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Kafka backup is more than copying broker files. In-cluster replication protects against a broker failure, but it is not an independent recovery copy. A dependable plan exports records or continuously replicates them to another failure domain, while also preserving topic settings, security, schemas, connector state and consumer positions. Use Kafka Connect for file or external-system pipelines, MirrorMaker 2 (MM2) for a live target cluster, or both when you need a hot migration target and an independent archive.
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What a Kafka backup must protect
A Kafka deployment has several kinds of state. The records in a topic are only one part of what an application needs in order to resume service.
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- Records: keys, values, timestamps, headers, tombstones and transaction-related behavior where applicable.
- Topic structure: topic names, partition counts, replication factors, retention, cleanup policy, compaction settings and other topic-level configuration.
- Consumer progress: consumer-group membership information and committed offsets. A target cluster can contain every record and still restart consumers at the wrong position.
- Security: principals, ACLs, quotas, TLS/SASL settings and the client configuration that connects applications to the cluster.
- Integration state: Kafka Connect connector definitions plus their configuration, offset and status stores.
- Data contracts: schema definitions, compatibility rules and serializer settings used by producers and consumers.
- Application dependencies: external databases, object stores and other systems whose state is not stored in Kafka.
Broker replication keeps multiple copies inside Kafka’s normal operating domain. It does not by itself protect against accidental deletion, a bad retention change, a compromised cluster, a region-wide outage or an operator mistake that is replicated everywhere. An independent export or a second cluster in another failure domain addresses those risks differently.
Choose the copy method for the outcome you need
| Method | Best use | What it copies | Main limitations |
|---|---|---|---|
| Kafka Connect source and sink | Exporting to files, databases, object storage or another external system, then importing | Records as interpreted and serialized by the connector | Connector semantics, schema handling, offsets and exactly-once behavior vary by connector. The file example in the Kafka quickstart demonstrates the mechanism; it is not a complete disaster-recovery design. |
| Legacy MirrorMaker | Basic source-to-target topic replication | Records and keys to a same-named destination topic | Source and destination offsets differ. Apache Kafka documents it as replication, not transparent failover or a replacement for in-cluster replication. |
| MirrorMaker 2 | Migration, disaster recovery, geo-replication and hybrid-cloud moves | Topics, topic configurations, consumer groups and offsets, ACLs, partitioning, and newly discovered topics and partitions | Replication flows, naming, authentication, offset translation and cutover must be designed and tested. |
| Managed Kafka replication | Moving to a provider-operated Kafka service | Provider-specific replication and migration state | Feature compatibility, quotas, pricing, regional availability and partner terms differ. Verify them for the target service and date of the move. |
Many production plans combine methods: MM2 maintains a warm target cluster for a planned move or regional failure, while Kafka Connect exports selected topics to an independent archive for recovery from corruption or deletion.
#1 Best Overall
Set recovery objectives before moving data
There is no universal Kafka recovery point objective (RPO), recovery time objective (RTO), throughput limit or migration downtime that applies to every deployment. Set values per service and measure them in a drill.
- RPO: how much recently produced data may be lost. A continuously replicated target can reduce exposure, but replication lag still matters.
- RTO: how long the application may be unavailable while clients, credentials, schemas and consumers are switched.
- Retention window: how far back an archive must allow you to restore. Topic retention alone may be too short for an investigation or delayed recovery.
- Cutover tolerance: whether producers can be paused, drained or coordinated, and whether consumers can tolerate duplicates during a retry.
- Rollback window: how long the original cluster remains available after the switch.
Write these objectives down for each workload. A payment stream, an audit topic and a transient metrics topic may legitimately require different retention, validation and cutover procedures.
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Before creating connectors or replication flows, capture a point-in-time inventory. Record the Kafka and broker versions, whether the deployment uses KRaft or ZooKeeper, and the network and security model. Then enumerate:
- Every topic, partition count, replication factor, leader distribution and in-sync replica policy.
- Retention, cleanup policy, compaction, segment and message-size settings that affect replay.
- Producer applications, consumer applications, consumer groups and their committed positions.
- ACLs, principals, quotas, TLS certificates, SASL mechanisms and bootstrap-server settings.
- Schema registry subjects, versions, compatibility modes and serializer/deserializer choices.
- Kafka Connect workers, connector names, task counts, transforms and destination systems.
- Throughput, peak traffic, partition growth and any topics created dynamically.
- External databases, object stores and services that must be backed up or coordinated separately.
Keep the inventory with the backup manifest. A list of topic names without their configuration and ownership is insufficient to rebuild an operational cluster.
Select an architecture
Use Kafka Connect for an export or import pipeline
Kafka Connect is designed to continuously ingest data from external systems into Kafka and in the opposite direction. The official quickstart demonstrates a file source connector that reads lines and publishes them to a topic, and a file sink connector that writes topic records to a file. Those examples establish the workflow, not the durability, schema or audit guarantees of a production archive.
