Node Roles in Elasticsearch

Elasticsearch nodes can assume different roles based on their configurations and responsibilities within the cluster. The common node roles include:

1. Master-eligible Nodes

• Master-eligible nodes participate in the election process to elect a master node responsible for cluster-wide management tasks.
• They maintain cluster state, coordinate node additions or removals, and handle administrative actions like creating or deleting indices.
• Typically, it’s recommended to have at least three master-eligible nodes for fault tolerance and to avoid split-brain scenarios.

2. Data Nodes

• Data nodes store and manage indexed documents and handle data-related operations such as indexing, search, and retrieval.
• They store shards (partitions of indices) and replicate data for fault tolerance.
• Adding more data nodes increases the storage capacity and improves search performance by distributing the workload.

3. Ingest Nodes

• Ingest nodes are responsible for preprocessing documents before indexing.
• They can apply transformations, enrich data, or extract specific fields from incoming documents using ingest pipelines.
• Ingest nodes are optional but useful for offloading preprocessing tasks from data and master nodes.

4. Client Nodes

• Client nodes help route search and indexing requests to the right data nodes in the cluster.
• They serve as a gateway for external clients, distributing requests evenly across data nodes for load balancing.
• Client nodes help improve the scalability and resilience of the cluster by isolating query processing from data storage.

Elasticsearch’s cluster architecture and node roles are fundamental to building scalable and fault-tolerant search infrastructures. A cluster comprises interconnected nodes, each serving specific roles like master, data, ingest, or coordinating-only. Understanding these components is crucial for efficient cluster management and performance.

In this article, We will learn about the Elasticsearch Cluster Architecture, Node Roles in Elasticsearch, and Practical Examples in detail.