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MySQL Logs
Ship logs from MySQL to logstash
Configure Filebeat to ship logs from MySQL to Logstash and Elasticsearch.
Step 1 - Install Filebeat
deb (Debian/Ubuntu/Mint)
curl -L -O https://artifacts.elastic.co/downloads/beats//-oss-7.15.1-amd64.deb
sudo dpkg -i -oss-7.15.1-amd64.deb
rpm (CentOS/RHEL/Fedora)
curl -L -O https://artifacts.elastic.co/downloads/beats//-oss-7.15.1-x86_64.rpm
sudo rpm -vi -oss-7.15.1-x86_64.rpm
macOS
curl -L -O https://artifacts.elastic.co/downloads/beats//-oss-7.15.1-darwin-x86_64.tar.gz
tar xzvf -oss-7.15.1-darwin-x86_64.tar.gz
Windows
- Download and extract the Windows zip file.
- Rename the
-<version>-windows
directory to ``. - Open a PowerShell prompt as an Administrator.
- Run the following to install as a Windows service:
.\install-service-.ps1
PowerShell.exe -ExecutionPolicy UnRestricted -File .\install-service-.ps1
.
Step 2 - Enable the Mysql Module
There are several built in filebeat modules you can use. To enable the mysql module run.
deb/rpm
filebeat modules list
filebeat modules enable mysql
macOS
cd <EXTRACTED_ARCHIVE>
./filebeat modules list
./filebeat modules enable mysql
Windows
.\Filebeat modules enable mysql
The default configured paths for MySQL logs are as follows.
/var/log/mysql/mysql.log
/var/log/mysql/mysql-slow.log
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
error:
enabled: true
# Set custom paths for the log files. If left empty,
# Filebeat will choose the paths depending on your OS.
#var.paths:
# Slow logs
slowlog:
enabled: true
# Set custom paths for the log files. If left empty,
# Filebeat will choose the paths depending on your OS.
#var.paths:
Step 3 - Copy Configuration File
The configuration file below is pre-configured to send data to your Logit.io Stack via Logstash.
Copy the configuration file below and overwrite the contents of filebeat.yml.
# ============================== Filebeat modules ==============================
filebeat.config.modules:
# Glob pattern for configuration loading
path: ${path.config}/modules.d/*.yml
# Set to true to enable config reloading
reload.enabled: false
# Period on which files under path should be checked for changes
#reload.period: 10s
# ======================= Elasticsearch template setting =======================
setup.template.settings:
index.number_of_shards: 1
#index.codec: best_compression
#_source.enabled: false
# ================================== Outputs ===================================
# ------------------------------ Logstash Output -------------------------------
<div class="sw-warning">
<b>No input available! </b> Your stack is missing the required input for this data source <a href="#" onclick="Intercom('showNewMessage')" class="btn btn-info btn-sm">Talk to support to add the input</a>
</div>
Step 4 - Start Filebeat
Ok, time to start ingesting data!
deb/rpm
sudo systemctl enable filebeat
sudo systemctl start filebeat
macOS
./filebeat
Windows
PS C:\Program Files\Filebeat> Start-Service filebeat
Step 5 - how to diagnose no data in Stack
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 6 - MySQL dashboard
The MySQL module comes with predefined Kibana dashboards. To view your dashboards for any of your Logit.io stacks, launch Kibana and choose Dashboards.
Step 7 - MySQL Logging Overview
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.