---
title: Node near out of memory
description: Describes what AutoOps detects and surfaces with the Node near out of memory insight: A node is under severe JVM memory pressure: heap use stays very high while garbage collection consumes much of the time.
url: https://docs-v3-preview.elastic.dev/elastic/autoops-insights/tree/main/elasticsearch/node_near_out_of_memory
products:
  - Elastic Cloud Enterprise
  - Elastic Cloud Hosted
  - Elastic Cloud on Kubernetes
  - Elasticsearch
applies_to:
  - Elastic Cloud Hosted: Generally available
  - Elastic Cloud on Kubernetes: Generally available
  - Elastic Cloud Enterprise: Generally available
  - Self-managed Elastic deployments: Generally available
---

# Node near out of memory
A node is under severe JVM memory pressure: heap use stays very high while garbage collection consumes much of the time. The node might slow down, reject work, or disconnect from the cluster.
<note>
  For a complete list of insights, refer to [AutoOps insights](https://docs-v3-preview.elastic.dev/elastic/autoops-insights/tree/main/elasticsearch).
</note>


## Insight details


| Field     | Value                          |
|-----------|--------------------------------|
| Component | Elasticsearch                  |
| Severity  | High                           |
| Scope     | Node                           |
| Domains   | performance, memory, stability |


## Example: What you might see in AutoOps

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.

### Node es-data-01 is almost out of memory


#### What was detected

High GC overhead on `es-data-01` and `es-data-02`. Heap utilization is 30%. GC ran for more than 50% of the time over the last 30 seconds.

#### Recommendations

<note>
  AutoOps shows different recommendations depending on how their conditions match your deployment or cluster.
</note>

<dropdown title="Restart es-data-01 node">
  **Condition**: Always shown for this insight.Restart the es-data-01 node to clear abnormal load and recover normal operation.
</dropdown>


#### Background and impact

When heap stays near full and collectors run most of the time, the JVM spends capacity reclaiming memory instead of serving search and indexing. Pause times grow, thread pools back up, and the node can become unresponsive or leave the cluster.
Typical drivers include heap sized too small for the workload, expensive queries and aggregations, large field data, shard over-allocation, and concurrent heavy operations. Sustained pressure raises the risk of out-of-memory failures and cluster instability.

## Guide

[High JVM memory pressure](https://docs-v3-preview.elastic.dev/elastic/docs-content/tree/main/troubleshoot/elasticsearch/high-jvm-memory-pressure)