For an export, choose a sink connector whose destination provides the retention and immutability you require. Define how keys, headers, timestamps, tombstones and schema identifiers are represented. For an import, use a source connector that can preserve the original identity and ordering assumptions your consumers rely on.
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- Decide whether the destination is append-only, versioned or subject to its own retention policy.
- Record connector configuration, task status and source offsets along with the exported data.
- Test restart behavior, retries and duplicate handling; exactly-once guarantees depend on the connector and destination.
In distributed Kafka Connect mode, worker configuration, offsets and status are stored in Kafka topics. In standalone mode, source offsets are kept in a local file. Include those internal stores in the backup design and protect the standalone offset file from loss.
Use legacy MirrorMaker only for simple replication
Legacy MirrorMaker reads records from source topics and writes them to same-named topics in the destination cluster. It can be adequate for a straightforward feed where applications are prepared to start with destination offsets managed independently.
It is not a transparent failover mechanism. The source and destination clusters maintain different offset spaces, so a consumer cannot blindly take a source offset and seek to that number on the target. Plan a new consumer position, accept an application-specific replay window, or use MM2’s offset-sync features instead.
Use MirrorMaker 2 for a live migration target
MM2 is the Kafka replication tool intended for migrations, disaster recovery and multi-cluster topologies. It can replicate topic data and configuration, consumer groups and offsets, ACLs, partitioning, and topics or partitions discovered after the initial setup.
Design the replication direction and naming before starting. Decide whether destination topic names are prefixed, how loops are prevented, which topics are allowed, and which cluster is authoritative during the move. Configure authentication in both directions and restrict the replicated principals to the minimum required permissions.
Offset translation deserves its own test. A group that exists on both clusters may have a translated position based on records observed by MM2, but the result is not a guarantee that every application will resume without replay or a gap. Validate with a test consumer and known markers before the production cutover.
Capture configuration, security and schemas
Export or record the non-record state before replication begins. Use a versioned manifest so that a restore can be repeated rather than reconstructed from memory.
| Item | Why it matters during restore | Verification |
|---|---|---|
| Topic configuration | Retention, compaction and message-size differences can change replay results. | Compare topic names, partition counts and effective configuration on both clusters. |
| Consumer groups and offsets | Consumers need a deliberate restart point. | Check translated positions with test records and application-level lag. |
| ACLs, principals and quotas | Applications may connect but still fail authorization or throttling checks. | Run producer and consumer permission tests using the real identities. |
| Connect configuration, offsets and status | Tasks can duplicate, skip or restart from the wrong source position without their internal state. | Restore a connector in a test environment and observe a controlled restart. |
| Schema and serializer settings | Bytes may be present while consumers cannot deserialize them. | Produce and consume representative records, including schema evolution cases. |
| Client configuration | Bootstrap addresses, security protocol, trust stores and schema endpoints determine whether applications can switch. | Use a staging client configuration against the target before cutover. |
Do not assume that copying a topic automatically copies external schema-registry subjects, application databases, connector plugins or certificates. Those systems have separate backup and restoration procedures.
Migration and backup runbook
- Define objectives and ownership. Assign an owner for each topic group, document RPO, RTO, retention and rollback duration, and obtain approval for the cutover window.
- Freeze the inventory. Capture versions, KRaft or ZooKeeper mode, topics, partitions, policies, groups, ACLs, quotas, schemas, connectors and client dependencies. Identify topics that may be created during the migration.
- Choose the copy path. Select Connect for file or external-system export/import, MM2 for a continuously replicated cluster, or both for hot migration plus independent archive.
- Prepare credentials and networking. Establish routable connectivity, TLS/SASL trust, firewall rules, service accounts and least-privilege ACLs on the target. Test authentication before sending production data.
- Provision the target. Install a compatible Kafka protocol and serialization stack. Pre-create topics when exact partition counts, replication factors or policies are important; otherwise confirm how the chosen replication method creates them.
- Deploy connectors or MM2 flows. Apply allowlists, replication factors, naming rules and task settings. For Connect, preserve the required internal configuration, offset and status stores. For MM2, configure each source-to-target flow and offset synchronization.
- Start monitoring immediately. Watch replication lag, connector task failures, authentication errors, missing topics, partition counts, ACL propagation, throughput and consumer-offset translation. Alert on a stalled flow rather than relying on eventual discovery.
- Validate before cutover. Compare inventories and effective topic settings. Where practical, compare record counts, checksums or known event IDs, timestamps, keys, headers, tombstones and compacted-topic behavior. Test producer and consumer permissions and restart a consumer from the planned target position.
- Drain and switch deliberately. Quiesce producers or coordinate a write boundary, let replication catch up, record the cutover marker, then update bootstrap servers, security references and schema endpoints in clients. Resume producers on the target and watch for duplicate or missing events.
