How to Store MySQL Audit Logs in MongoDB in a Maintenance-Free Setup

Store MySQL Audit Logs in MongoDBI was once helping one of our customers on how to load MySQL audit logs into a MySQL database and analyze them. But immediately I thought: “Hey, this is not the most efficient solution! MySQL or typical RDBMS, in general, were not really meant to store logs after all.”

So, I decided to explore an alternative – which seemed more sensible to me – and use MongoDB as the storage for logs, for three main reasons:

  • schema-less nature fits well to the audit log nature, where different types of events may use different fields
  • speaks JSON natively and the audit plugin can use JSON format
  • has capped collections feature, which allows avoiding additional maintenance overhead

Just to mention, audit logging is available in MySQL Enterprise Edition but a similar, yet free, solution, is available in Percona Server for MySQL. In both cases, it works by installing the audit log plugin.

Ad Hoc Import

The simplest scenario is to just set the audit log format to JSON:

And as soon as it collects some data, import the log file into MongoDB collection via the mongoimport command, like this:

Of course, this works, but I prefer an automated solution, so I looked at available options for live-streaming the logs.


The first thing that looked useful is the ability to send the audit log directly to syslog instead of a file. Knowing that both rsyslog, as well as syslog-ng, have MongoDB output modules, it felt like a very easy approach. So I installed the rsyslog-mongodb module package on my test Ubuntu VM with running Percona Server for MySQL, configured audit log with:

Rsyslog (version 8.2) example configuration with:

This worked, however, inserted documents looked like this:

Basically, because of syslog escaping the double quote symbols, the whole audit record appears as a single string inside MongoDB collection, instead of a JSON object. No matter what I tried, like custom templates and property values in rsyslog, I could not disable escaping. Therefore, although feeding MongoDB with audit logs works this way, it becomes pretty useless when it comes to analyzing the logs later. The same issue applies to syslog-ng and the syslog-ng-mod-mongodb module. And since MongoDB does not offer before-insert triggers, I could not easily “fix” the inserted data on the fly.

Fluentd For The Rescue!

This forced me to look for alternative solutions. One of them would be using FIFO file and tail the audit log continuously to feed it, and then read from it to insert logs to mongodb. I wanted a more robust way, though, and decided to try Fluentd instead. It was created as a versatile log collector machine, highly flexible, prepared to work with many different applications out of the box, but most importantly, it is an open source project and speaks JSON natively. Making it to do the job I wanted turned out to be easier than I expected.

Here is what I did:

  • Installed the Fluentd package (I chose td-agent variant here for an even easier user experience)
  • Installed MongoDB plugin for Fluentd with (don’t use the usual ‘gem install’ here):

  • Configured audit log as a source and output directive for MongoDB:

  • Added the user used by Fluentd to mysql group to allow it to read from the audit log:

  • Restarted both services to apply changes:

  • Checked the Fluentd log to see if it reads the audit log as expected, also for when Percona Server for MySQL rotates it:

  • Ran sysbench against MySQL instance and verified the new collection in MongoDB gets updated:

Yay, it works like a charm! Not only are the audit logs rotated automatically on Percona Server for MySQL, but also on MongoDB the destination collection size cap works as well, so I am safe when it comes to disk space on both hosts!

Here, there is a little caveat – if for some reason you drop the destination collection manually on MongoDB, incoming inserts will make it re-created without the capped setting! Therefore, either let the collection be created by Fluentd on its service startup or create it manually with a capped setting, and don’t drop it later.

Now, we can try some example aggregations to get some useful audit stats: