Upgrade Elasticsearch

Disable shard allocation.

When you shut down a data 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 data nodes:

PUT _cluster/settings
{
  "persistent": {
    "cluster.routing.allocation.enable": "primaries"
  }
}

Stop non-essential indexing and perform a 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 flush.

POST /_flush

Temporarily stop the tasks associated with active machine learning jobs and datafeeds. (Optional)

It is possible to leave your machine learning jobs running during the upgrade, but it puts increased load on the cluster. When you shut down a machine learning node, its jobs automatically move to another node and restore the model states.

Shut down a single node.

To shut down a single node depends on what is currently used to run Elasticsearch. For example, if using systemd or SysV init run the commands below.

Upgrade the node you shut down.

To upgrade using a Debian or RPM package:

To upgrade using a zip or compressed tarball:

Leave cluster.initial_master_nodes unset when performing a rolling upgrade. Each upgraded node is joining an existing cluster so there is no need for cluster bootstrapping. You must configure either discovery.seed_hosts or discovery.seed_providers on every node.

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.

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

Reenable shard allocation.

For data nodes, 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
  }
}

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=true

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

Shards that were not 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.

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=true

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

GET /_cat/nodes?h=ip,name,version&v=true

Restart machine learning jobs.

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

If you closed all machine learning jobs before the upgrade, open the jobs and start the datafeeds from Kibana or with the open jobs and start datafeed APIs.