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Table of Contents
Check the current memory usage
Key parameters: Buffer Pool settings should not be too large
Control the number of connections and temporary memory consumption
Daily monitoring suggestions: automated alarm mechanism
Home Database Mysql Tutorial Monitoring and managing MySQL server memory usage

Monitoring and managing MySQL server memory usage

Jul 04, 2025 am 02:26 AM
Server monitoring

To monitor and manage MySQL server memory, you need to view memory usage, set Buffer Pool reasonably, control the number of connections, and establish a monitoring alarm mechanism. First, you can view the current memory usage through top, SHOW ENGINE INNODB STATUS\G and performance_schema; secondly, you can set the innodb_buffer_pool_size according to the server purpose, which is set to 50% to 70% of the memory specifically for MySQL, and the shared control is within 40%. Then, you can control the number of connections and temporary memory consumption through max_connections and sort_buffer_size, and reduce resource waste with the help of connection pools. Finally, it is recommended to use Prometheus Grafana to build a monitoring panel, and implement automated management with scripts and alarm mechanisms.

Monitoring and managing MySQL server memory usage

The memory usage monitoring and management of MySQL servers is an important part of ensuring the stable operation of the database. Many people ignore the memory configuration after deploying MySQL, resulting in performance degradation or even crashes during high loads. In fact, this problem is not complicated. As long as you master a few key points, you can effectively avoid it.

Monitoring and managing MySQL server memory usage

Check the current memory usage

To manage memory well, you must first understand how much is currently used and how it is used. You can view it in the following ways:

Monitoring and managing MySQL server memory usage
  • Use the top or htop command to directly observe the memory usage of the mysqld process.
  • After logging in to MySQL, execute the following statement to view internal statistics:
 SHOW ENGINE INNODB STATUS\G

Here you can see the usage of InnoDB Buffer Pool, such as how much data is currently cached and whether there are frequent read and write swaps.

In addition, you can also use views in a database like performance_schema or sys to analyze memory allocation more intuitively.

Monitoring and managing MySQL server memory usage

Key parameters: Buffer Pool settings should not be too large

InnoDB's buffer pool is the most memory-eating part of MySQL, which determines how much data can be cached in memory to speed up access. But setting it too large can backfire, especially if there are other services running on the server.

Suggested practices:

  • If it is a server dedicated to MySQL, you can set Buffer Pool to 50% to 70% of physical memory
  • If shared with other services, it is best to control it within 40% of the total memory
  • Adjust the configuration file through the innodb_buffer_pool_size parameter

For example, if your server has 16GB of memory and only runs MySQL, then the Buffer Pool can be set to about 10GB~12GB, leaving the rest to the system and other connection overhead.

Note: After modifying this parameter, you need to restart MySQL to take effect.


Control the number of connections and temporary memory consumption

Each client connection will occupy a certain amount of memory resources, especially when the connection performs complex queries or sorting operations, temporary memory may also be used (such as sort_buffer_size and join_buffer_size ). If there are too many connections, it is easy to cause memory bursts.

Common optimization methods include:

  • Limit the maximum number of connections: control through max_connections , estimate reasonable values ??based on the total amount of server memory
  • Reduce the buffer size used by a single connection: For example, lower sort_buffer_size to 1MB to 2MB (the default may be relatively large)
  • Regularly check slow query logs to optimize SQL with long execution time and high resource consumption

You can use the following command to see how many active connections are currently available:

 SHOW STATUS LIKE 'Threads_connected';

If there are a large number of idle connections, consider using connection pooling tools, such as ProxySQL or the application-side connection pooling mechanism to reduce resource waste.


Daily monitoring suggestions: automated alarm mechanism

Manual memory checking is too troublesome, and it is best to cooperate with monitoring tools to perform automatic detection in daily operations and maintenance. for example:

  • Use Prometheus Grafana to build a visual monitoring panel
  • Collect memory usage regularly with scripts and record logs
  • Set threshold alarms, for example, if memory usage exceeds 85%, send a notification reminder

These methods can help you detect abnormal trends in advance, rather than wait until the service is stuck before processing.


Basically that's it. Memory management is not a matter of good luck after all configurations. As business growth and data volume changes, parameters must be reviewed and adjusted regularly.

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