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Send data via MySQL to your Logstash instance provided by

MySQL Logs

Ship logs from MySQL to logstash

Configure Filebeat to ship logs from MySQL to Logstash and Elasticsearch.

Step 1 - Install FilebeatCopy

deb (Debian/Ubuntu/Mint)

curl -L -O
sudo dpkg -i -oss-7.15.1-amd64.deb

rpm (CentOS/RHEL/Fedora)

curl -L -O
sudo rpm -vi -oss-7.15.1-x86_64.rpm


curl -L -O
tar xzvf -oss-7.15.1-darwin-x86_64.tar.gz


  • Download the Windows zip file from the official downloads page.
  • Extract the contents of the zip file into C:\Program Files.
  • Rename the -<version>-windows directory to ``.
  • Open a PowerShell prompt as an Administrator (right-click the PowerShell icon and select Run As Administrator). If you are running Windows XP, you may need to download and install PowerShell.
  • Run the following commands to install as a Windows service:
cd 'C:\Program Files\'
If script execution is disabled on your system, you need to set the execution policy for the current session to allow the script to run. For example: PowerShell.exe -ExecutionPolicy UnRestricted -File .\install-service-.ps1.
My OS isn't here! Don't see your system? Check out the official downloads page for more options (including 32-bit versions).

Step 2 - Locate Configuration FileCopy

deb/rpm /etc/filebeat/filebeat.yml
mac/win <EXTRACTED_ARCHIVE>/filebeat.yml

Step 3 - Enable the Mysql ModuleCopy

There are several built in filebeat modules you can use. To enable the mysql module run.


filebeat modules list
filebeat modules enable mysql


./filebeat modules list
./filebeat modules enable mysql


.\Filebeat modules enable mysql

The default configured paths for MySQL logs are as follows.



c:\programdata\MySQL\MySQL Server*\error.log*

c:\programdata\MySQL\MySQL Server*\mysql-slow.log*

Additional module configuration can be done using the per module config files located in the modules.d folder, most commonly this would be to read logs from a non-default location

deb/rpm /etc/filebeat/modules.d/
mac/win <EXTRACTED_ARCHIVE>/modules.d/

- module: mysql
# Error logs
  enabled: true

  # Set custom paths for the log files. If left empty,
  # Filebeat will choose the paths depending on your OS.

# Slow logs
  enabled: true

  # Set custom paths for the log files. If left empty,
  # Filebeat will choose the paths depending on your OS.

Step 4 - Configure outputCopy

We'll be shipping to Logstash so that we have the option to run filters before the data is indexed.
Comment out the elasticsearch output block.

## Comment out elasticsearch output
#  hosts: ["localhost:9200"]
No input available! Your stack is missing the required input for this data source Talk to support to add the input

Step 5 - Validate configurationCopy

Let's check the configuration file is syntactically correct by running directly inside the terminal. If the file is invalid, will print an error loading config file error message with details on how to correct the problem.


sudo  -e -c /etc//.yml


./ -e -c .yml


.\.exe -e -c .yml

Step 6 - Start FilebeatCopy

Ok, time to start ingesting data!


sudo systemctl enable filebeat
sudo systemctl start filebeat




PS C:\Program Files\Filebeat> Start-Service filebeat

Step 7 - how to diagnose no data in StackCopy

If you don't see data appearing in your Stack after following the steps, visit the Help Centre guide for steps to diagnose no data appearing in your Stack or Chat to support now.

Step 8 - MySQL dashboardCopy

The MySQL module comes with predefined Kibana dashboards. To view your dashboards for any of your stacks, launch Kibana and choose Dashboards.

Predefined kibana dashboard screenshot

Step 9 - MySQL Logging OverviewCopy

MySQL is an open source relational database management system created by Michael Widenius in 1995, this relational database runs across the majority of operating systems & is closely associated with its usage for web applications.

MySQL powers some of the world’s highest traffic sites, including Facebook, YouTube & Pinterest.

MySQL is able to work within an operating system to organise data into multiple data tables and show which data types may be related to each other. This helps the user to easily structure their data.

When used in this way, relational databases can be used to test database integrity, manage users and create backups of vital data.

MySQL Servers create numerous logs that you can use for troubleshooting and analysis, the most important ones include: Slow query logs, General query logs & error logs.

These logs default to a text file format, which can quickly become tedious to parse and process quickly to spot functional problems, opportunities to improve performance and identify security issues.

Our built in HA (high availability) MySQL log file analyser can be used to centralise your data & set up alerts to monitor your log data in real-time as well as deliver metrics for Kibana visualisations & reports with easily.

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