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update(MirrorMaker): improve configuration concepts (#586)
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Co-authored-by: Harshini Rangaswamy <harshini.rangaswamy@aiven.io>
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jclarysse and harshini-rangaswamy authored Dec 13, 2024
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139 changes: 92 additions & 47 deletions docs/products/kafka/kafka-mirrormaker/concepts/mirrormaker2-tuning.md
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---
title: MirrorMaker 2 common parameters
title: Configuration parameters for Aiven for Apache Kafka® MirrorMaker 2
---

MirrorMaker 2 (MM2) offers a suite of parameters to help with data replication and monitoring within Apache Kafka® ecosystems.
This topic outlines common parameters you can adjust, along with tips for
validating MM2's performance.

1. Increase the value of `kafka_mirrormaker.tasks_max_per_cpu` in the
advanced options. Setting this to match the number of partitions can
enhance performance.
1. Ensure the interval seconds for the following settings match. You
can reduce these intervals for more frequent data synchronization:
- Advanced options:
- `kafka_mirrormaker.emit_checkpoints_interval_seconds`
- `kafka_mirrormaker.sync_group_offsets_interval_seconds`
- Replication flow:
- `Sync interval in seconds`.
1. To exclude internal topics, add these patterns to your topic
blacklist:
- `.*[\-\.]internal` `.*\.replica` `__.*` `connect.*`
1. Depending on your use case, consider adjusting these parameters:
- `kafka_mirrormaker.consumer_fetch_min_bytes`
- `kafka_mirrormaker.producer_batch_size`
- `kafka_mirrormaker.producer_buffer_memory`
- `kafka_mirrormaker.producer_linger_ms`
- `kafka_mirrormaker.producer_max_request_size`

## MirrorMaker 2 validation tips

To ensure MirrorMaker 2 is up-to-date with message processing, monitor
these:

1. **Consumer lag metric**: Monitor the `kafka.consumer_lag` metric.

1. **Dashboard metrics**: If MirrorMaker 2 stops adding records to a
topic, the `jmx.kafka.connect.mirror.record_count` metric stops
increasing, showing a flat line on the dashboard.

1. **Retrieve latest messages with \`kt\`**: Use
[kt](https://github.com/fgeller/kt) to retrieve the latest messages
from all partitions with the following command:

```
kt consume -auth ./mykafka.conf \
-brokers SERVICE-PROJECT.aivencloud.com:PORT \
-topic topicname -offsets all=newest:newest | \
jq -c -s 'sort_by(.partition) | .[] | \
{partition: .partition, value: .value, timestamp: .timestamp}'
```
Learn about the configuration layers in Aiven for Apache Kafka® MirrorMaker 2, including service, replication flow, and integration settings.
Optimize data replication and performance in your Kafka ecosystem.

## Configuration layers

Aiven for Apache Kafka® MirrorMaker 2 configurations are organized into three layers:
**service**, **replication flow**, and **integration**. Each layer controls a specific
aspect of the replication process.

### Service configurations

Service configurations control the behavior of nodes and workers in the
Aiven for Apache Kafka® MirrorMaker 2 cluster.

**Example of a service configuration**:

- Parameter: [`kafka_mirrormaker.emit_checkpoints_enabled`](https://aiven.io/docs/products/kafka/kafka-mirrormaker/reference/advanced-params#kafka_mirrormaker_emit_checkpoints_enabled)
- Description: Enables or disables periodically emitting consumer group offset
checkpoints to the target cluster.
- Impact:
- Automatically restarts the workers.
- Restarts all connectors and tasks.

### Replication-flow configurations

Replication-flow configurations manage the behavior of connectors, such as Source, Sink,
Checkpoint, and Heartbeat.

**Example of a replication-flow configuration**:

- Parameter: [`topics`](https://registry.terraform.io/providers/aiven/aiven/latest/docs/resources/mirrormaker_replication_flow)
- Description: Specifies a list of topics or regular expressions to replicate.
For more information, see the [topics included in a replication flow](/docs/products/kafka/kafka-mirrormaker/concepts/replication-flow-topics-regex).
- Impact:
- Automatically restarts the affected connectors.
- Restarts their associated tasks.

