Elasticsearch Elasticsearch Network Host Configuration: Best Practices and Optimization

By Opster Team

Updated: Jun 14, 2023

| 2 min read

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Configuring the network host settings in Elasticsearch is a crucial step in ensuring that your cluster operates efficiently and securely. In this article, we will discuss the importance of the network.host setting, best practices for configuring it, and how to optimize it for different scenarios.

Understanding the network.host Setting

The network.host setting in Elasticsearch determines the network interface(s) on which Elasticsearch will bind its HTTP and transport services. This setting is essential for controlling how Elasticsearch communicates with other nodes in the cluster and how clients can access the cluster.

By default, Elasticsearch binds to the loopback address (, which means it will only be accessible from the same machine. This is suitable for development and testing purposes but not for production environments where multiple nodes need to communicate with each other.

Best Practices for Configuring network.host

1. Use IP addresses or hostnames: You can specify the network.host setting using an IP address, a hostname, or a combination of both. It is recommended to use IP addresses or resolvable hostnames to avoid potential issues with DNS resolution.




network.host: my-node.example.com

2. Bind to a specific network interface: If your Elasticsearch node has multiple network interfaces, you can bind the node to a specific interface by specifying its IP address or hostname. This can help you segregate traffic and improve security.



3. Bind to all available network interfaces: In some cases, you may want Elasticsearch to bind to all available network interfaces. You can achieve this by using the special value “” or “_local_”.




network.host: _local_

4. Use special values for dynamic configuration: Elasticsearch supports several special values for the network.host setting, which can be useful in dynamic environments like cloud deployments or containerized environments.

  • _local_: Binds to all available network interfaces on the local machine.
  • _site_: Binds to all site-local (private) IPv4 addresses.
  • _global_: Binds to all globally-scoped (public) IPv4 addresses.
  • _[networkInterface]_: Binds to the IP address of the specified network interface.


network.host: _site_


network.host: _eth0_

Optimizing network.host for Different Scenarios

  1. Development and testing: For development and testing purposes, you can use the default loopback address ( or bind to all available network interfaces using “” or “_local_”.
  1. Production environments: In production environments, it is recommended to bind Elasticsearch to a specific network interface or use the special values like “_site_” or “_global_” to ensure that the node is accessible only from the intended networks.
  1. Multi-node clusters: For multi-node clusters, configure each node to bind to a specific network interface or use the special values like “_site_” or “_global_” to ensure that nodes can communicate with each other and clients can access the cluster.
  1. Cloud deployments: In cloud environments, you can use the special values like “_site_” or “_global_” to automatically bind Elasticsearch to the appropriate network interfaces. Alternatively, you can use the cloud provider’s metadata service to obtain the node’s IP address and configure the network.host setting accordingly.
  1. Containerized environments: In containerized environments, you can use the special values like “_site_” or “_global_” to automatically bind Elasticsearch to the appropriate network interfaces. Alternatively, you can use environment variables or configuration management tools to dynamically set the network.host setting based on the container’s network configuration.


In conclusion, properly configuring the network.host setting in Elasticsearch is essential for ensuring efficient and secure communication between nodes and clients. By following the best practices and optimization tips outlined in this article, you can ensure that your Elasticsearch cluster is well-prepared for various deployment scenarios.

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