Rolling upgradesedit

A rolling upgrade allows an Elasticsearch cluster to be upgraded one node at a time so upgrading does not interrupt service. Running multiple versions of Elasticsearch in the same cluster beyond the duration of an upgrade is not supported, as shards cannot be replicated from upgraded nodes to nodes running the older version.

Rolling upgrades can be performed between minor versions. Elasticsearch 6.x supports rolling upgrades from Elasticsearch 5.6. Upgrading from earlier 5.x versions requires a full cluster restart. You must reindex to upgrade from versions prior to 5.x.

If the Elasticsearch security features are enabled on your 5.x cluster, before you can do a rolling upgrade you must encrypt the internode-communication with SSL/TLS, which requires a full cluster restart. For more information about this requirement and the associated bootstrap check, see SSL/TLS check.

The format used for the internal indices used by Kibana and X-Pack has changed in 6.x. When upgrading from 5.6 to 6.x, these internal indices have to be upgraded before the rolling upgrade procedure can start. Otherwise the upgraded node will refuse to join the cluster.

To perform a rolling upgrade:

  1. Disable shard allocation.

    When you shut down a node, the allocation process waits for index.unassigned.node_left.delayed_timeout (by default, one minute) before starting to replicate the shards on that node to other nodes in the cluster, which can involve a lot of I/O. Since the node is shortly going to be restarted, this I/O is unnecessary. You can avoid racing the clock by disabling allocation of replicas before shutting down the node:

    PUT _cluster/settings
      "persistent": {
        "cluster.routing.allocation.enable": "primaries"
  2. Stop non-essential indexing and perform a synced flush. (Optional)

    While you can continue indexing during the upgrade, shard recovery is much faster if you temporarily stop non-essential indexing and perform a synced-flush.

    POST _flush/synced

    When you perform a synced flush, check the response to make sure there are no failures. Synced flush operations that fail due to pending indexing operations are listed in the response body, although the request itself still returns a 200 OK status. If there are failures, reissue the request.

  3. Stop any machine learning jobs that are running.

    If your machine learning indices were created earlier than the previous major version, they must be reindexed. In those circumstances, there must be no machine learning jobs running during the upgrade.

    In all other circumstances, there is no requirement to close your machine learning jobs. There are, however, advantages to doing so. If you choose to leave your jobs running during the upgrade, they are affected when you stop the machine learning nodes. The jobs move to another machine learning node and restore the model states. This scenario has the least disruption to the active machine learning jobs but incurs the highest load on the cluster.

    To close all machine learning jobs before you upgrade, see Stopping machine learning. This method persists the model state at the moment of closure, which means that when you open your jobs after the upgrade, they use the exact same model. This scenario takes the most time, however, especially if you have many jobs or jobs with large model states.

    To temporarily halt the tasks associated with your machine learning jobs and datafeeds and prevent new jobs from opening, use the set upgrade mode API:

    POST _ml/set_upgrade_mode?enabled=true

    This method does not persist the absolute latest model state, rather it uses the last model state that was automatically saved. By halting the tasks, you avoid incurring the cost of managing active jobs during the upgrade and it’s quicker than stopping datafeeds and closing jobs.

  4. Shut down a single node.

    • If you are running Elasticsearch with systemd:

      sudo systemctl stop elasticsearch.service
    • If you are running Elasticsearch with SysV init:

      sudo -i service elasticsearch stop
    • If you are running Elasticsearch as a daemon:

      kill $(cat pid)
  5. Upgrade the node you shut down.

    If you are upgrading from a version prior to 6.3 and use X-Pack then you must remove the X-Pack plugin before upgrading with bin/elasticsearch-plugin remove x-pack. As of 6.3, X-Pack is included in the default distribution so make sure to upgrade to that one. If you upgrade without removing the X-Pack plugin first the node will fail to start. If you did not remove the X-Pack plugin and the node fails to start then you must downgrade to your previous version, remove X-Pack, and then upgrade again. In general downgrading is not supported but in this particular case it is.

    To upgrade using a Debian or RPM package:

    • Use rpm or dpkg to install the new package. All files are installed in the appropriate location for the operating system and Elasticsearch config files are not overwritten.

