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A reliable Kafka backup is more than copying broker files or relying on replication inside one cluster. Use an independent export when you need an archive, a continuously replicated target cluster when you need rapid recovery or migration, and a separate capture of configuration, security, schemas, connector state, and consumer positions. MirrorMaker 2 (MM2) is the usual foundation for a live cluster move; Kafka Connect is the practical path for exporting records to files or external systems. Plan the work as a controlled replication and cutover project, then prove it with a restore drill.
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What a Kafka backup must protect
Kafka stores records on multiple brokers, but those copies share the cluster’s failure domain. A broker outage, accidental deletion, bad deployment, credential compromise, or regional incident can affect every replica. In-cluster replication therefore improves availability; it is not an independent backup.
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A recovery set has several layers:
- Records: the messages, keys, headers, timestamps, tombstones, and ordering within each partition.
- Topic behavior: partition counts, replication factors, retention, cleanup policy, compaction, and other topic-level settings.
- Consumers: group identities and the positions from which applications should resume.
- Security: ACLs, principals, quotas, listener and client settings, and the credentials or certificates needed to reconnect.
- Integration state: connector definitions and the configuration, offset, and status stores used by Kafka Connect.
- Application dependencies: schema definitions, serialization settings, external databases, and any state that is not stored in Kafka.
Cross-cluster replication and exported records solve different problems. A replicated cluster is designed for a quicker failover or migration, while an independent export gives you a copy outside the source cluster’s operational boundary. Many organizations use both.
Choose the copy method for the recovery job
| Method | Best use | What it copies | Main limits |
|---|---|---|---|
| Kafka Connect source and sink | Export or import to files, databases, object storage, or another system | Records transformed by the connector’s serialization | Connector semantics, schemas, offsets, and exactly-once behavior depend on the connector. The official file example demonstrates a pipeline; it is not a complete disaster-recovery system. |
| Legacy MirrorMaker | Basic source-to-target topic replication | Records and keys | Destination offsets differ from source offsets. Apache Kafka documents it as unsuitable for transparent failover and not a replacement for in-cluster replication. |
| MirrorMaker 2 | Migration, disaster recovery, geographic replication, and hybrid-cloud moves | Topics, topic configurations, consumer groups and offsets, ACLs, partitioning, and newly discovered topics and partitions | Replication flows, naming, security, offset translation, and cutover require deliberate design and validation. |
| Managed Kafka replication | Moving to a provider-operated Kafka service | Provider-specific replication and migration state | Pricing, quotas, feature compatibility, regional availability, and partner terms vary and must be verified for the chosen service. |
Use Connect when the destination is a file or a non-Kafka system. Use MM2 when the destination must remain a Kafka cluster that can take over with minimal application change. Combining them gives you a hot migration target plus an independent archive.
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Set recovery objectives before copying anything
Write down a recovery-point objective (RPO), recovery-time objective (RTO), acceptable cutover downtime, and retention period for each service. The Kafka documentation does not provide universal RPO, RTO, throughput, downtime, or data-volume figures; those values depend on your traffic, connector, network, retention, and operational process.
Separate objectives by workload. A game matchmaking stream, billing topic, and telemetry topic may have different tolerances for lost records, replay, or downtime. Record who owns each objective and how it will be tested. A target that replicates successfully but cannot restore the required consumer position or credentials does not meet the objective.
Inventory the source cluster
Before provisioning a destination, create a dated inventory that another operator can use during an incident. Include:
- Kafka and broker versions, deployment mode (KRaft or ZooKeeper), listeners, security protocols, and client authentication.
- Every topic, its partition count, replication factor, retention and compaction settings, cleanup policy, and approximate traffic.
- Producer applications, consumer applications, consumer groups, group ownership, and expected restart behavior.
- ACLs, principals, quotas, bootstrap-server settings, certificates, and network routes or firewall rules.
- Schema definitions and registry settings, including the serialization used by each producer and consumer.
- Kafka Connect workers, connector configurations, external destinations, and whether workers run in distributed or standalone mode.
- External databases, object stores, caches, and application state that Kafka records alone cannot recreate.
Capture the inventory in version control or another controlled store. Do not assume that a topic’s existence implies that its configuration, security rules, or application dependencies will be recreated automatically.
Capture configuration, security, and connector state
Export topic configurations and ACLs separately from the records. Preserve quotas, client bootstrap settings, schema definitions, connector configurations, and the identities required to authenticate. MM2 can replicate topic configurations, consumer groups and offsets, and ACLs, but you still need a documented target-side security and networking plan.
