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# Tag: DevOps

## “Anemomaster”: DML visibility. Your must-do for tomorrow

MySQL Anemometer DevOps Monitoring Open Source Replication April 18, 2014April 18, 2014

Here’s our take of master DML query monitoring at Outbrain (presented April 2014). It took a half-day to code, implement, automate and deploy, and within the first hour of work we managed to catch multiple ill-doing services and scripts. You might want to try this out for yourself.

#### What’s this about?

What queries do you monitor on your MySQL servers? Many don’t monitor queries at all, and only look up slow queries on occasion, using pt-query-digest. Some monitor slow queries, where Anemometer (relying on pt-query-digest) is a very good tool. To the extreme, some monitor TCP traffic on all MySQL servers — good for you! In between, there’s a particular type of queries that are of special interest: DML (INSERT/UPDATE/DELETE) queries issued against the master.

They are of particular interest because they are only issued once against the master, yet propagate through replication topology to execute on all slaves. These queries have a direct impact on your slave lag and on your overall replication capacity. I suggest you should be familiar with your DMLs just as you are with your slow queries.

In particular, we had multiple occasions in the past where all or most slaves started lagging. Frantically we would go to our metrics; yes! We would see a spike in com_insert. Someone (some service) was obviously generating more INSERTs than usual, at a high rate that the slaves could not keep up with. But, which INSERT was that? Blindly, we would look at the binary logs. Well, erm, what are we looking for, exactly?

Two such occasions convinced us that there should be a solution, but it took some time till it hit us. We were already using Anemometer for monitoring our slow logs. We can do the same for monitoring our binary logs. Thus was born “Anemomaster”.

Quick recap on how Anemometer works: you issue pt-query-digest on your slow logs on all MySQL hosts (we actually first ship the slow logs to a central place where we analyse them; same thing). This is done periodically, and slow logs are then rotated. You throw the output of pt-query-digest to a central database (this is built in with pt-query-digest; it doesn’t necessarily produce human readable reports). Anemometer would read this central database and visualize the slow queries.

#### Analysing DMLs

But then, pt-query-digest doesn’t only parse slow logs. It can parse binary logs. Instead of asking for total query time, we ask for query count, and on we go to establish the same mechanism, using same pt-query-digest and same Anemometer to store and visualize the DMLs issued on our masters.

When analysing DMLs we’re interested in parsing binary logs — and it makes no sense to do the same on all slaves. All slaves just have same copy of binlog entries as the master produces. It only takes one server to get an accurate picture of the DMLs on your replication topology.

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## Speaking at Percona Live: common_schema, MySQL DevOps

MySQL common_schema Development DevOps Open Source PerconaLive Speaking March 10, 2014April 4, 2014

In less than a month I’ll be giving these two talks at Percona Live:

- common_schema: DBA’s framework for MySQL

If you are still unfamiliar with common_schema, this will make for a good introduction. I’ll give you multiple reasons why you would want to use it, and how it would come to immediate use at your company. I do mean immediate, as in previous common_schema presentations I happened to get feedback emails from attendees within the same or next day letting me know how common_schema solved an insistent problem of theirs or how it exposed an unknown status.

I’ll review some useful views & routines, and discuss the ease and power of QueryScript. common_schema is a Swiss-knife of solutions, and all from within your MySQL server.

I am using common_schema in production on a regular basis, and it happened to be hero of the day in multiple occasions. I’ll present a couple such cases.

common_schema 2.2: DBA's framework for MySQL (April 2014) from Shlomi Noach

- MySQL DevOps @ Outbrain

This is a technical talk touching at some cultural issues.

At Outbrain, where I work, we have two blessings: a large group of engineers and a large dataset. We at the infrastructure team, together with the ops team, are responsible for the availability of the data. What we really like is technology which lets the owners of a problem be able to recognize it and take care of it. We want ops guys to do ops, and engineers to do engineering. And we want them to be able to talk to each other and understand each other.

What tools can you use to increase visibility? To allow sharing of data between the teams? I’ll share some tools and techniques that allow us to automate deployments, detect a malfunctioning/abusing service, deploy schema changes across dozens of hosts, control data retention, monitor connections, and more.

We like open source. The tools discussed are mostly open source, or open sourced by Outbrain.

I’ll explain why these tools matter, and how they serve the purpose of removing friction between teams, allowing for quick analysis of problems and overall visibility on all things that happen.

MySQL DevOps at Outbrain from Shlomi Noach

#### Do come by!