We are pleased to announce the launch of PMM 2.0.0-alpha2, Percona’s second Alpha release of our long-awaited PMM 2 project! In this release, you’ll find support for MongoDB Metrics and Query Analytics – watch for sharp edges as we expect to find a lot of bugs!  We’ve also expanded our existing support of MySQL from our first Alpha to now include MySQL Slow Log as a data source for Query Analytics, which enhances the Query Detail section to include richer query metadata.

• MongoDB Metrics – You can now launch PMM 2 against MongoDB and gather metrics and query data!
• MongoDB Query Analytics – Data source from MongoDB Profiler is here!
• MySQL Query Analytics
  • Queries source – MySQL Slow Log is here!
  • Sorting and more …

We are pleased to announce the launch of PMM 2.0.0-alpha1, Percona’s first Alpha release of our long-awaited PMM 2 project! We focused exclusively on MySQL support in our first Alpha (because we wanted to show progress sooner rather than later), and you’ll find updated MySQL dashboards along with enhancements to Query Analytics. We’ve also added better visibility regarding which services are registered with PMM Server, the client-side addition of a new agent called pmm-agent, and finally PMM Server is now exposing an API!

• Query Analytics
  • Support for large environments – default view all queries from all instances
  • Filtering – display only the results matching filters – MySQL schema name, MySQL server instance
  • Sorting and more columns – now sort by any …

One of the great things about Percona Monitoring and Management (PMM) is its flexibility. An example of that is how one can go beyond the exporters to collect data. One approach to achieve that is using textfile collectors, as explained in  Extended Metrics for Percona Monitoring and Management without modifying the Code. Another method, which is the subject matter of this post, is to use custom queries.

While working on a customer’s contention issue I wanted to check the behaviour of InnoDB Mutexes over time. Naturally, I went straight to PMM and didn’t find a graph suitable for my needs. No graph, no problem! Luckily anyone can enhance PMM. So here’s how I made the …

In this blog post, I want to share a case we worked on a few days ago. I’ll show you how we approached the resolution of a MySQL performance issue and used Percona Monitoring and Management PMM to support troubleshooting. The customer had noticed a linear high CPU usage in one of their MySQL instances and was not able to figure out why as there was no much traffic hitting the app. We needed to reduce the high CPU usage on MySQL. The server is a small instance:

Models | 6xIntel(R) Xeon(R) CPU E5-2430 0 @ 2.20GHz
10GB RAM

This symptom can be caused by various different reasons. Let’s see how PMM can be used to troubleshoot the issue.

CPU

It’s important to understand where the CPU time is being consumed: user space, system space, iowait, and so on. Here we can see that CPU usage was …

Percona Monitoring and Management (PMM) is a free and open-source platform for managing and monitoring MySQL®, MongoDB®, and PostgreSQL performance. You can run PMM in your own environment for maximum security and reliability. It provides thorough time-based analysis for MySQL®, MongoDB®, and PostgreSQL® servers to ensure that your data works as efficiently as possible.

In this release, we are introducing support for detection of our upcoming PMM 2.0 release in order to avoid potential version conflicts in the future, as PMM 1.x will not be compatible with PMM 2.x.

Another improvement in this release is we have updated the Tooltips for Dashboard MySQL Query Response Time by providing a description of what the graphs display, along with links to related documentation resources. An example of Tooltips in action:

While the PMM team works hard on our PMM 2.0 release, we have been working on a few things in the background which we’d like to show off !  In particular we have developed a new dashboard that displays metrics related to memory usage on Linux systems. The dashboard leverages information collected by node_exporter. The graphs take advantage of  /proc filesystem files, specifically:

• meminfo: Provides information about distribution and utilization of memory. This varies by architecture and compile options.
• vmstat: Provides information about block IO and CPU activity in addition to memory.

…

EverSQL is a platform that intelligently tunes your SQL queries by providing query optimization recommendations, and feedback on missing indexes. This is the second post of our EverSQL series, if you missed our introductory post take a look there first and then come back to this article.

We’ll use the Stackoverflow data set again as we did in our first post.

Diving into query optimization

We’ll grab the worst performing query in the list from PMM and optimize it. This query builds a list of the top 50 most recent posts which have a score greater than two, and involves joining two large tables – posts and comments. The original runtime of that query is …

A common challenge with continuously deployed applications is that new and modified SQL queries are constantly being introduced to the application. Many companies choose to use a database monitoring system (such as PMM) to identify those slow queries. But identifying slow queries is only the start – what about actually optimizing them?

In this post we’ll demonstrate a new way to both identify and optimize slow queries, by utilizing the recent integration of Percona Monitoring and Management with EverSQL Query Optimizer via Chrome browser extension. This integration allows you to identify slow queries using PMM, and optimize them automatically using EverSQL Query Optimizer.

Optimizing queries with PMM & EverSQL

We’re using PMM to monitor our MySQL …

PMM (Percona Monitoring and Management) is a free and open-source platform for managing and monitoring MySQL, MongoDB, and PostgreSQL performance. You can run PMM in your own environment for maximum security and reliability. It provides thorough time-based analysis for MySQL® and MongoDB® servers to ensure that your data works as efficiently as possible.

While much of the team is working on longer-term projects, we were able to provide the following feature:

• MySQL and PostgreSQL support for all cloud DBaaS providers – Use PMM Server to gather Metrics and Queries from remote instances!
• Query Analytics + Metric Series – See Database activity alongside queries
• Collect local metrics using node_exporter + textfile …

Recently we had a customer that had issues with a filled disk on the server hosting their Docker pmm-server environment. They were not able to access the web UI, or even stop the pmm-server container because they had filled the /var/ mount point.

Setting correct expectations

The best way to avoid these kinds of issues in the first place is to plan ahead, and to know exactly with what you are dealing with in terms of disk space requirements. Michael Coburn has written a great blogpost on this matter:

https://www.percona.com/blog/2017/05/04/how-much-disk-space-should-i-allocate-for-percona-monitoring-and-management/

We are now using …