Fix common cluster issuesedit
This 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.