Before you dig into reading this guide, have you tried asking OpsGPT what this log means? You’ll receive a customized analysis of your log.
Try OpsGPT now for step-by-step guidance and tailored insights into your Elasticsearch operation.
Briefly, this error occurs when Elasticsearch is unable to update the cluster state due to issues like network problems, node failures, or insufficient resources. To resolve this, you can check the network connectivity between nodes, ensure all nodes are running and healthy, and verify that there are enough resources (CPU, memory, disk space) available. Additionally, check the Elasticsearch logs for more specific error messages that can help identify the root cause.
For a complete solution to your to your search operation, try for free AutoOps for Elasticsearch & OpenSearch . With AutoOps and Opster’s proactive support, you don’t have to worry about your search operation – we take charge of it. Get improved performance & stability with less hardware.
This guide will help you check for common problems that cause the log ” failed to publish cluster state ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: discovery, cluster.
Overview
The process known as discovery occurs when an Elasticsearch node starts, restarts or loses contact with the master node for any reason. In those cases, the node needs to contact other nodes in the cluster to find any existing master node or initiate the election of a new master node.
How it works
Upon startup, each node looks for other nodes, firstly by contacting the IP addresses of eligible master nodes held in the previous cluster state. If they are not available, it will look for nodes based upon the seed host provider mechanisms available.
Seed host providers may be defined in 3 ways: list based, file based or plugin based. All of these methods provide a list of IP addresses or hostnames which the node should contact in order to obtain a list of master eligible nodes. The node will contact all of these addresses in turn, until either an active master is found, or failing that, until sufficient nodes can be found to elect a new master node.
Examples
The simplest form is to define a list of seed host providers in elasticsearch.yml:
discovery.seed_hosts: - 192.168.1.10:9300 - 192.168.1.11 - seeds.mydomain.com
An alternative way is to refer to a file using the following setting:
discovery.seed_providers: file
The file MUST be placed in the following filepath: $ES_PATH_CONF/unicast_hosts.txt
10.10.10.5 10.10.10.6:9305 10.10.10.5:10005 # an IPv6 address [2001:0db8:85a3:0000:0000:8a2e:0370:7334]:9301
Note that the use of a port is optional. If not used, then the default port range of 9300-9400 will be used.
If you use AWS or GCS then you can install and use a plugin to obtain a list of seed hosts from an API. A plugin also exists for Azure but is deprecated since version 5.
AWS plugin
A typical configuration could be as follows:
discovery.seed_providers: ec2 discovery.ec2.tag.role: master discovery.ec2.tag.environment: dev discovery.ec2.endpoint: ec2.us-east-1.amazonaws.com cloud.node.auto_attributes: true cluster.routing.allocation.awareness.attributes: aws_availability_zone
The above configuration would look for all nodes with a tag called “environment” set to “dev” and a tag called “role” set to “master”, in the AWS zone us-east-1. The last two lines set up cluster routing allocation awareness based upon aws availability zones. (Not necessary, but nice to have).
GCE plugin
A typical configuration could be as follows:
discovery.seed_providers: gce cloud.gce.project_id: <your-google-project-id> cloud.gce.zone: <your-zone> discovery.gce.tags: <my-tag-name>
The above configuration would look for all virtual machines inside your project, zone and with a tag set to the tag name you provide.
Notes and good things to know
Cluster formation depends on correct setup of the network.host settings in elasticsearch.yml. Make sure that the nodes can reach each other across the network using their IP addresses / hostname, and are not getting blocked due to firewall settings on the ports required.
Overview
An Elasticsearch cluster consists of a number of servers (nodes) working together as one. Clustering is a technology which enables Elasticsearch to scale up to hundreds of nodes that together are able to store many terabytes of data and respond coherently to large numbers of requests at the same time.
Search or indexing requests will usually be load-balanced across the Elasticsearch data nodes, and the node that receives the request will relay requests to other nodes as necessary and coordinate the response back to the user.
Notes and good things to know
The key elements to clustering are:
Cluster State – Refers to information about which indices are in the cluster, their data mappings and other information that must be shared between all the nodes to ensure that all operations across the cluster are coherent.
Master Node – Each cluster must elect a single master node responsible for coordinating the cluster and ensuring that each node contains an up-to-date copy of the cluster state.
Cluster Formation – Elasticsearch requires a set of configurations to determine how the cluster is formed, which nodes can join the cluster, and how the nodes collectively elect a master node responsible for controlling the cluster state. These configurations are usually held in the elasticsearch.yml config file, environment variables on the node, or within the cluster state.
Node Roles – In small clusters it is common for all nodes to fill all roles; all nodes can store data, become master nodes or process ingestion pipelines. However as the cluster grows, it is common to allocate specific roles to specific nodes in order to simplify configuration and to make operation more efficient. In particular, it is common to define a limited number of dedicated master nodes.
Replication – Data may be replicated across a number of data nodes. This means that if one node goes down, data is not lost. It also means that a search request can be dealt with by more than one node.
Common problems
Many Elasticsearch problems are caused by operations which place an excessive burden on the cluster because they require an excessive amount of information to be held and transmitted between the nodes as part of the cluster state. For example:
- Shards too small
- Too many fields (field explosion)
Problems may also be caused by inadequate configurations causing situations where the Elasticsearch cluster is unable to safely elect a Master node. This situation is discussed further in:
Backups
Because Elasticsearch is a clustered technology, it is not sufficient to have backups of each node’s data directory. This is because the backups will have been made at different times and so there may not be complete coherency between them. As such, the only way to backup an Elasticsearch cluster is through the use of snapshots, which contain the full picture of an index at any one time.
Cluster resilience
When designing an Elasticsearch cluster, it is important to think about cluster resilience. In particular – what happens when a single node goes down? And for larger clusters where several nodes may share common services such as a network or power supply – what happens if that network or power supply goes down? This is where it is useful to ensure that the master eligible nodes are spread across availability zones, and to use shard allocation awareness to ensure that shards are spread across different racks or availability zones in your data center.
Log Context
Log “failed to publish cluster state” class name is ZenDiscovery.java. We extracted the following from Elasticsearch source code for those seeking an in-depth context :
newState.version();
electMaster.minimumMasterNodes()
); synchronized (stateMutex) {
pendingStatesQueue.failAllStatesAndClear(new ElasticsearchException("failed to publish cluster state")); rejoin("zen-disco-failed-to-publish");
} publishListener.onFailure(t);
