IMPORTANT: No additional bug fixes or documentation updates
will be released for this version. For the latest information, see the
current release documentation.
Fix common cluster issues
editFix common cluster issues
editThis guide describes how to fix common errors and problems with Elasticsearch clusters.
- Watermark errors
- Fix watermark errors that occur when a data node is critically low on disk space and has reached the flood-stage disk usage watermark.
- Circuit breaker errors
- Elasticsearch uses circuit breakers to prevent nodes from running out of JVM heap memory. If Elasticsearch estimates an operation would exceed a circuit breaker, it stops the operation and returns an error.
- High CPU usage
- The most common causes of high CPU usage and their solutions.
- High JVM memory pressure
- High JVM memory usage can degrade cluster performance and trigger circuit breaker errors.
- Red or yellow cluster status
- A red or yellow cluster status indicates one or more shards are missing or unallocated. These unassigned shards increase your risk of data loss and can degrade cluster performance.
- Rejected requests
-
When Elasticsearch rejects a request, it stops the operation and returns an error with a
429response code. - Task queue backlog
- A backlogged task queue can prevent tasks from completing and put the cluster into an unhealthy state.
- Diagnose unassigned shards
- There are multiple reasons why shards might get unassigned, ranging from misconfigured allocation settings to lack of disk space.
- Troubleshooting an unstable cluster
- A cluster in which nodes leave unexpectedly is unstable and can create several issues.
- Mapping explosion
- A cluster in which an index or index pattern as exploded with a high count of mapping fields which causes performance look-up issues for Elasticsearch and Kibana.
- Hot spotting
- Hot spotting may occur in Elasticsearch when resource utilizations are unevenly distributed across nodes.