Recently, I encountered a Percona Monitoring and Management (PMM) server that was rapidly approaching complete disk exhaustion. This post outlines the steps taken to identify the issue and reclaim disk…

The post How to Resolve Disk Space Issues in PMM: Case Study first appeared on Change Is Inevitable.

As businesses grow and develop, the requirements that they have for their data platform grow along with it. As such, one of the more common questions I get from my clients is whether or not their system will be able to endure an anticipated load increase. Or worse yet, sometimes I get questions about regaining normal operations after a traffic increase caused performance destabilization.

As the subject of this blog post suggests, this all comes down to proper capacity planning. Unfortunately, this topic is more of an art than a science, given that there is really no foolproof algorithm or approach that can tell you exactly where you might hit a bottleneck with server performance. But we can discuss common bottlenecks, how to assess them, and have a better understanding as to why proactive monitoring is so important when it comes to responding to traffic growth.

Hardware considerations

The first thing we have to consider …

2022 was an exciting year for Percona Monitoring and Management (PMM). We’ve added and improved many features, including Alerting and Backup Management. These updates are designed to keep databases running at peak performance and simplify database operations. But as companies grow and see more demand for their databases, we need to ensure that PMM also remains scalable so you don’t need to worry about its performance while tending to the rest of your environment.

PMM2 uses VictoriaMetrics (VM) as its metrics storage engine. Percona’s co-Founder Peter Zaitsev wrote a detailed post about migration from Prometheus to VictoriaMetrics, One of the most significant differences in …

In this blog, I will demonstrate how to use Percona Monitoring and Management (PMM) to find out the reason why the MySQL server is stalling. I will use only one typical situation for the MySQL server stall in this example, but the same dashboards, graphs, and principles will help you in all other cases.

Nobody wants it but database servers may stop handling connections at some point. As a result, the application will slow down and then will stop responding.

It is always better to know about the stall from a monitoring instrument rather than from your own customers.

PMM is a great help in this case. If you look at its graphs and notice that many of them started showing unusual behavior, you need to react. In the case of stalls, you will see that either some activity went to 0 or, otherwise, it increased to high …

In the previous posts of this series, I presented how the Percona Support team approaches the analysis and troubleshooting of a MySQL server using a tried-and-tested method supported by specific tools found in the Percona Toolkit:

Inspecting MySQL Servers Part 1: The Percona Support Way

Inspecting MySQL Servers Part 2: Knowing the Server

Inspecting MySQL Servers Part 3: What MySQL?

Inspecting MySQL Servers Part 4: An Engine in …

Visibility is a blessing, and with databases, visibility is a must. That’s true not only for metrics but for the queries themselves. Having info on all the stats around query execution is priceless, and Percona Monitoring and Management (PMM) offers that in the form of the Query Analytics dashboard (QAN).

But where to start? QAN helps you with that by calculating the query profile. What is the profile? It’s a rank of queries, ordered by Load, so it is easy to spot the heaviest queries hitting your database. The Load is defined as the “Average Active Queries” but can also be defined as a mix of Query Execution Time Plus Query count. In other words, all the time the query was alive and kicking.

The Profile in PMM 2.10.0 looks like this:

The purpose of this profile is to facilitate the task of finding the …

PMM (Percona Monitoring and Management) is a great community tool for monitoring your OSDB (MySQL, PostgreSQL, MongoDB) fleet. It’s feature rich, and it’s built and distributed as open-source based on several de-facto industry standard tools such as Grafana and Prometheus. In the second half of last year, major version 2 was released and whereas the major components remained mostly the same, some significant architectural changes were made, but this is out-of-scope for this post.

Upgrading to PMM2 is basically the same as starting from scratch with a fresh install; it requires re-adding all your servers, which can be a painful process if you have a large fleet of instances. For servers where you have OS level access, you can just install the PMM2 agent, but for RDS there is no access to the OS so another approach is required. In this blog, I will focus on getting a large number of RDS instances added.

Adding RDS instances …

When I speak about MySQL performance troubleshooting (or frankly any other database), I tend to speak about four primary resources which typically end up being a bottleneck and limiting system performance: CPU, Memory, Disk, and Network.

It would be great if when seeing what resource is a bottleneck, we could also easily see what queries contribute the most to its usage and optimize or eliminate them. Unfortunately, it is not as easy as it may seem.

First, MySQL does not really provide very good instrumentation in those terms, and it is not easy to get information on how much CPU usage, Disk IO, or Memory a given query caused.  Second, direct attribution is not even possible in a lot of cases. For example, disk writes from flushing data from the InnoDB buffer pool in the …

A few days ago, a customer got in touch asking how they could use Percona Monitoring and Management (PMM) to monitor the roles played by each node in an InnoDB cluster. More specifically, they wanted to check when one of the nodes changed its role from Primary to Secondary, or vice-versa. PMM allows for a high level of flexibility and customization through its support for custom queries, and we just have to be creative on how we approach the problem. In this post, we present the steps we did to test our solution, including the deployment of a 3-node InnoDB Cluster hosted in the same server (for testing) and a PMM 2 server, and connecting them together. Even though this has already been covered in other blog …

Even though Percona Monitoring and Management 2 (PMM) comes with a lot of dashboards and metrics out of the box, sometimes we need to extend the default metrics by running custom MySQL queries.

For example, suppose you want to have information about cached indexes from Innodb tables from innodb_cached_indexes table. That metric is not being captured by any default dashboard, but it is possible to extend PMM and make it capture the result of custom queries.

Getting Started With Custom Queries

Custom queries can be added to mysqld_exporter by adding them to the appropriate config file in /usr/local/percona/pmm2/collectors/custom-queries/mysql. There are three subdirectories inside it: high-resolution, low-resolution, and medium-resolution. PMM allows …