Kafka Connect’s internal state is part of the backup:
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- In standalone mode, source offsets are kept in a local file. Protect that file with the same care as the exported records, or a connector may restart from an unintended position.
Transactional records, compacted topics, tombstones, schemas, and external databases may need procedures beyond a generic record copy. Confirm that the selected connector or replication path preserves the semantics your applications rely on.
Export and import records with Kafka Connect
How the official file example works
Kafka Connect is designed to ingest data from external systems into Kafka and to write Kafka data back to external systems. The Apache Kafka quickstart demonstrates two connectors: a file source connector reads lines from a file and produces records to a topic; a file sink connector consumes topic records and writes them to a file.
- Prepare a Connect worker in standalone or distributed mode and secure its access to the source or destination topic.
- Configure a source connector for the external input, including its file path or system endpoint and the key and value converters that define serialization.
- Run the connector and verify that records arrive in the expected topic, retaining the keys, timestamps, headers, and tombstones your application needs.
- For import, configure a sink or source in the opposite direction, then test a small, identifiable dataset before processing the full archive.
- Record the connector configuration and its offset and status stores so the job can resume or be rebuilt consistently.
The file connectors are demonstrations, not a turnkey disaster-recovery design. A production pipeline to a database, object store, or another Kafka cluster inherits that connector’s delivery guarantees, error handling, schema behavior, and offset semantics. Exactly-once behavior is not automatic; verify what the specific connector and converter support.
When Connect is the right choice
- Choose it for an independent archive that must live outside Kafka.
- Choose it when the destination is a database, object store, or a different event platform.
- Choose it when records must be transformed during export or import and that transformation is intentional and documented.
Do not treat a line-oriented file as a faithful representation of every Kafka feature without testing. Binary values, headers, schemas, transactions, tombstones, and compaction behavior can be lost or changed by serialization and connector settings.
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Replicate a cluster with MirrorMaker
Why legacy MirrorMaker is limited
Legacy MirrorMaker reads records from source topics and writes them to same-named topics in the destination cluster. Keys and records are copied, but source and destination offsets are different. An application that stores an offset from the source cannot blindly seek to that number on the destination. Apache Kafka therefore describes legacy mirroring as neither a substitute for in-cluster replication nor a transparent failover mechanism.
It can still serve a simple, one-way topic-copy use case when consumers are restarted according to a separately defined replay policy. If you need consumer groups and their positions to follow the data, use MM2 and validate the translated positions.
What MirrorMaker 2 adds
MM2 can replicate topics and their configurations, consumer groups and offsets, ACLs, partitioning, and topics or partitions discovered after replication starts. That makes it suitable for a continuously synchronized migration target, a disaster-recovery cluster, geographic replication, or a hybrid-cloud move.
Design the replication flow before enabling it. Decide which cluster is the source, which is the destination, how topics are named, which direction is allowed, which principals can read and write, and how offset translation will be checked. Bidirectional or active-active arrangements require especially careful loop prevention, ownership, and conflict handling.
Provision the destination cluster
Create the target only after the inventory and recovery objectives are approved. Match compatible Kafka protocol, security, and serialization settings. Establish network connectivity and target principals before replication begins. Pre-create topics when exact partition counts, replication factors, retention, or compaction settings matter; otherwise, confirm that the replication process creates them with the intended values.
For a managed service, include provider limits, quotas, regional placement, supported Kafka versions, connector availability, and migration-state reporting in the design review. Managed Kafka services can simplify operations, but their commercial terms and feature compatibility are provider-specific and change over time.
Migration runbook: replicate, validate, and cut over
- Define objectives. Set RPO, RTO, retention, and permitted cutover downtime for each workload.
- Inventory the source. Record versions, KRaft or ZooKeeper mode, topics, partitions, replication factors, policies, clients, groups, ACLs, quotas, schemas, connectors, and external sinks.
- Select the copy path. Use Connect for file or external-system export, MM2 for a continuously replicated Kafka target, or both when you need a hot target and an independent archive.
- Capture metadata and security. Store topic configurations, ACLs, quotas, client bootstrap settings, schema definitions, connector configurations, and Connect internal state.
- Provision the target. Build compatible networking and security, then create or verify topics and their policies.
- Start replication. Enable the MM2 flow or Connect connectors and monitor replication lag, errors, missing topics, partition counts, ACL propagation, and consumer-offset translation.
- Validate before switching traffic. Compare topic inventories, configurations, partition counts, record counts or checksums where practical, timestamps, keys, headers, tombstones, compacted-topic behavior, ACLs, and consumer restart positions.
