Fix common cluster issues
Use these topics to fix common issues with Elasticsearch clusters.
Tip
If you're using Elastic Cloud Hosted, you can use AutoOps to monitor your cluster. AutoOps significantly simplifies cluster management with performance recommendations, resource utilization visibility, and real-time issue detection with resolution paths. For more information, refer to AutoOps.
- 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.
- Symptom: 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 health 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.
- 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.