Important Elasticsearch configuration

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.

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 path.data and path.logs in elasticsearch.yml to locations outside of $ES_HOME. Docker, Debian, and RPM installations write data and log to locations outside of $ES_HOME by default.

Supported path.data and path.logs values vary by platform:

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

path:
  data: "C:\\Elastic\\Elasticsearch\\data"
  logs: "C:\\Elastic\\Elasticsearch\\logs"

If needed, you can specify multiple paths in path.data. 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.

path:
  data:
    - /mnt/elasticsearch_1
    - /mnt/elasticsearch_2
    - /mnt/elasticsearch_3

path:
  data:
    - "C:\\Elastic\\Elasticsearch_1"
    - "E:\\Elastic\\Elasticsearch_1"
    - "F:\\Elastic\\Elasticsearch_3"

Support for multiple data paths was deprecated in 7.13 and will be removed in a future release.

As an alternative to multiple data paths, you can create a filesystem which spans multiple disks with a hardware virtualisation layer such as RAID, or a software virtualisation layer such as Logical Volume Manager (LVM) on Linux or Storage Spaces on Windows. If you wish to use multiple data paths on a single machine then you must run one node for each data path.

If you currently use multiple data paths in a highly available cluster then you can migrate to a setup that uses a single path for each node without downtime using a process similar to a rolling restart: shut each node down in turn and replace it with one or more nodes each configured to use a single data path. In more detail, for each node that currently has multiple data paths you should follow the following process. In principle you can perform this migration during a rolling upgrade to 8.0, but we recommend migrating to a single-data-path setup before starting to upgrade.

You can alternatively add some number of single-data-path nodes to your cluster, migrate all your data over to these new nodes using allocation filters, and then remove the old nodes from the cluster. This approach will temporarily double the size of your cluster so it will only work if you have the capacity to expand your cluster like this.

If you currently use multiple data paths but your cluster is not highly available then the you can migrate to a non-deprecated configuration by taking a snapshot, creating a new cluster with the desired configuration and restoring the snapshot into it.

A node can only join a cluster when it shares its cluster.name 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.

cluster.name: logging-prod

Elasticsearch uses node.name 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:

node.name: prod-data-2

By default, Elasticsearch only binds to loopback addresses such as 127.0.0.1 and [::1]. This is sufficient to run a cluster of one or more nodes on a single server for development and testing, but a resilient production cluster must involve nodes on other servers. There are many network settings but usually all you need to configure is network.host:

network.host: 192.168.1.10

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.

discovery.seed_hosts:
   - 192.168.1.10:9300
   - 192.168.1.11 
   - seeds.mydomain.com 
   - [0:0:0:0:0:ffff:c0a8:10c]:9301 

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.

discovery.seed_hosts:
   - 192.168.1.10:9300
   - 192.168.1.11
   - seeds.mydomain.com
   - [0:0:0:0:0:ffff:c0a8:10c]:9301
cluster.initial_master_nodes: 
   - master-node-a
   - master-node-b
   - master-node-c

See bootstrapping a cluster and discovery and cluster formation settings.

By default, Elasticsearch automatically sets the JVM heap size based on a node’s roles and total memory. We recommend the default sizing for most production environments.

If needed, you can override the default sizing by manually setting the JVM heap size.

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:

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
-Xlog:disable

# Default settings from JEP 158, but with `utctime` instead of `uptime` to match the next line
-Xlog:all=warning:stderr:utctime,level,tags

# Enable GC logging to a custom location with a variety of options
-Xlog:gc*,gc+age=trace,safepoint:file=/opt/my-app/gc.log:utctime,pid,tags:filecount=32,filesize=64m

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

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.

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.

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 Create a snapshot.