- Keep rollback capacity. Leave the source read-only or otherwise available for the agreed window. Preserve its credentials and manifests, monitor both clusters, and decommission the source only after application owners accept the target.
How to validate a target cluster
Structural checks
- Every required topic exists, including topics created after the initial replication setup.
- Partition counts and replication settings meet the application’s ordering and availability assumptions.
- Retention and compaction policies match the intended recovery window.
- ACLs, quotas and principal mappings produce the expected allow and deny results.
Record checks
- Use deterministic event IDs or sampled hashes to detect gaps and duplicates.
- Verify keys, timestamps, headers, tombstones and representative large messages.
- For compacted topics, check the final key state as well as the raw event stream; compaction can make simple record-count comparisons misleading.
- Include transactional or otherwise special records in the test set if applications depend on them.
Application checks
- Start a test producer and consumer with production-like serializers and credentials.
- Stop and restart a consumer to confirm its target offset behavior.
- Restart Connect workers and verify that tasks resume from the intended positions without unexplained replay.
- Exercise downstream databases and services, because Kafka availability alone does not restore external application state.
Restore from an exported archive
An archive restore is a controlled import, not a file copy into a broker directory. First provision a clean or approved target cluster and apply the captured security, schema and topic configuration. Then configure the source connector for the archive and the sink-side application or topic import.
- Validate the archive manifest, retention period and integrity checks.
- Recreate schemas and serializer settings before importing records.
- Create topics with the required partition and cleanup policies.
- Import a small sample into an isolated topic and verify decoding, keys, headers, timestamps and tombstones.
- Import the required time range or topic set, monitoring connector offsets, task errors and destination lag.
- Restore consumer groups deliberately. Choose a timestamp, event ID or translated offset as the restart boundary instead of assuming the archive’s position is valid for the new cluster.
- Run application and downstream-system checks, then open traffic only after owners approve the results.
If the archive stores transformed records rather than Kafka’s original wire representation, document the transformation. A successful import may reproduce business values while still being unsuitable for byte-for-byte replay or transaction-sensitive consumers.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Common failure modes and fixes
“The brokers are replicated, so we have a backup.”
Replication within the same failure domain can reproduce an accidental deletion or an unsafe configuration change. Add an independent archive or a separately operated target cluster, and test restoring it.
Consumers start at the wrong place
Source and destination offset spaces differ, especially with legacy MirrorMaker. Use MM2 offset synchronization where appropriate, then verify the translated position with known records. Otherwise define an explicit replay boundary and make consumers idempotent.
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Static topic lists do not cover topics created later. Configure MM2 discovery or an equivalent onboarding process, and alert when source and target inventories diverge.
Messages exist but applications cannot read them
Check serializer versions, schema subjects, compatibility rules, headers and security protocol settings. Reproducing bytes without the matching data contract does not constitute a usable restore.
Best Value
Connect restarts duplicate or skip records
Inspect the connector’s documented delivery semantics and internal offset store. Distributed workers require their internal Kafka topics; standalone workers require the local offset file. Test failure and restart behavior with the actual connector and destination.
Compacted topics do not match record counts
Compaction changes which historical records remain visible. Compare key state and application outcomes, not only total records, and verify tombstone handling.
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Check network capacity, source production rate, destination throttling, connector task errors, authorization and partition skew. Do not cut over while an unmeasured backlog remains; record the lag and its associated event boundary.
Run a restore drill
A backup is credible only when an independent operator can restore it within the chosen objectives. Schedule a drill that uses the same manifests, credentials, connector versions and client configuration intended for an incident.
- Measure elapsed time from declaring the incident to producing and consuming a verified record on the target.
- Measure the oldest and newest recoverable event and compare the result with the RPO.
- Verify topic policies, schemas, ACLs, quotas, consumer positions and Connect task recovery.
- Record duplicates, gaps, manual steps and assumptions, then update the runbook.
- Keep the drill evidence with the backup manifest and repeat it after Kafka, connector, schema or security changes.
The practical standard is not “the files exist.” It is that records, metadata, security and applications can resume predictably, with measured data loss and downtime, after the failure scenario the plan is meant to address.
Quick Recap
Which approach should you use?
- Need a portable export to another system? Use Kafka Connect, select a destination with suitable retention and integrity controls, and preserve connector and schema state.
- Need a continuously updated cluster for migration or regional recovery? Use MM2, design naming and offset translation, and validate a planned cutover.
- Need both rapid failover and protection from deletion or corruption? Maintain an MM2 target plus an independent Connect-based archive for the topics and retention period that matter.
- Need to move to a managed service? Treat provider replication as a migration project: verify protocol, feature, quota, security and regional compatibility, and measure the resulting RPO and RTO rather than assuming them.
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