Important Elasticsearch configurationedit

Elasticsearch requires very little configuration to get started, but there are a number of items which must be considered before using your cluster in production:

Our Elastic Cloud service configures these items automatically, making your cluster production-ready by default.

Path settingsedit

Elasticsearch writes the data you index to indices and data streams to a data directory. Elasticsearch writes its own application logs, which contain information about cluster health and operations, to a logs directory.

For macOS .tar.gz, Linux .tar.gz, and Windows .zip installations, data and logs are subdirectories of $ES_HOME by default. However, files in $ES_HOME risk deletion during an upgrade.

In production, we strongly recommend you set the and path.logs in elasticsearch.yml to locations outside of $ES_HOME.

Docker, Debian, RPM, macOS Homebrew, and Windows .msi installations write data and log to locations outside of $ES_HOME by default.

Supported and path.logs values vary by platform:

Linux and macOS installations support Unix-style paths:

  data: /var/data/elasticsearch
  logs: /var/log/elasticsearch

If needed, you can specify multiple paths in Elasticsearch stores the node’s data across all provided paths but keeps each shard’s data on the same path.

Elasticsearch does not balance shards across a node’s data paths. High disk usage in a single path can trigger a high disk usage watermark for the entire node. If triggered, Elasticsearch will not add shards to the node, even if the node’s other paths have available disk space. If you need additional disk space, we recommend you add a new node rather than additional data paths.

Linux and macOS installations support multiple Unix-style paths in

    - /mnt/elasticsearch_1
    - /mnt/elasticsearch_2
    - /mnt/elasticsearch_3

Cluster name settingedit

A node can only join a cluster when it shares its with all the other nodes in the cluster. The default name is elasticsearch, but you should change it to an appropriate name that describes the purpose of the cluster. logging-prod

Do not reuse the same cluster names in different environments. Otherwise, nodes might join the wrong cluster.

Node name settingedit

Elasticsearch uses as a human-readable identifier for a particular instance of Elasticsearch. This name is included in the response of many APIs. The node name defaults to the hostname of the machine when Elasticsearch starts, but can be configured explicitly in elasticsearch.yml: prod-data-2

Network host settingedit

By default, Elasticsearch binds to loopback addresses only such as and [::1]. This binding is sufficient to run a single development node on a server.

more than one node can be started from the same $ES_HOME location on a single node. This setup can be useful for testing Elasticsearch’s ability to form clusters, but it is not a configuration recommended for production.

To form a cluster with nodes on other servers, your node will need to bind to a non-loopback address. While there are many network settings, usually all you need to configure is

The setting also understands some special values such as _local_, _site_, _global_ and modifiers like :ip4 and :ip6. See Special values for

When you provide a custom setting for, Elasticsearch assumes that you are moving from development mode to production mode, and upgrades a number of system startup checks from warnings to exceptions. See the differences between development and production modes.

Discovery and cluster formation settingsedit

Configure two important discovery and cluster formation settings before going to production so that nodes in the cluster can discover each other and elect a master node.


Out of the box, without any network configuration, Elasticsearch will bind to the available loopback addresses and scan local ports 9300 to 9305 to connect with other nodes running on the same server. This behavior provides an auto-clustering experience without having to do any configuration.

When you want to form a cluster with nodes on other hosts, use the static discovery.seed_hosts setting. This setting provides a list of other nodes in the cluster that are master-eligible and likely to be live and contactable to seed the discovery process. This setting accepts a YAML sequence or array of the addresses of all the master-eligible nodes in the cluster. Each address can be either an IP address or a hostname that resolves to one or more IP addresses via DNS.

   - [0:0:0:0:0:ffff:c0a8:10c]:9301 

The port is optional and defaults to 9300, but can be overridden.

If a hostname resolves to multiple IP addresses, the node will attempt to discover other nodes at all resolved addresses.

IPv6 addresses must be enclosed in square brackets.

If your master-eligible nodes do not have fixed names or addresses, use an alternative hosts provider to find their addresses dynamically.


