How To Solve Issues Related to Log – Updating number_of_replicas to for indices

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Updated: Jan-20

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Log Context
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Quick Overview

Elasticsearch replica shards can be updated dynamically both manually (by hitting API) or dynamically (based on the number of nodes and configuration) in order to improve search latency. A change in the number of replicas is a critical event, and Elasticsearch logs this event as below:

updating number_of_replicas to {new replicas number} for indices {affected indices list}.

Manual update: 

Using Index update setting for existing indices or Index template for a future index. The Elasticsearch class for executing these changes is 

Dynamic update: 

It’s common to upscale and downscale Elasticsearch clusters based on traffic, and for the same reason, having a fixed number of replicas isn’t very useful in cases like these. That’s why Elasticsearch came up with the concept of Index.auto_expand_replicas(default false), which can dynamically increase/decrease the number of replicas based on the configuration and number of nodes in the cluster


If configured (0-5), the number of allocated replicas will match the number of nodes you create. If you increase/decrease, these numbers will also be changed accordingly. Refer to Elasticsearch founder post and this official doc for more details.

org.elasticsearch.cluster.routing.allocation.AllocationService#adaptAutoExpandReplicas This method handles dynamically updating the replicas.

Bottom Line: 

This log is solely for information purposes and there’s nothing much to worry about with them, but if it changes without your knowledge,  there is a scope to take appropriate actions like:

Index.auto_expand_replicas : false


Changing the index template to make sure all future indices are not created with fixed settings

Troubleshooting background

To troubleshoot Elasticsearch log “Updating number_of_replicas to for indices” it’s important to understand common problems related to Elasticsearch concepts: allocation, cluster, indices, routing. See detailed explanations below complete with common problems, examples and useful tips.

Cluster in Elasticsearch

What is it

In Elasticsearch a cluster is a collection of one or more nodes (servers / VMs). A cluster can consist of an unlimited number of nodes. The cluster provides interface for indexing and storing data and search capability across all of the data which is stored in the data nodes

Each cluster has a single master node that is elected by the master eligible nodes. In cases where the master is not available the other connected master eligible nodes elect a new master. Clusters are identified by a unique name, which defaults to “Elasticsearch”.

Index in Elasticsearch

What it is

In Elasticsearch, an index (indices in plural) can be thought of as a table inside a database that has a schema and can have one or more shards and replicas. An Elasticsearch index is divided into shards and each shard is an instance of a Lucene index.

Indices are used to store the documents in dedicated data structures corresponding to the data type of fields. For example, text fields are stored inside an inverted index whereas numeric and geo fields are stored inside BKD trees.

Create Index

The following example is based on Elasticsearch version 5.x onwards. An index with two shards, each having one replica will be created with the name test_index1

PUT /test_index1?pretty
    "settings" : {
        "number_of_shards" : 2,
        "number_of_replicas" : 1
    "mappings" : {
        "properties" : {
            "tags" : { "type" : "keyword" },
            "updated_at" : { "type" : "date" }
List Indices

All the index names and their basic information can be retrieved using the following command:

GET _cat/indices?v
Index a document

Let’s add a document in the index with below command:

PUT test_index1/_doc/1
  "tags": [
  "date": "01-01-2020"
Query an index
GET test_index1/_search
  "query": {
    "match_all": {}
Query Multiple Indices

It is possible to search multiple indices with a single request. If it is a raw HTTP request, Index names should be sent in comma-separated format, as shown in the example below, and in the case of a query via a programming language client such as python or Java, index names are to be sent in a list format.

GET test_index1,test_index2/_search
Delete Indices
DELETE test_index1
Common Problems
  • It is good practice to define the settings and mapping of an Index wherever possible because if this is not done, Elasticsearch tries to automatically guess the data type of fields at the time of indexing. This automatic process may have disadvantages, such as mapping conflicts, duplicate data and incorrect data types being set in the index. If the fields are not known in advance, it’s better to use dynamic index templates.
  • Elasticsearch supports wildcard patterns in Index names, which sometimes aids with querying multiple indices, but can also be very destructive too. For example, It is possible to delete all the indices in a single command using the following commands:

To disable this, you can add the following lines in the elasticsearch.yml:

action.destructive_requires_name: true

To help troubleshoot related issues we have gathered selected Q&A from the community and issues from Github , please review the following for further information :

1 How to (persistently) update the index.number_of_replicas setting in Elasticsearch without restarting the cluster? 2 6.66 K 

2 Updating the default index number_of_replicas setting for new indices   12 14.40 K 

Log Context

Log ”Updating number_of_replicas to [{}] for indices {}” classname is
We have extracted the following from Elasticsearch source code to get an in-depth context :

                     final IndexMetaData indexMetaData = metaDataBuilder.get(index);
                    final IndexMetaData.Builder indexMetaDataBuilder =
                            new IndexMetaData.Builder(indexMetaData).settingsVersion(1 + indexMetaData.getSettingsVersion());
      "updating number_of_replicas to [{}] for indices {}"; numberOfReplicas; indices);
            final ClusterState fixedState = ClusterState.builder(clusterState).routingTable(
            assert AutoExpandReplicas.getAutoExpandReplicaChanges(fixedState.metaData(); fixedState.nodes()).isEmpty();
            return fixedState;

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