Elasticsearch Understanding and Optimizing vm.max_map_count for Elasticsearch Performance

By Opster Team

Updated: Nov 6, 2023

| 2 min read


Elasticsearch often requires certain system-level configurations to perform optimally. One such configuration is the vm.max_map_count kernel setting. This setting is crucial for Elasticsearch’s performance and stability, and understanding its role can help you optimize your Elasticsearch deployment.

The vm.max_map_count parameter refers to the maximum number of memory map areas a process may have. Memory-mapped files are a method that programs use to bring data into memory faster. Elasticsearch uses a mechanism called mmapfs (memory-mapped file system) to perform file I/O operations, which relies heavily on memory-mapped areas. 

vm.max_map_count value

The default value of vm.max_map_count on many systems is 65536. However, Elasticsearch recommends setting it to at least 262144 to prevent out-of-memory exceptions. This is because Elasticsearch uses a large number of file descriptors and memory-mapped areas, especially in larger clusters. If the number of memory-mapped areas is insufficient, Elasticsearch may fail to start or may crash during operation.

To check the current value of vm.max_map_count, you can use the following command:

sysctl vm.max_map_count

If the value is less than 262144, you should increase it. To set the value of vm.max_map_count to 262144, you can use the following command:

sysctl -w vm.max_map_count=262144

However, this change is not persistent and will be reset after a system reboot. To make the change permanent, you need to update the /etc/sysctl.conf file. Add or update the following line in the file:


After saving the changes and rebooting, the new value will persist.

It’s important to note that while increasing vm.max_map_count can improve Elasticsearch’s stability, it does not necessarily improve performance. The optimal value depends on your specific use case and workload. If your Elasticsearch nodes are frequently running out of memory, it might be more effective to add more RAM or reduce the heap size, rather than increasing vm.max_map_count.

In addition, while Elasticsearch recommends a vm.max_map_count of at least 262144, setting it too high can also cause problems. Each memory-mapped area consumes resources, and having too many can lead to increased memory usage and slower performance. Therefore, it’s important to monitor your system’s performance and adjust the vm.max_map_count value as needed.


In conclusion, the vm.max_map_count setting is a crucial part of Elasticsearch’s configuration. By understanding its role and how to optimize it, you can ensure that your Elasticsearch deployment is stable and performs well under heavy workloads. 

How helpful was this guide?

We are sorry that this post was not useful for you!

Let us improve this post!

Tell us how we can improve this post?