When you start an Elasticsearch cluster for the first time, a cluster bootstrapping step determines the set of master-eligible nodes whose votes are counted in the first election. In development mode, with no discovery settings configured, this step is performed automatically by the nodes themselves.

Because auto-bootstrapping is inherently unsafe, when starting a new cluster in production mode, you must explicitly list the master-eligible nodes whose votes should be counted in the very first election. You set this list using the cluster.initial_master_nodes setting.

After the cluster forms successfully for the first time, remove the cluster.initial_master_nodes setting from each nodes' configuration. Do not use this setting when restarting a cluster or adding a new node to an existing cluster.

   - [0:0:0:0:0:ffff:c0a8:10c]:9301
   - master-node-a
   - master-node-b
   - master-node-c

Identify the initial master nodes by their, which defaults to their hostname. Ensure that the value in cluster.initial_master_nodes matches the exactly. If you use a fully-qualified domain name (FQDN) such as for your node names, then you must use the FQDN in this list. Conversely, if is a bare hostname without any trailing qualifiers, you must also omit the trailing qualifiers in cluster.initial_master_nodes.

See bootstrapping a cluster and discovery and cluster formation settings.

Heap size settingsedit

By default, Elasticsearch tells the JVM to use a heap with a minimum and maximum size of 1 GB. When moving to production, it is important to configure heap size to ensure that Elasticsearch has enough heap available.

Elasticsearch will assign the entire heap specified in jvm.options via the Xms (minimum heap size) and Xmx (maximum heap size) settings. These two settings must be equal to each other.

The value for these settings depends on the amount of RAM available on your server:

  • Set Xmx and Xms to no more than 50% of your physical RAM. Elasticsearch requires memory for purposes other than the JVM heap and it is important to leave space for this. For instance, Elasticsearch uses off-heap buffers for efficient network communication, relies on the operating system’s filesystem cache for efficient access to files, and the JVM itself requires some memory too. It is normal to observe the Elasticsearch process using more memory than the limit configured with the Xmx setting.
  • Set Xmx and Xms to no more than the threshold that the JVM uses for compressed object pointers (compressed oops). The exact threshold varies but is near 32 GB. You can verify that you are under the threshold by looking for a line in the logs like the following:

    heap size [1.9gb], compressed ordinary object pointers [true]
  • Set Xmx and Xms to no more than the threshold for zero-based compressed oops. The exact threshold varies but 26 GB is safe on most systems and can be as large as 30 GB on some systems. You can verify that you are under this threshold by starting Elasticsearch with the JVM options -XX:+UnlockDiagnosticVMOptions -XX:+PrintCompressedOopsMode and looking for a line like the following:

    heap address: 0x000000011be00000, size: 27648 MB, zero based Compressed Oops

    This line shows that zero-based compressed oops are enabled. If zero-based compressed oops are not enabled, you’ll see a line like the following instead:

    heap address: 0x0000000118400000, size: 28672 MB, Compressed Oops with base: 0x00000001183ff000

The more heap available to Elasticsearch, the more memory it can use for its internal caches, but the less memory it leaves available for the operating system to use for the filesystem cache. Also, larger heaps can cause longer garbage collection pauses.

Here is an example of how to set the heap size via a jvm.options.d/ file:


Set the minimum heap size to 2g.

Set the maximum heap size to 2g.

Using jvm.options.d is the preferred method for configuring the heap size for production deployments.

It is also possible to set the heap size via the ES_JAVA_OPTS environment variable. This is generally discouraged for production deployments but is useful for testing because it overrides all other means of setting JVM options.

ES_JAVA_OPTS="-Xms2g -Xmx2g" ./bin/elasticsearch 
ES_JAVA_OPTS="-Xms4000m -Xmx4000m" ./bin/elasticsearch 

Set the minimum and maximum heap size to 2 GB.

Set the minimum and maximum heap size to 4000 MB.

Configuring the heap for the Windows service is different than the above. The values initially populated for the Windows service can be configured as above but are different after the service has been installed. Consult the Windows service documentation for additional details.