    To upgrade using a zip or compressed tarball:

    1. Extract the zip or tarball to a new directory. This is critical if you are not using external config and data directories.
    2. Set the ES_PATH_CONF environment variable to specify the location of your external config directory and jvm.options file. If you are not using an external config directory, copy your old configuration over to the new installation.
    3. Set in config/elasticsearch.yml to point to your external data directory. If you are not using an external data directory, copy your old data directory over to the new installation.

      If you use X-Pack monitoring, re-use the data directory when you upgrade Elasticsearch. Monitoring identifies unique Elasticsearch nodes by using the persistent UUID, which is stored in the data directory.

    4. Set path.logs in config/elasticsearch.yml to point to the location where you want to store your logs. If you do not specify this setting, logs are stored in the directory you extracted the archive to.

    When you extract the zip or tarball packages, the elasticsearch-n.n.n directory contains the Elasticsearch config, data, and logs directories.

    We recommend moving these directories out of the Elasticsearch directory so that there is no chance of deleting them when you upgrade Elasticsearch. To specify the new locations, use the ES_PATH_CONF environment variable and the and path.logs settings. For more information, see Important Elasticsearch configuration.

    The Debian and RPM packages place these directories in the appropriate place for each operating system. In production, we recommend installing using the deb or rpm package.

  6. Upgrade any plugins.

    Use the elasticsearch-plugin script to install the upgraded version of each installed Elasticsearch plugin. All plugins must be upgraded when you upgrade a node.

  7. Start the upgraded node.

    Start the newly-upgraded node and confirm that it joins the cluster by checking the log file or by submitting a _cat/nodes request:

    GET _cat/nodes
  8. Reenable shard allocation.

    Once the node has joined the cluster, remove the cluster.routing.allocation.enable setting to enable shard allocation and start using the node:

    PUT _cluster/settings
      "persistent": {
        "cluster.routing.allocation.enable": null
  9. Wait for the node to recover.

    Before upgrading the next node, wait for the cluster to finish shard allocation. You can check progress by submitting a _cat/health request:

    GET _cat/health?v

    Wait for the status column to switch to green. Once the node is green, all primary and replica shards have been allocated.

    During a rolling upgrade, primary shards assigned to a node running the new version cannot have their replicas assigned to a node with the old version. The new version might have a different data format that is not understood by the old version.

    If it is not possible to assign the replica shards to another node (there is only one upgraded node in the cluster), the replica shards remain unassigned and status stays yellow.

    In this case, you can proceed once there are no initializing or relocating shards (check the init and relo columns).

    As soon as another node is upgraded, the replicas can be assigned and the status will change to green.

    Shards that were not sync-flushed might take longer to recover. You can monitor the recovery status of individual shards by submitting a _cat/recovery request:

    GET _cat/recovery

    If you stopped indexing, it is safe to resume indexing as soon as recovery completes.

  10. Repeat

    When the node has recovered and the cluster is stable, repeat these steps for each node that needs to be updated. You can monitor the health of the cluster with a _cat/health request:

    GET /_cat/health?v

    And check which nodes have been upgraded with a _cat/nodes request:

    GET /_cat/nodes?h=ip,name,version&v
  11. Restart machine learning jobs.

    If you closed all machine learning jobs before the upgrade, you must open them. Use Kibana or the open jobs API.

    Alternatively, if you temporarily halted the tasks associated with your machine learning jobs, use the set upgrade mode API to return them to active states:

    POST _ml/set_upgrade_mode?enabled=false

During a rolling upgrade, the cluster continues to operate normally. However, any new functionality is disabled or operates in a backward compatible mode until all nodes in the cluster are upgraded. New functionality becomes operational once the upgrade is complete and all nodes are running the new version. Once that has happened, there’s no way to return to operating in a backward compatible mode. Nodes running the previous major version will not be allowed to join the fully-updated cluster.

In the unlikely case of a network malfunction during the upgrade process that isolates all remaining old nodes from the cluster, you must take the old nodes offline and upgrade them to enable them to join the cluster.

[1] You must delete or reindex any indices created in 2.x before upgrading.