Elasticsearch Cross-Cluster Replication: Architecture and Design
Cross-cluster replication (CCR) in Elasticsearch allows you to replicate indices from a source cluster to a destination cluster. This powerful feature provides solutions for a variety of use cases, including disaster recovery, geo-proximity search, and rolling upgrades. This article delves into the architecture and design of CCR, explaining its components and how they interact to facilitate seamless data synchronization.
Core Components:
- Leader Index (Source Cluster): The index on the source cluster that you want to replicate. It acts as the primary source of data.
- Follower Index (Destination Cluster): The replica of the leader index on the destination cluster. It receives and applies operations from the leader index.
- Replication API: Used to configure and manage CCR relationships between leader and follower indices.
- Remote Cluster Connection: A connection established from the destination cluster to the source cluster. This connection allows the follower index to communicate with the leader index.
- Auto-follow Pattern: (Optional) Allows for automated replication of newly created indices matching a specified pattern. This simplifies management and ensures consistent replication across clusters.
- History Retention Lease: A mechanism that prevents the leader index from deleting history information needed for replication until the follower index has processed it. This guarantees data consistency and prevents data loss.
Architecture and Workflow:
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Establishing a Connection: The destination cluster initiates a connection to the source cluster using a remote cluster connection. This connection identifies the source cluster and provides necessary authentication credentials.
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Creating a Follower Index: Using the Replication API, a follower index is created on the destination cluster. This follower index specifies the leader index on the source cluster that it will follow.
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Index Changes on Leader: When documents are indexed, updated, or deleted on the leader index, these operations are recorded in the transaction log (translog).
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Changes Pulled by Follower: The follower index periodically polls the leader index’s translog for new changes.
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Replaying Operations: The follower index receives these changes and replays them locally, ensuring that the data remains synchronized with the leader index.
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History Retention Lease: The follower index maintains a history retention lease on the leader index. This lease informs the leader index how long to retain the operation history in its translog, even after it’s been merged into the index segments. This ensures that the follower index can catch up if it falls behind.
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Auto-follow (Optional): If auto-follow patterns are configured, any newly created indices on the source cluster matching the defined pattern will automatically be replicated to the destination cluster.
Design Considerations:
- Resource Utilization: CCR consumes resources on both the source and destination clusters. Plan accordingly for increased CPU, memory, and network bandwidth usage.
- Network Latency: Network latency between the clusters can impact replication performance. Consider the geographical location of your clusters and optimize network connectivity.
- Version Compatibility: CCR requires compatible versions of Elasticsearch between the source and destination clusters.
- Security: Secure the connection between the clusters using appropriate authentication and authorization mechanisms.
- Conflict Resolution: In bi-directional replication scenarios, conflicts can arise. Elasticsearch doesn’t provide built-in conflict resolution, requiring careful planning and potential custom solutions.
Use Cases:
- Disaster Recovery: Replicate data to a geographically separate cluster to provide redundancy and business continuity in case of a primary cluster failure.
- Geo-proximity Search: Replicate data to geographically distributed clusters to improve search latency for users in different regions.
- Rolling Upgrades: Replicate data to a new cluster running a newer version of Elasticsearch, allowing for seamless upgrades with minimal downtime.
Conclusion:
Cross-cluster replication in Elasticsearch offers a robust and flexible mechanism for data synchronization between clusters. Understanding its architecture and design principles is crucial for successfully implementing and managing CCR deployments. By carefully considering resource utilization, network latency, security, and potential conflicts, you can leverage CCR to enhance the resilience, performance, and scalability of your Elasticsearch infrastructure.