Database Monitoring for MariaDB and Percona Server
Join the DZone community and get the full member experience.Join For Free
Both MariaDB and Percona Server are forks of MySQL and strive to be drop in replacements for MySQL from a binary, api compatibility, and command line perspective.
It’s great to have an alternative to MySQL since you never know what might happen to it given that Oracle bought it for 1 billion dollars. In this blog post I set out to see if these MySQL forks would work 100% with AppDynamics for Databases. If you’re not familiar with the AppDynamics for Databases product I suggest you take a few minutes to read this other blog post.
Getting both MariaDB and Percona Server installed onto test instances was pretty simple. I chose to use 2 Red Hat Enterprise Linux (RHEL) servers running on Amazon Web Services (AWS) for no particular reason other than they were quick and easy to get running. My first step was to make sure that MySQL was gone from my RHEL servers by running “yum remove mysql-server”.
Installing both MariaDB and Percona Server consisted of setting up yum repository files (documented here andhere) and running the yum installation commands. This took care of getting the binaries installed so the rest of the process was related to starting and configuring the individual database servers.
The startup command for both MariaDB and Percona Server is “/etc/init.d/mysql start” so you can see that these products really do strive for direct drop in adherence to MySQL. As you can see in the screen grabs below I ended up running MariaDB 10.0.3 and Percona Server 5.5.31-30.3.
Connected to each of these databases were 1 instance of WordPress and 1 instance of Drupal in a nearly “out of the box” configuration besides adding a couple of new posts to each CMS to help drive a small amount of load. I didn’t want to set up a load testing tool so I induced a high disk I/O load on each server by running the UNIX command “cat /dev/zero > /tmp/zerofile”. This command pumps the number 0 into that file as fast as it can basically crushing the disk. (Use Ctrl-C to kill this command before you fill up your disk.)
Getting the monitoring set up was really easy. I used a test instance of AppDynamics for Databases to remotely monitor each database instance (yep, no agent install required). To initiate monitoring I opened up my AppDynamics for Databases console, navigated to the agent manager, clicked the “add agent” button, and filled in the fields as shown below (I selected MySQL as the database type):
My remote agent didn’t connect the first time I tired this because I forgot to configure iptables to let my connection through even though I had set up my AWS firewall rules properly (facepalm). After getting iptables out of the way (I just turned it off since these were test instances) my database monitoring connections came to life and I was off and running.
Taking a look at all of the data pouring into AppDynamics for Databases I can see that it is 100% compatible with MariaDB and Percona Server. There are no errors being thrown and the data is everything that it should be.
The beauty of my induced disk I/O load was that just by clicking around the web interface of WordPress and Drupal I was getting slow response times. That always makes data more interesting to look at. So here are some screen grabs for each database type for you to check out…
If you’re currently running MySQL you might want to check out MariaDB and Percona Server. It’s possible that you might see some performance improvements since the storage engine for MariaDB and Percona is XtraDB as opposed to MySQL’s InnoDB. Having choices in technology is a great thing. Having a unified monitoring platform for your MySQL, MariaDB, Percona Server, Oracle, SQL Server, Sybase, IBM DB2, and PostgreSQL database is even better. Click here to get started with your free trial of AppDynamics for Databases today.
Published at DZone with permission of Jim Hirschauer, DZone MVB. See the original article here.
Opinions expressed by DZone contributors are their own.
The SPACE Framework for Developer Productivity
Front-End: Cache Strategies You Should Know
Auditing Tools for Kubernetes
Real-Time Made Easy: An Introduction to SignalR