# Topic naming (Prefixed vs Identical)
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MSK Replicator has two topic name configuration modes: *Prefixed* (default) or *Identical* topic name replication.

**Prefixed topic name replication**  
By default, MSK Replicator creates new topics in the target cluster with an auto-generated prefix added to the source cluster topic name, such as `<sourceKafkaClusterAlias>.topic`. This distinguishes the replicated topics from others in the target cluster and avoids circular replication of data between the clusters.

For example, MSK Replicator replicates data in a topic named "topic" from the source cluster to a new topic in the target cluster called `<sourceKafkaClusterAlias>.topic`. You can find the prefix under the **sourceKafkaClusterAlias** field using the `DescribeReplicator` API or the **Replicator details** page on the MSK console.

To make sure your consumers can reliably restart processing from the standby cluster, configure your consumers to read data from the topics using a wildcard operator `.*`. For example, your consumers would need to consume using `.*topic1` in both AWS Regions. This example would also include a topic such as `footopic1`, so adjust the wildcard operator according to your needs.

Use Prefixed topic name replication when you want to keep replicated data in a separate topic in the target cluster, such as for active-active cluster setups. For Prefixed configuration, both `ReplicatorBytesInPerSec` and `ReplicatorThroughput` will have the same value as no data will be filtered by MSK Replicator.

**Identical topic name replication**  
As an alternative, Amazon MSK Replicator allows you to create a Replicator with topic replication set to Identical topic name replication (**Keep the same topics name** in console). Identically-named replicated topics let you avoid reconfiguring clients to read from replicated topics.

Identical topic name replication has the following advantages:
+ Retains identical topic names during replication while automatically avoiding infinite replication loops.
+ Simplifies multi-cluster streaming architectures since you can avoid reconfiguring clients.
+ Streamlines the failover process for active-passive architectures, allowing applications to seamlessly failover without topic name changes or client reconfigurations.
+ Can consolidate data from multiple MSK clusters into a single cluster for data aggregation or centralized analytics (requires separate Replicators for each source cluster).
+ Can streamline data migration from one MSK cluster to another.

Amazon MSK Replicator uses Kafka headers to automatically avoid data being replicated back to the topic it originated from, eliminating the risk of infinite cycles during replication. MSK Replicator embeds identifiers for source cluster and topic into the header of each record being replicated (`__mskmr`). You should verify that your clients are able to read replicated data as expected.