- Coordinate the cutover. Quiesce or coordinate producers, allow replication to drain, record the cutover point, update client bootstrap servers and schema or configuration references, and resume traffic on the target.
- Keep rollback capacity. Leave the source available or read-only for the agreed rollback window. Watch for duplicates, gaps, authentication failures, and consumers that resume at an incorrect position.
- Run a restore drill. Rehearse recovery with records, metadata, security, connectors, schemas, and applications. Measure the result against the objectives before decommissioning the source.
Validate data and application behavior
Record-level checks
- Compare topic and partition inventories on both sides.
- Use record counts or checksums where they are meaningful for the workload, and sample timestamps, keys, headers, values, and tombstones.
- Exercise compacted topics with updates and deletes; verify that the destination’s cleanup policy produces the expected final state.
- Test serialization and schema compatibility with real producers and consumers, not just an administrative listing.
Operational checks
- Confirm ACLs, principals, quotas, listeners, certificates, and network routes.
- Restart representative consumer groups and verify that MM2-translated positions produce the intended replay or continuation behavior.
- Stop and resume a connector to confirm that its stored offsets and status recover as designed.
- Measure replication lag and error handling during normal traffic and a deliberately interrupted network connection.
Document every discrepancy. A migration is not complete when the destination contains messages; it is complete when the applications can authenticate, deserialize, consume, produce, and recover according to the agreed objectives.
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The destination has records but consumers replay or skip data
This usually reflects offset differences between clusters or an offset-translation problem. Do not copy a numeric source offset directly to the destination. Use MM2’s consumer-group and offset replication where appropriate, then test a real consumer restart and define how duplicates or intentional replay are handled.
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Replication may have created a topic without the retention, compaction, partition, or replication settings your workload requires. Compare configurations explicitly, pre-create critical topics, and correct the target before cutover.
Connect resumes from an unexpected point
Check whether the connector runs in distributed mode, where offsets live in Kafka topics, or standalone mode, where source offsets live in a local file. Restore the correct internal state and configuration together; rebuilding only the connector definition can change its starting position.
Records arrive but applications cannot use them
Investigate converters, schema definitions, headers, transactional records, tombstones, and compacted-topic behavior. A connector can successfully transfer bytes while changing the semantics an application expects.
Replication is healthy but cutover fails
Check target-side principals, ACLs, quotas, bootstrap addresses, certificates, firewall rules, and schema or configuration references. These dependencies are outside the record stream and must be provisioned and tested separately.
An archive cannot restore the service
Exported records alone are insufficient if the restore procedure omits topic policies, schemas, consumer positions, connector state, or external databases. Expand the recovery set and repeat the drill until the complete application path works.
How to decide between an archive, a replica, or both
- Independent archive: choose Kafka Connect when retention outside the cluster, offline recovery, or export to another system is the primary requirement.
- Hot migration target: choose MM2 when applications must move to another Kafka cluster with synchronized topics, groups, offsets, and ACLs.
- Layered protection: combine MM2 with Connect when you need fast failover plus a copy that does not depend on either Kafka cluster.
- Managed destination: use a provider’s replication workflow only after checking its supported Kafka version, quotas, regional placement, connector options, pricing, and partner terms for your deployment.
The decision should follow the failure you are trying to survive. Replication reduces migration and failover time; an external export reduces dependence on the source cluster. Neither removes the need to capture metadata, security, schemas, application state, and a tested restore procedure.
What a finished recovery package contains
Store a dated, access-controlled package containing:
- Record exports or a documented MM2 replication state.
- Topic lists and configurations, including partitions, replication factors, retention, and compaction.
- Consumer groups and the chosen restart or offset-translation policy.
- ACLs, principals, quotas, certificates, bootstrap settings, and network requirements.
- Schema definitions and serializer or converter settings.
- Kafka Connect worker and connector configurations plus distributed internal topics or standalone offset files.
- Provisioning notes for the target cluster and any managed-service settings.
- External database, object-store, cache, and application-state procedures.
- A cutover checklist, rollback window, owners, and the results of the latest restore drill.
Review the package after Kafka, connector, schema, security, or application changes. A backup that reflects last month’s topology cannot reliably restore today’s system.
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Bottom line
Back up Kafka as a system, not just as a pile of messages. Use Kafka Connect for controlled export and import, MM2 for a continuously replicated Kafka destination, and preserve the configuration, ACLs, schemas, consumer positions, connector state, and external dependencies that make those records usable. Validate the target before cutover, retain rollback capacity, and require a restore drill before calling the migration complete.
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