High memory-to-disk ratio on content nodes

Content-tier data nodes show a higher memory-to-disk ratio than the recommended range for that role. Content indices are often large and less search-heavy than hot tiers, so oversized heap is a common overspend.

Note

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

Field Value
Component Elasticsearch
Severity Low
Scope Node
Domains memory, resource-utilization

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
Disk-to-memory ratio threshold for content-tier data nodes Integer 30

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 memory-to-disk ratio is higher than needed on the following content nodes: es-data-01 and es-data-02.

For example, on es-data-01, allocated memory is 64 GB and allocated disk is 10240 GB, a memory-to-disk ratio of 1:160. A common target ratio for content nodes is 1:160.

Note

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

The memory-to-disk ratio compares heap size to disk capacity on a node. When the ratio is higher than the target for that role or tier, you pay for RAM that the disk-backed workload does not need.

Content tiers often hold large indices that are less search-intensive than hot data. Oversized heap relative to disk is a frequent source of unused capacity.

If the condition persists, cloud or license cost stays elevated without a matching gain in search or indexing capacity.