Elasticsearch Elasticsearch Minimum Requirements

By Opster Team

Updated: Mar 10, 2024

| 2 min read

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Elasticsearch Minimum Requirements: Hardware and Configuration Guidelines

When deploying an Elasticsearch cluster, it is crucial to consider the minimum requirements for hardware and configuration settings to ensure optimal performance and stability. This article will provide you with detailed guidelines on the minimum requirements for Elasticsearch, including hardware specifications, JVM settings, and cluster configuration best practices.

1. Hardware Requirements

To run Elasticsearch efficiently, you should consider the following hardware requirements:

a. Memory (RAM)

Elasticsearch relies heavily on the Java heap space for storing and processing data. A minimum of 8GB RAM is recommended for production environments, with at least 50% of the total memory allocated to the Java heap (4GB). For larger deployments, consider using machines with 64GB or more RAM.

b. CPU

Elasticsearch can benefit from multiple CPU cores for parallel processing. A minimum of 4 CPU cores is recommended for production environments, with more cores providing better performance for indexing and search operations.

c. Disk Space

The required disk space depends on the amount of data you plan to store in your Elasticsearch cluster. It is recommended to have at least 50GB of free disk space for a small production environment. For larger deployments, consider using SSDs for better I/O performance.

d. Network

A high-speed network connection is essential for efficient communication between Elasticsearch nodes. A minimum of 1Gbps network bandwidth is recommended for production environments.

2. JVM Settings

Elasticsearch runs on the Java Virtual Machine (JVM), and configuring the JVM settings is crucial for optimal performance. Consider the following JVM settings:

a. Heap Size

Allocate at least 50% of the total RAM to the Java heap (e.g., 4GB for an 8GB RAM machine). Avoid allocating more than 50% of the total RAM to prevent swapping and garbage collection issues.

b. Garbage Collection

Use the G1 garbage collector for better performance and lower latency. To enable G1, add the following JVM options in the “$ELASTICSEARCH_HOME/config/jvm.options” file:


3. Cluster Configuration Best Practices

To ensure a stable and performant Elasticsearch cluster, follow these best practices for cluster configuration:

a. Node Roles

Assign specific roles to each node in the cluster, such as data nodes, master nodes, coordinating nodes, ingest nodes, machine learning nodes (ml), and some more. This separation of roles helps distribute the workload and improves cluster stability.

b. Shard Allocation

Distribute shards evenly across the nodes in the cluster to balance the load. Use the “index.number_of_shards” and “index.number_of_replicas settings to control the number of primary and replica shards for each index.

c. Discovery and Fault Detection

Configure the discovery.seed_hosts” and “cluster.initial_master_nodes” settings to help nodes discover each other and form a cluster. Also, set the “discovery.zen.ping.unicast.hosts” setting for unicast discovery in Elasticsearch versions prior to 7.x.

d. Monitoring and Logging

Enable monitoring and logging features to track the performance and health of your Elasticsearch cluster. Use the built-in monitoring features provided by Elasticsearch, such as the _cat APIs and the Monitoring UI in Kibana.


In conclusion, understanding and adhering to the minimum requirements for Elasticsearch in terms of hardware, JVM settings, and cluster configuration is essential for a stable and performant deployment. By following these guidelines, you can ensure that your Elasticsearch cluster operates efficiently and meets the demands of your production environment.

If you want to learn more about Elasticsearch minimum requirements, take a look at this guide, which goes into further details which the requirements for a production environment are.