Our Approach to Percona Monitoring and Management Upgrade Testing

Percona Monitoring and Management Upgrade

Percona Monitoring and Management UpgradeHey Community! This is my first blog post so let me introduce myself. My name is Vasyl Yurkovych. I am a QA Automation Engineer at Percona and I have solid experience in software testing. 

Software quality is one of the main focuses of Percona so we put a lot of energy into it (hopefully so you don’t have to!). Our biggest challenge in testing isn’t necessarily running the routines against the current version, but the fact that users can decide to upgrade at any time, from pretty much any supported version.  So I’d like to share with you our upgrade testing approach for Percona Monitoring and Management (PMM) in hopes that this might be useful to others who create software that users install!

PMM is released every month and our users do not reinstall each new version – they just perform the upgrade operation when there’s a compelling feature or fix. Also, these PMM instances are not “empty”; they are full of various settings, monitored DBs, etc.,  all of which need to be preserved.

Taking into account all of that, we want to make sure that: 

  • the user will not suffer after the upgrade and will enjoy the new version of PMM
  • user’s instances will still be under monitoring without missing vital data during the upgrade
  • settings will be preserved
  • new features will work as expected

We decided to automate this process and select critical automation scenarios to execute. They were split into 3 stages: Pre Upgrade, Upgrade, and Post Upgrade.

Pre Upgrade (UI and API Scenarios)

  1. “Fill” PMM with monitored instances. We add each supported DB type for monitoring. Along with this, we ensure that the monitoring status of each added instance is ”RUNNING”. For these scenarios, we use corresponding PMM API endpoints.
  2. Apply custom Settings.
  3. Check that the Upgrade widget at the Home Dashboard is present and contains an Update button, the available version of PMM is correct and What’s new link is there.


  1. To fully simulate a user’s behavior we use the UI upgrade option.

Post Upgrade (UI Scenarios Only)

  1. After the upgrade itself was successful we check that the Upgrade widget at the Home Dashboard indicates that the PMM has the latest version.
  2. Also, we check the PMM Inventory to confirm that all the previously monitored DB instances exist and have “RUNNING” statuses.
  3. We check that Query Analytics Dashboard has corresponding DB filters (filters only exist when the DB specific queries exist).
  4. We confirm that all our custom Settings were properly upgraded and remain intact.

Also, we test upgrades from the older PMM versions, so we created a CI job that runs on the weekends and during the release testing phase. This gives us the ability to check the upgrade from any available version to the latest one. All we have to do is to specify the version we want to upgrade from. Check out this screenshot as an example of a failed upgrade.

Currently, we use this approach for testing Docker-based PMM Server upgrade, because PMM docker images are most commonly used. But we plan to implement the same upgrade job for OVF and AMI based PMM-Server soon. 

This is the final piece of our upgrade testing approach which alerts us immediately if some version has a problem upgrading to the latest one and allows us to react at the same time.

While this may seem an obvious tactic to ensure software quality, it’s amazing how often we’ll discover something that only impacts a single version.  

You are now safe to upgrade your Percona Monitoring and Management version, as PMM CI is watching your back!

by Vasyl Yurkovych via Percona Database Performance Blog


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