JVM heap dump path settingedit

By default, Elasticsearch configures the JVM to dump the heap on out of memory exceptions to the default data directory. On RPM and Debian packages, the data directory is /var/lib/elasticsearch. On Linux and MacOS and Windows distributions, the data directory is located under the root of the Elasticsearch installation.

If this path is not suitable for receiving heap dumps, modify the -XX:HeapDumpPath=... entry in jvm.options:

  • If you specify a directory, the JVM will generate a filename for the heap dump based on the PID of the running instance.
  • If you specify a fixed filename instead of a directory, the file must not exist when the JVM needs to perform a heap dump on an out of memory exception. Otherwise, the heap dump will fail.

GC logging settingsedit

By default, Elasticsearch enables garbage collection (GC) logs. These are configured in jvm.options and output to the same default location as the Elasticsearch logs. The default configuration rotates the logs every 64 MB and can consume up to 2 GB of disk space.

You can reconfigure JVM logging using the command line options described in JEP 158: Unified JVM Logging. Unless you change the default jvm.options file directly, the Elasticsearch default configuration is applied in addition to your own settings. To disable the default configuration, first disable logging by supplying the -Xlog:disable option, then supply your own command line options. This disables all JVM logging, so be sure to review the available options and enable everything that you require.

To see further options not contained in the original JEP, see Enable Logging with the JVM Unified Logging Framework.


Change the default GC log output location to /opt/my-app/gc.log by creating $ES_HOME/config/jvm.options.d/gc.options with some sample options:

# Turn off all previous logging configuratons

# Default settings from JEP 158, but with `utctime` instead of `uptime` to match the next line

# Enable GC logging to a custom location with a variety of options

Configure an Elasticsearch Docker container to send GC debug logs to standard error (stderr). This lets the container orchestrator handle the output. If using the ES_JAVA_OPTS environment variable, specify:

MY_OPTS="-Xlog:disable -Xlog:all=warning:stderr:utctime,level,tags -Xlog:gc=debug:stderr:utctime"
docker run -e ES_JAVA_OPTS="$MY_OPTS" # etc

Temporary directory settingsedit

By default, Elasticsearch uses a private temporary directory that the startup script creates immediately below the system temporary directory.

On some Linux distributions, a system utility will clean files and directories from /tmp if they have not been recently accessed. This behavior can lead to the private temporary directory being removed while Elasticsearch is running if features that require the temporary directory are not used for a long time. Removing the private temporary directory causes problems if a feature that requires this directory is subsequently used.

If you install Elasticsearch using the .deb or .rpm packages and run it under systemd, the private temporary directory that Elasticsearch uses is excluded from periodic cleanup.

If you intend to run the .tar.gz distribution on Linux or MacOS for an extended period, consider creating a dedicated temporary directory for Elasticsearch that is not under a path that will have old files and directories cleaned from it. This directory should have permissions set so that only the user that Elasticsearch runs as can access it. Then, set the $ES_TMPDIR environment variable to point to this directory before starting Elasticsearch.

JVM fatal error log settingedit

By default, Elasticsearch configures the JVM to write fatal error logs to the default logging directory. On RPM and Debian packages, this directory is /var/log/elasticsearch. On Linux and MacOS and Windows distributions, the logs directory is located under the root of the Elasticsearch installation.

These are logs produced by the JVM when it encounters a fatal error, such as a segmentation fault. If this path is not suitable for receiving logs, modify the -XX:ErrorFile=... entry in jvm.options.

Cluster backupsedit

In a disaster, snapshots can prevent permanent data loss. Snapshot lifecycle management is the easiest way to take regular backups of your cluster. For more information, see Back up a cluster.

You cannot back up an Elasticsearch cluster by simply copying the data directories of all of its nodes. Elasticsearch may be making changes to the contents of its data directories while it is running; copying its data directories cannot be expected to capture a consistent picture of their contents. If you try to restore a cluster from such a backup, it may fail and report corruption and/or missing files. Alternatively, it may appear to have succeeded though it silently lost some of its data. The only reliable way to back up a cluster is by using the snapshot and restore functionality.