Server hangs due to high uses CPU and memory by elasticsearch or kibana

Elastic Search
1

Kibana version:
9.5.0

Elasticsearch version:
9.5.0
Server OS version:
24.04.3 LTS (Noble Numbat)

Original install method (e.g. download page, yum, from source, etc.):
Docker

Describe the bug:
Kibana is consuming an unexpectedly high amount of memory when running in a Docker environment. Over time, Kibana's memory usage continues to increase, causing tasks to become stuck or remain incomplete.

As memory consumption reaches the available system/container limit, the server eventually triggers an Out-Of-Memory (OOM) condition and kills the Kibana process/container. This results in interrupted or stuck tasks and makes Kibana unavailable until the service is restarted.

The issue appears to be related to excessive or continuously increasing memory consumption by Kibana in the Docker environment
Steps to reproduce:

  1. Deploy Kibana in a Docker environment with the configured memory limits.
  2. Run Kibana and perform the required tasks/workload for an extended period.
  3. Monitor Kibana/container memory usage and observe that memory consumption progressively increases.
  4. Once available memory is exhausted, observe that tasks become stuck and the server/container experiences an OOM kill.

Expected behavior:
Kibana should manage memory efficiently and release memory when it is no longer required. Memory consumption should remain within the configured Docker/container limits, and tasks should continue to execute without becoming stuck.

Kibana should not cause the server or container to reach an OOM condition under the expected workload.
Screenshots (if relevant):

Image
Image842×181 36.3 KB

Image
Image648×732 128 KB

Errors in browser console (if relevant):

Provide logs and/or server output (if relevant):
Please refer the sceenshots
Any additional context:

  1. Kibana is running in a Docker environment.
  2. Memory consumption appears to increase significantly over time.
  3. Tasks become stuck when available memory becomes low.
  4. The server eventually performs an OOM kill due to memory exhaustion.
  5. Further investigation is required to determine whether the issue is caused by a Kibana memory leak, a specific workload/task, or insufficient Docker memory allocation.
2

@stephenb Can you please share your observation on this issue?

3

Hi @yogesh119905

It seems like you posted duplicate topics.

I am not sure if I have thoughts yet

Question, a couple key metrics / questions

What is the memory allocated to the container for Kibana / Elasticsearch.

Sorry I can not (and many other can not) ready the screen shoot of those numbers, especially with not explanation.

2GB is the recommended minimum

You can also limit the memory used.

What is the unexpectedly high that you're seeing? I don't see any of those stats in your post?

What's this working in previous versions?

What tests are you running against Kibana and Elasticsearch during this looks CI pipeline Alerting, workflows, SLOs etc

Let's get started with these things them perhaps we can work understanding of what's going on...

4

@stephenb We have used the following configuration in the Docker Compose file: 4 GB RAM and 2 vCPUs. we have initiated the installation of Kibana and Elasticsearch.

docker compose file

version: "2"
services:
elastic:
image: XXXXXXXX/elasticsearch/elasticsearch:9.5.0
container_name: elastic
environment:

  • node.name=log-01
  • cluster.name=logging-cluster
  • discovery.type=single-node
  • bootstrap.memory_lock=true
  • ELASTIC_PASSWORD=XXXX
  • "ES_JAVA_OPTS=-Xms512m -Xmx512m"
  • xpack.security.enabled=true
  • xpack.security.http.ssl.enabled=true
  • xpack.security.http.ssl.verification_mode=none
  • xpack.security.http.ssl.key=/usr/share/elasticsearch/config/ssl/XXXX.key
  • xpack.security.http.ssl.certificate=/usr/share/elasticsearch/config/ssl/XXXX.crt
    volumes:
  • /var/molecule-platform/logging-new/ssl:/usr/share/elasticsearch/config/ssl
  • /var/molecule-platform/logging-new/users:/usr/share/elasticsearch/config/users
  • /var/molecule-platform/logging-new/users_roles:/usr/share/elasticsearch/config/users_roles
    ulimits:
    memlock:
    soft: -1
    hard: -1
    ports:
  • "9200:9200"
    restart: unless-stopped
    kibana:
    image: XXXX/kibana/kibana:9.5.0
    container_name: kibana
    environment:
    ELASTICSEARCH_HOSTS: '["https://elastic:9200"]'
    volumes:
  • /var/molecule-platform/logging-new/ssl:/usr/share/kibana/config/ssl
  • /var/molecule-platform/logging-new/kibana/kibana.yml:/usr/share/kibana/config/kibana.yml
    ports:
  • "5601:5601"
    restart: unless-stopped

Below are the memory uses by container

Screenshot from 2026-08-24 10-09-30

What's this working in previous versions?
In previous version 9.4.3 we were facing similar issue some time but nowadays it is affected by almost everywhere.

What tests are you running against Kibana and Elasticsearch during this looks CI pipeline Alerting, workflows, SLOs etc?

We are initiating the installation of Elasticsearch and Kibana to verify whether our logging is working as expected.

5

Repeat: Posting images of text is discouraged, please just post the text.

That said Kibana is taking more resources these days. You can limit the memory using this setting perhaps you should try that.

Did you read this page?

Limit memory usage

A limit can be defined by setting --max-old-space-size in the node.options config file found inside the kibana/config folder or any other folder configured with the environment variable KBN_PATH_CONF. For example, in the Debian-based system, the folder is /etc/kibana.

The option accepts a limit in MB:

--max-old-space-size=2048

I am not sure that is accurate... what action you are looking for from this group.

Yes is there possibly a Bug... 9.5.0 has already been "Pulled" on Elastic cloud it was not stable enough I would retry when we get to 9.5.2 which should be released soon.

6

Thank you for suggestion. I will go through this options "--max-old-space-size" and let you know.

7

9.5.2 is already released, ca: 4 days ago - see here

8

Thank you