Red or yellow cluster health status

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A red or yellow cluster health status indicates one or more shards are not assigned to a node.

  • Red health status: The cluster has some unassigned primary shards, which means that some operations such as searches and indexing may fail.
  • Yellow health status: The cluster has no unassigned primary shards but some unassigned replica shards. This increases your risk of data loss and can degrade cluster performance.

When your cluster has a red or yellow health status, it will continue to process searches and indexing where possible, but may delay certain management and cleanup activities until the cluster returns to green health status. For instance, some ILM actions require the index on which they operate to have a green health status.

In many cases, your cluster will recover to green health status automatically. If the cluster doesn’t automatically recover, then you must manually address the remaining problems so management and cleanup activities can proceed.

Diagnose your cluster status

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Check your cluster status

Use the cluster health API.

response = client.cluster.health(
  filter_path: 'status,*_shards'
)
puts response
GET _cluster/health?filter_path=status,*_shards

A healthy cluster has a green status and zero unassigned_shards. A yellow status means only replicas are unassigned. A red status means one or more primary shards are unassigned.

View unassigned shards

To view unassigned shards, use the cat shards API.

response = client.cat.shards(
  v: true,
  h: 'index,shard,prirep,state,node,unassigned.reason',
  s: 'state'
)
puts response
GET _cat/shards?v=true&h=index,shard,prirep,state,node,unassigned.reason&s=state

Unassigned shards have a state of UNASSIGNED. The prirep value is p for primary shards and r for replicas.

To understand why an unassigned shard is not being assigned and what action you must take to allow Elasticsearch to assign it, use the cluster allocation explanation API.

response = client.cluster.allocation_explain(
  filter_path: 'index,node_allocation_decisions.node_name,node_allocation_decisions.deciders.*',
  body: {
    index: 'my-index',
    shard: 0,
    primary: false
  }
)
puts response
GET _cluster/allocation/explain?filter_path=index,node_allocation_decisions.node_name,node_allocation_decisions.deciders.*
{
  "index": "my-index",
  "shard": 0,
  "primary": false
}

Fix a red or yellow cluster status

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A shard can become unassigned for several reasons. The following tips outline the most common causes and their solutions.

Re-enable shard allocation
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You typically disable allocation during a restart or other cluster maintenance. If you forgot to re-enable allocation afterward, Elasticsearch will be unable to assign shards. To re-enable allocation, reset the cluster.routing.allocation.enable cluster setting.

response = client.cluster.put_settings(
  body: {
    persistent: {
      'cluster.routing.allocation.enable' => nil
    }
  }
)
puts response
PUT _cluster/settings
{
  "persistent" : {
    "cluster.routing.allocation.enable" : null
  }
}
Recover lost nodes
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Shards often become unassigned when a data node leaves the cluster. This can occur for several reasons, ranging from connectivity issues to hardware failure. After you resolve the issue and recover the node, it will rejoin the cluster. Elasticsearch will then automatically allocate any unassigned shards.

To avoid wasting resources on temporary issues, Elasticsearch delays allocation by one minute by default. If you’ve recovered a node and don’t want to wait for the delay period, you can call the cluster reroute API with no arguments to start the allocation process. The process runs asynchronously in the background.

response = client.cluster.reroute(
  metric: 'none'
)
puts response
POST _cluster/reroute?metric=none
Fix allocation settings
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Misconfigured allocation settings can result in an unassigned primary shard. These settings include:

To review your allocation settings, use the get index settings and cluster get settings APIs.

response = client.indices.get_settings(
  index: 'my-index',
  flat_settings: true,
  include_defaults: true
)
puts response

response = client.cluster.get_settings(
  flat_settings: true,
  include_defaults: true
)
puts response
GET my-index/_settings?flat_settings=true&include_defaults=true

GET _cluster/settings?flat_settings=true&include_defaults=true

You can change the settings using the update index settings and cluster update settings APIs.

Allocate or reduce replicas
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To protect against hardware failure, Elasticsearch will not assign a replica to the same node as its primary shard. If no other data nodes are available to host the replica, it remains unassigned. To fix this, you can:

  • Add a data node to the same tier to host the replica.
  • Change the index.number_of_replicas index setting to reduce the number of replicas for each primary shard. We recommend keeping at least one replica per primary.
response = client.indices.put_settings(
  body: {
    'index.number_of_replicas' => 1
  }
)
puts response
PUT _settings
{
  "index.number_of_replicas": 1
}
Free up or increase disk space
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Elasticsearch uses a low disk watermark to ensure data nodes have enough disk space for incoming shards. By default, Elasticsearch does not allocate shards to nodes using more than 85% of disk space.

To check the current disk space of your nodes, use the cat allocation API.

response = client.cat.allocation(
  v: true,
  h: 'node,shards,disk.*'
)
puts response
GET _cat/allocation?v=true&h=node,shards,disk.*

If your nodes are running low on disk space, you have a few options:

  • Upgrade your nodes to increase disk space.
  • Delete unneeded indices to free up space. If you use ILM, you can update your lifecycle policy to use searchable snapshots or add a delete phase. If you no longer need to search the data, you can use a snapshot to store it off-cluster.
  • If you no longer write to an index, use the force merge API or ILM’s force merge action to merge its segments into larger ones.

    response = client.indices.forcemerge(
      index: 'my-index'
    )
    puts response
    POST my-index/_forcemerge
  • If an index is read-only, use the shrink index API or ILM’s shrink action to reduce its primary shard count.

    response = client.indices.shrink(
      index: 'my-index',
      target: 'my-shrunken-index'
    )
    puts response
    POST my-index/_shrink/my-shrunken-index
  • If your node has a large disk capacity, you can increase the low disk watermark or set it to an explicit byte value.

    PUT _cluster/settings
    {
      "persistent": {
        "cluster.routing.allocation.disk.watermark.low": "30gb"
      }
    }
Reduce JVM memory pressure
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Shard allocation requires JVM heap memory. High JVM memory pressure can trigger circuit breakers that stop allocation and leave shards unassigned. See High JVM memory pressure.

Recover data for a lost primary shard
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If a node containing a primary shard is lost, Elasticsearch can typically replace it using a replica on another node. If you can’t recover the node and replicas don’t exist or are irrecoverable, you’ll need to re-add the missing data from a snapshot or the original data source.

Only use this option if node recovery is no longer possible. This process allocates an empty primary shard. If the node later rejoins the cluster, Elasticsearch will overwrite its primary shard with data from this newer empty shard, resulting in data loss.

Use the cluster reroute API to manually allocate the unassigned primary shard to another data node in the same tier. Set accept_data_loss to true.

POST _cluster/reroute?metric=none
{
  "commands": [
    {
      "allocate_empty_primary": {
        "index": "my-index",
        "shard": 0,
        "node": "my-node",
        "accept_data_loss": "true"
      }
    }
  ]
}

If you backed up the missing index data to a snapshot, use the restore snapshot API to restore the individual index. Alternatively, you can index the missing data from the original data source.