_CLASS_NAME: "org.apache.kafka.metadata.authorizer.StandardAuthorizer" KAFKA_CFG_SUPER_USERS: User:redpanda;User:ANONYMOUS ports: - 9092:9092 - 19092:19092 healthcheck: test: [ "CMD", "kafka-topics.sh", "--bootstrap-server=localhost:9092", "--list" ] start_period: 5s interval: 3s init_source: image: bitnami/kafka working_dir: /opt/bitnami/kafka/bin entrypoint: /bin/bash depends_on: source: condition: service_healthy command: > -c "kafka-topics.sh --bootstrap-server source:19092 --create --if-not-exists --topic foo --replication-factor=1 --partitions=2 && kafka-topics.sh --bootstrap-server source:19092 --create --if-not-exists --topic bar --replication-factor=1 --partitions=2 && echo 'Created topics:' && kafka-topics.sh --bootstrap-server source:19092 --list --exclude-internal && kafka-acls.sh --bootstrap-server source:19092 --add --allow-principal User:redpanda --operation Read --topic foo && kafka-acls.sh --bootstrap-server source:19092 --add --deny-principal User:redpanda --operation Read --topic bar echo 'Created ACLs:' && kafka-acls.sh --bootstrap-server source:19092 --list" source_schema_registry: image: bitnami/schema-registry environment: SCHEMA_REGISTRY_KAFKA_BROKERS: PLAINTEXT://source:19092 ports: - 8081:8081 depends_on: source: condition: service_healthy destination: image: redpandadata/redpanda command: - redpanda - start - --node-id 0 - --mode dev-container - --set rpk.additional_start_flags=[--reactor-backend=epoll] - --set redpanda.auto_create_topics_enabled=false - --kafka-addr 0.0.0.0:9093 - --advertise-kafka-addr localhost:9093 - --schema-registry-addr 0.0.0.0:8081 ports: - 8082:8081 - 9093:9093 - 9645:9644 docker-compose -f docker-compose.yml up --force-recreate -V This command uses an init container to create two topics, foo and bar, each with two partitions and an associated ACL. Create schemas When the demo clusters are up and running, use curl to create a schema for each topic in the source cluster. curl -X POST -H "Content-Type: application/vnd.schemaregistry.v1+json" --data '{"schema": "{\"name\": \"Foo\", \"type\": \"record\", \"fields\": [{\"name\": \"data\", \"type\": \"int\"}]}"}' http://localhost:8081/subjects/foo/versions curl -X POST -H "Content-Type: application/vnd.schemaregistry.v1+json" --data '{"schema": "{\"name\": \"Bar\", \"type\": \"record\", \"fields\": [{\"name\": \"data\", \"type\": \"int\"}]}"}' http://localhost:8081/subjects/bar/versions Generate messages Let’s simulate an application with a producer and consumer actively publishing and reading messages on the source cluster. You can use Redpanda Connect to generate some Avro-encoded messages and push them to the two topics from the source cluster. generate_data.yaml http: enabled: false input: sequence: inputs: - generate: mapping: | let msg = counter() root.data = $msg meta kafka_topic = match $msg % 2 { 0 => "foo" 1 => "bar" } interval: 1s count: 0 batch_size: 1 processors: - schema_registry_encode: url: "http://localhost:8081" subject: ${! metadata("kafka_topic") } avro_raw_json: true output: kafka_franz: seed_brokers: [ "localhost:9092" ] topic: ${! @kafka_topic } partitioner: manual partition: ${! random_int(min:0, max:1) } Now, run this command to start the pipeline, and leave it running: redpanda-connect run generate_data.yaml Next, add a Redpanda Connect consumer, which reads messages from the source cluster topics, and leave it running. This consumer uses the foobar consumer group, which will be reused in a later step when consuming from the destination cluster. read_data_source.yaml http: enabled: false input: kafka_franz: seed_brokers: [ "localhost:9092" ] topics: - '^[^_]' # Skip topics which start with `_` regexp_topics: true start_from_oldest: true consumer_group: foobar processors: - schema_registry_decode: url: "http://localhost:8081" avro_raw_json: true output: stdout: {} processors: - mapping: | root = this.merge({"count": counter(), "topic": @kafka_topic, "partition": @kafka_partition}) Launch the source consumer pipeline, and leave it running: redpanda-connect run read_data_source.yaml At this point, the source cluster should have some data in both foo and bar topics, and the consumer should print the messages it reads from these topics to stdout. Configure and start Kafka Migrator You’re ready to start the new Kafka Migrator Bundle, which will do the following: On startup, it reads all the schemas from the source cluster Schema Registry through the REST API and pushes them to the destination cluster Schema Registry using the same API. It needs to preserve the schema IDs, so the destination cluster must not have any schemas in it. Once the schemas have been imported, Kafka Migrator begins the migration of all the selected topics from the source cluster, and any associated ACLs. After it finishes creating all the topics and ACLs that don’t exist in the destination cluster, it begins the migration of messages and performs consumer group offsets remapping. If any new topics are created in the source cluster while Kafka Migrator is running, they are only migrated to the destination cluster if messages are written to them. ACL migration for topics adheres