...

To handle this scenario gracefully, consumers should configure auto.offset.reset=latest when consuming from mirrored topics. This ensures that if a committed offset is beyond the current LEO after failover, the consumer automatically resets to the latest available offset rather than failing or resetting to the earliest offset.

Security

Cluster Mirroring supports comprehensive security controls through both authorization and authentication mechanisms. On the destination cluster, mirror-related operations (creating mirrors, adding/removing topics from mirrors, managing mirror configurations) require the CLUSTER_ACTION permission on the cluster resource. This ensures that only authorized principals can establish and manage cluster mirrors. When configuring a mirror, administrators specify ACLs that should be synchronized from the source cluster, and these ACLs are periodically replicated to the destination cluster to maintain consistent access control policies across both environments.

For connecting to the source cluster, Cluster Mirroring requires only the bootstrap server address and appropriate credentials, no other sensitive cluster information is exposed or required. The destination cluster's mirror configuration supports all standard Kafka authentication mechanisms including TLS/SSL for encrypted transport and SASL for client authentication.

Each mirror can be configured with its own security settings, allowing different mirrors to connect to source clusters with varying security requirements. This enables secure cross-cluster replication even when source and destination clusters use different authentication protocols or when connecting across security boundaries such as on-premises to cloud environments. All credentials are stored in the destination cluster's mirror configuration and used exclusively for establishing authenticated connections to the source cluster.

Idempotent Producer

The idempotent producers rely on producer IDs to detect duplicate writes and ensure idempotent production. To avoid conflicts with the destination cluster's producer ID space, we rewrite source producer IDs to occupy the unused negative space by applying the formula: 

destinationProducerId = -(sourceProducerId + 2)

The rationale of this formula is to keep the existing semantic of NO_PRODUCER_ID (-1) but still have a way to avoid the conflict. The CRC checksum is automatically recalculated after the producer ID changes to maintain batch integrity. Producer epochs from the source cluster are preserved exactly as they appear in the source batches. This ensures the last stable offset is correctly reflected because the producer state is updated after each append.

When a mirror topic becomes writable during failover, records with transformed producer IDs (<= -2) remain in the log with their original sequence numbers and epochs. Applications that reconnect to the destination cluster receive new producer IDs (>=0) from the destination's transaction coordinator, allowing them to continue producing.

Exactly-Once Semantics

Cluster Mirroring ensures transactional consistency when stopping by truncating to the Last Stable Offset (LSO). Note that this doesn’t mean it supports exactly-once semantics (EOS) across clusters, which would require synchronous communication.

During the mirror stopping transition, the MirrorCoordinator performs a log truncation operation that resets each mirror partition to its LSO. This offset represents the point in the log where all transactions have been decided (committed or aborted), essentially the highest offset where data is known to be consistent from a transactional perspective. Any records beyond this point may belong to incomplete transactions and should not persist after mirroring stops.

This approach prevents a critical consistency issue: the destination cluster could retain partial transaction data that would never be completed since mirroring has stopped. This would leave the topic in an inconsistent state where read_committed consumers may be blocked due to incomplete transaction data. Additionally, the transaction coordinator would not be able to rollback these hanging transactions because there is no __transaction_state metadata in the destination cluster.

Consider this source cluster log:

If replication reaches offset 4 and the source cluster fails, the destination cluster contains data records for transaction 4002 (offset 2) without the abort marker (offset 4). This creates a hanging transaction that can never be committed or aborted on the destination cluster.

Note that this approach causes data loss for any in-flight transactions during the failover and may result in already-processed records being lost if consumers on the destination cluster read uncommitted data.

Bandwidth Control

Cluster Mirroring adopts a dual-sided throttling mechanism that extends Kafka's existing bandwidth control capabilities to work across cluster boundaries.

1. Destination Cluster Throttling: To avoid conflicts with intra-cluster replication controls, mirror-specific throttling configurations operate independently from standard replication throttling. The system provides two configuration levels: a broker-level rate limit that sets the overall bandwidth ceiling for mirror replication traffic, and a topic-level replica list that specifies which partition-broker combinations should be throttled using the standard partition-index and broker-id notation. Operators can dynamically adjust throttling rates at runtime without restarting brokers, first setting a cluster-wide default rate, then fine-tuning specific topic partitions as mirroring progresses. This allows gradual bandwidth allocation as mirror relationships are established.

1. Source Cluster Throttling: The source cluster side requires a different approach because mirror fetch requests operate as consumer traffic rather than replication traffic. This design is intentional since the mirroring must fetch only up to the LSO to maintain transactional consistency, which is a consumer-level guarantee not available through the replication protocol. Consequently, standard leader replication throttling mechanisms cannot apply to mirror traffic. Instead, the source cluster leverages Kafka's client quota system. Each mirror fetcher thread presents itself with a deterministic client identifier that encodes the broker ID, fetcher thread number, and mirror name. Operators can apply per-client byte rate quotas to these identifiers, effectively throttling the outbound mirror traffic from the source cluster. This approach integrates seamlessly with Kafka's existing quota enforcement infrastructure.

Tiered Storage

Tiered Storage is not initially supported, but a detailed design of the metadata synchronization protocol, API schema, and state management will be provided in a follow-up KIP.

A mirror follower that receives an OffsetMovedToTieredStorageException from the source leader handles it by marking the partition as failed, and also the mirror partition state will move to FAILED state.

Share Group

Cluster Mirroring supports both traditional consumer groups and share consumer groups (Kafka Queue functionality) to ensure seamless failover for all consumer types. While the data mirroring mechanism remains identical, the offset synchronization strategy differs based on the group type.

Share consumer groups use a different offset management model based on Share-Partition Start Offset (SPSO) and Share-Partition End Offset (SPEO) rather than traditional committed offsets. First we retrieve the current SPSO for each share group using the DescribeShareGroupOffsets API from the source cluster, and then we update the SPSO in the destination cluster using the AlterShareGroupOffsets API, which also initializes the group state in both the group coordinator and share coordinator. This means the API can initialize a share group in the destination cluster even if it doesn't exist yet, eliminating the need for pre-creation or complex state management.

Kafka enforces that consumer group and share group names must be unique within a single cluster. This creates a potential conflict scenario during mirroring. When such conflicts occur, the offset commit operation will fail with GroupIdNotFoundException. Users must resolve these conflicts manually by either deleting the conflicting group in the destination cluster before mirroring begins, or excluding the conflicting groups from offset synchronization. These conflicts affect only offset synchronization and do not impact data mirroring itself. The topic data continues to replicate normally, and only the automatic offset synchronization for the conflicting groups is blocked.

Diskless Topics

Given Diskless Topics KIP (KIP-1500) is still under discussion, there will be future KIPs to support it.

Active-Active Writes

Active-active topology is not initially supported in Cluster Mirroring, though it could potentially be achieved through topic prefixing and removing the reliance on topic ID for mirroring. This is a candidate for a future improvement KIP. 

Instead, bidirectional mirroring is supported, but only when mirroring different topics between clusters, allowing records produced to either cluster to be consumed from both. Unlike MirrorMaker 2, Cluster Mirroring does not need special cycle detection or prevention logic because the read-only enforcement inherently blocks the conditions that would create infinite replication loops.

Public Interfaces

Briefly list any new interfaces that will be introduced as part of this proposal or any existing interfaces that will be removed or changed. The purpose of this section is to concisely call out the public contract that will come along with this feature.

...