### Integration configurations

Integration configurations fine-tune the interaction between producers and consumers
within connectors.

**Example of an integration configuration**:

- Parameter: [`consumer_fetch_min_bytes`](https://registry.terraform.io/providers/aiven/aiven/latest/docs/resources/service_integration#nested-schema-for-kafka_mirrormaker_user_configkafka_mirrormaker)
- Description: Sets the minimum amount of data the server should return for a fetch
request.
- Impact:
- Automatically restarts the workers.
- Restarts all connectors and tasks.

:::note
Most configuration parameters are derived from
[KIP-382: MirrorMaker 2.0 - Configuration Properties](https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=95650722#KIP382:MirrorMaker2.0-ConnectorConfigurationProperties). Refer to this resource for additional details.
:::

## Common parameters

This section describes common parameters that can be adjusted to optimize the performance
and behavior of Aiven for Apache Kafka MirrorMaker 2 replication.

1. **Optimize task allocation**:
Increase the value of
[`kafka_mirrormaker.tasks_max_per_cpu`](/docs/products/kafka/kafka-mirrormaker/reference/advanced-params#kafka_mirrormaker_tasks_max_per_cpu)
in the advanced configuration.
Setting this to match the number of partitions can improve performance.

1. **Align interval settings**:
Ensure the following interval settings match to achieve more frequent and synchronized
data replication:
- **Advanced configurations**:
- [`kafka_mirrormaker.emit_checkpoints_interval_seconds`](/docs/products/kafka/kafka-mirrormaker/reference/advanced-params#kafka_mirrormaker_emit_checkpoints_interval_seconds)
- [`kafka_mirrormaker.sync_group_offsets_interval_seconds`](/docs/products/kafka/kafka-mirrormaker/reference/advanced-params#kafka_mirrormaker_sync_group_offsets_interval_seconds)
- **Replication flow**:
- `Sync interval in seconds`

1. **Exclude internal topics**:
Add these patterns to your topic blacklist to exclude internal topics:
- `.*[\-\.]internal`
- `.*\.replica`
- `__.*`
- `connect.*`

1. **Adjust integration parameters**:
Modify these integration parameters based on your use case to improve producer and
consumer performance:
- `consumer_fetch_min_bytes`
- `producer_batch_size`
- `producer_buffer_memory`
- `producer_linger_ms`
- `producer_max_request_size`
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---
title: Monitor replication execution
---
Apache Kafka® MirrorMaker 2 uses Kafka® Connect for monitoring and state management, helping you track replication flows and address issues.

## Monitoring tips

Follow these tips to ensure that replication is up-to-date with message processing:

1. **Monitor consumer lag:** Use the `kafka.consumer_lag` metric to track replication
progress and identify delays.

1. **Track dashboard metrics:** Check the `jmx.kafka.connect.mirror.record_count` metric.
If MirrorMaker 2 stops adding records to a topic, this metric will show a flat line,
indicating no new records are being replicated.

1. **Retrieve the latest messages using `kt`:** Use the
[**kt**](https://github.com/fgeller/kt) tool to fetch the latest messages from all
partitions. Run the following command:

```bash
kt consume -auth ./mykafka.conf \
-brokers SERVICE-PROJECT.aivencloud.com:PORT \
-topic topicname -offsets all=newest:newest | \
jq -c -s 'sort_by(.partition) | .[] | \
{partition: .partition, value: .value, timestamp: .timestamp}'
```
1 change: 1 addition & 0 deletions sidebars.ts
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Expand Up @@ -1060,6 +1060,7 @@ const sidebars: SidebarsConfig = {
items: [
'products/kafka/kafka-mirrormaker/howto/integrate-external-kafka-cluster',
'products/kafka/kafka-mirrormaker/howto/setup-replication-flow',
'products/kafka/kafka-mirrormaker/howto/monitor-replication-execution',
'products/kafka/kafka-mirrormaker/howto/remove-mirrormaker-prefix',
'products/kafka/kafka-mirrormaker/howto/datadog-customised-metrics',
'products/kafka/kafka-mirrormaker/howto/log-analysis-offset-sync-tool',
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