July 28, 2014

How to Monitor MySQL with Percona’s Nagios Plugins

In this post, I’ll cover the new MySQL monitoring plugins we created for Nagios, and explain their features and intended purpose. I want to add a little context. What problem were we trying to solve with these plugins? Why yet another set of MySQL monitoring plugins? The typical problem with Nagios monitoring (and indeed with […]

Configuring MySQL For High Number of Connections per Second

One thing I noticed during the observation was that there were roughly 2,000 new connections to MySQL per second during peak times. This is a high number by any account. When a new connection to MySQL is made, it can go into the back_log, which effectively serves as a queue for new connections on operating […]

Finding an optimal balance of I/O, CPU, and RAM for MySQL

For a long time I’ve wanted to know how MySQL scales as you add more memory to the server. Vadim recently benchmarked the effects of increasing memory and CPU core count. He looked for a balance between utilizing the hardware as much as possible, limiting the system complexity, and lowering the price-to-performance ratio. The outcome […]

MySQL Connection Timeouts

Sometimes on very busy MySQL server you will see sporadic connection timeouts, such as Can’t connect to MySQL server on ‘mydb’ (110). If you have connects timed in your application you will see some successful connections taking well over the second. The problem may start very slow and be almost invisible for long time, for […]

Innodb row size limitation

I recently worked on a customer case where at seemingly random times, inserts would fail with Innodb error 139. This is a rather simple problem, but due to it’s nature, it may only affect you after you already have a system running in production for a while.

MySQL caching methods and tips

“The least expensive query is the query you never run.” Data access is expensive for your application. It often requires CPU, network and disk access, all of which can take a lot of time. Using less computing resources, particularly in the cloud, results in decreased overall operational costs, so caches provide real value by avoiding […]

Modeling MySQL Capacity by Measuring Resource Consumptions

There are many angles you can look at the system to predict in performance, the model baron has published for example is good for measuring scalability of the system as concurrency growths. In many cases however we’re facing a need to answer a question how much load a given system can handle when load is […]

Percona Launches New Support Option for MySQL

We’ve just announced a new support offering for MySQL. There’s a press release here, and product information page here. But what does this new service really mean for you, in practical terms? This is actually important — it will open up a range of new choices for you. I’ll explain two major points that matter […]

Scaling: Consider both Size and Load

So lets imagine you have the server handling 100.000 user accounts. You can see the CPU,IO and Network usage is below 10% of capacity – does it mean you can count on server being able to handle 1.000.000 of accounts ? Not really, and there are few reasons why, I’ll name most important of them: […]

When should you store serialized objects in the database?

A while back Friendfeed posted a blog post explaining how they changed from storing data in MySQL columns to serializing data and just storing it inside TEXT/BLOB columns. It seems that since then, the technique has gotten more popular with Ruby gems now around to do this for you automatically.