Write hotspotting

Write work is backing up on a subset of write-eligible nodes while peer nodes in the same eligible set still have spare capacity. This usually points to uneven shard placement or competing search and indexing work on the busy nodes, which raises ingest latency and leaves available write capacity unused.

Note

For a complete list of insights, refer to AutoOps insights.

Field Value
Component Elasticsearch
Severity Medium
Scope Node
Domains performance, search, indexing, resource-utilization, shard-allocation

You can customize these settings to adjust when AutoOps detects this event and presents the insight. Refer to AutoOps event settings for details.

The default customization settings are:

Setting Type Default
Write queue threshold to count a node as overloaded Integer 50
Consecutive samples meeting the imbalance conditions Integer 3
Tip

Raising these thresholds reduces noise but delays detection. Lowering them triggers the insight sooner but can increase alerts during minor blips.

The following is an example of what you might see when this insight is triggered. Real insights use live data and links from your deployment or cluster.

The write thread pool queue is elevated on es-data-01 and es-data-02 while other write-eligible nodes in the same set have no writes waiting.

  • Indices with high indexing activity: logs-prod-000045

  • Indices with high search activity on the same nodes: logs-prod-000045

Related open insights on these nodes:

  • Disk watermark flood stage

  • Deployment not highly available

Inspect open insights

Note

AutoOps shows different recommendations depending on how their conditions match your deployment or cluster.

A write hotspot happens when indexing pressure concentrates on a few write-eligible nodes instead of being spread across the tier. This often reflects uneven shard placement, hot shards, or competing search, merge, and indexing work on the same nodes.

If the imbalance persists, ingest latency rises on the busy nodes, write queues can grow into rejections, and searches on those nodes can also slow down. Other write-eligible nodes stay underused, so the problem is distribution of work rather than uniform cluster-wide saturation.

Hotspotting