to the following principles: ALLOW WRITE ACLs for topics are not migrated ALLOW ALL ACLs for topics are downgraded to ALLOW READ Group ACLs are not migrated Changing topic configurations, such as partition count, isn’t currently supported. Now, use the following Kafka Migrator Bundle configuration. See the kafka_migrator_bundle input and kafka_migrator_bundle output docs for details. The max_in_flight: 1 setting is required to preserve message ordering at the partition level. See the kafka_migrator output documentation for more details. kafka_migrator_bundle.yaml input: kafka_migrator_bundle: kafka_migrator: seed_brokers: [ "localhost:9092" ] topics: - '^[^_]' # Skip internal topics which start with `_` regexp_topics: true consumer_group: migrator_bundle start_from_oldest: true schema_registry: url: http://localhost:8081 include_deleted: true subject_filter: "" output: kafka_migrator_bundle: kafka_migrator: seed_brokers: [ "localhost:9093" ] max_in_flight: 1 schema_registry: url: http://localhost:8082 metrics: prometheus: {} mapping: | meta label = if this == "input_kafka_migrator_lag" { "source" } Launch the Kafka Migrator Bundle pipeline, and leave it running: redpanda-connect run kafka_migrator_bundle.yaml Check the status of migrated topics You can use the Redpanda rpk CLI tool to check which topics and ACLs have been migrated to the destination cluster. You can quickly install rpk if you don’t already have it. For now, users need to be migrated manually. However, this step is not required for the current demo. Similarly, roles are specific to Redpanda and, for now, will also require manual migration if the source cluster is based on Redpanda. rpk -X brokers=localhost:9093 topic list NAME PARTITIONS REPLICAS _schemas 1 1 bar 2 1 foo 2 1 rpk -X brokers=localhost:9093 security acl list PRINCIPAL HOST RESOURCE-TYPE RESOURCE-NAME RESOURCE-PATTERN-TYPE OPERATION PERMISSION ERROR User:redpanda * TOPIC bar LITERAL READ DENY User:redpanda * TOPIC foo LITERAL READ ALLOW Check metrics to monitor progress Redpanda Connect provides a comprehensive suite of metrics in various formats, such as Prometheus, which you can use to monitor its performance in your observability stack. Besides the standard Redpanda Connect metrics, the kafka_migrator input also emits an input_kafka_migrator_lag metric for monitoring the migration progress of each topic and partition. curl http://localhost:4195/metrics ... # HELP input_kafka_migrator_lag Benthos Gauge metric # TYPE input_kafka_migrator_lag gauge input_kafka_migrator_lag{label="source",partition="0",path="root.input.sequence.broker.inputs.0",topic="__consumer_offsets"} 0 input_kafka_migrator_lag{label="source",partition="0",path="root.input.sequence.broker.inputs.0",topic="bar"} 0 input_kafka_migrator_lag{label="source",partition="0",path="root.input.sequence.broker.inputs.0",topic="foo"} 0 input_kafka_migrator_lag{label="source",partition="1",path="root.input.sequence.broker.inputs.0",topic="__consumer_offsets"} 0 input_kafka_migrator_lag{label="source",partition="1",path="root.input.sequence.broker.inputs.0",topic="bar"} 1 input_kafka_migrator_lag{label="source",partition="1",path="root.input.sequence.broker.inputs.0",topic="foo"} 0 ... Read from the migrated topics Stop the read_data_source.yaml consumer you started earlier and, afterwards, start a similar consumer for the destination cluster. Before starting the consumer up on the destination cluster, make sure you give the migrator bundle some time to replicate the translated offset. read_data_destination.yaml http: enabled: false input: kafka_franz: seed_brokers: [ "localhost:9093" ] topics: - '^[^_]' # Skip topics which start with `_` regexp_topics: true start_from_oldest: true consumer_group: foobar processors: - schema_registry_decode: url: "http://localhost:8082" avro_raw_json: true output: stdout: {} processors: - mapping: | root = this.merge({"count": counter(), "topic": @kafka_topic, "partition": @kafka_partition}) Now launch the destination consumer pipeline, and leave it running: redpanda-connect run read_data_destination.yaml It’s worth clarifying that the source cluster consumer uses the same foobar consumer group. As you can see, this consumer resumes reading messages from where the source consumer left off. And you’re all done! Due to the mechanics of the Kafka protocol, Kafka Migrator needs to perform offset remapping when migrating consumer group offsets to the destination cluster. While more sophisticated approaches are possible, Redpanda chose to use a simple timestamp-based approach. So, for each migrated offset, the destination cluster is queried to find the latest offset before the received offset timestamp. Kafka Migrator then writes this offset as the destination consumer group offset for the corresponding topic and partition pair. Although the timestamp-based approach doesn’t guarantee exactly-once delivery, it minimises the likelihood of message duplication and avoids the need for complex and error-prone offset remapping logic. The content from this cookbook was first introduced on the Redpanda Blog. 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