For virtually all development teams, testing code is a given: It's one of the most important parts of software development. Whether your organization includes a separate team devoted to QA, or your developers are testing their own code, QA is the primary way your team ensures that your application's logic is working correctly, and it's the best way for you to identify issues as early as possible.

As a result, QA is critical for engineering velocity, and it helps shape your users' overall experience when engaging with your product. Nobody likes finding a broken app or website. But what about quality assurance for a database? Do most teams apply the same QA practices to improve their data tier? Do many teams even know how to perform database QA? In this article, we'll talk about how you and your team can apply the same high standards of QA principles to your database, which many organizations often overlook.

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In this post, we'll take a quick look at rsync ("remote sync") and parallel rysnc—a way to increase the efficiency and speed of traditional rsync. At VividCortex, we've found each to be effective and handy at various times.

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Rsync is a tool for copying files between volumes in the same or separate servers. The advantage of rsync is that instead of copying data blindly, it compares the source and destination directories, so that only the difference between the two is sent through the network (or between volumes). 

Rsync can still be slow in certain situations, however—especially when there's a high volume of data that needs to be copied. In such a case, the process can take hours. Additionally, if the volume io has high latency—such as when cold Amazon EBS volumes are involved—the throughput can …

Recently I posted a blog on my time attending a DevOps event in Toronto.  In that blog I had intended to focus on the conference and highlight some of the topics that stood out for me.  In this blog though, I wanted to share what others were doing with containers like Docker, and particularly and… Read More »

I recently attended DevOpsDays Toronto 2017, my first proper DevOpsDaysTO event.  I had the pleasure of attending and being able to immerse myself in this openly collaborative and supportive culture of IT professionals.  The variety of considerations expressed for delivering software features in a rapidly, frequently and reliable release focused manner was really intriguing….but not without its own complexities.… Read More »

via GIPHY I was just responding to some Disqus comments on a recent blog post. Admittedly it had a provocative title Will SQL databases just die already. What do you think? Join 34,000 others and follow Sean Hull on twitter @hullsean. A reader pointed out that some No-SQL databases do support joins. Huh? My face … Continue reading A roughneck walk down database alley →

We saw yesterday that the new MySQL Shell was out and how we could create a MySQL InnoDB Cluster manually using the Shell.

Today, I would like to show you how easy it is to create recipes to automate all the process. I have created a Puppet module that can be used as Proof-of-concept (You might need more features to use it in production, feel free to fork it).

The module can be found on this github repo.

When using Puppet, I really like to put all configuration in hiera.

Environment

We have 3 GNU/Linux servers: mysql1, mysql2 and mysql3.

We won’t install anything related to MySQL manually, everything will be handled by Puppet.

Nodes definition …

MySQL continues to be one of the most popular databases used in cloud-native applications. In fact, MySQL is so popular that other cloud databases such as AWS Aurora maintain wire protocol compatibility with MySQL. For SREs and DevOps engineers running MySQL database in production, it is crucial to understand how to monitor MySQL. MySQL poor health can lead to cascading effects on other application components. For example, slow queries can impact page load times for an application, or missing indexes can result in high-latency and application time-outs. By effectively monitoring the performance of databases and query executions, SREs and DevOps can identify if there are bottlenecks in the database tier which affect the overall application performance. With this appreciation for the importance of MySQL monitoring, let us quickly survey what techniques are commonly used for MySQL monitoring and then discuss …

Vadim Tkachenko recently released  Docker images for Group Replication (thank you for that ).

As not everybody is already using Docker or just because having multiple choices is also nice (this is an OpenSource world isn’t it ?), I decided to share a Vagrant environment that you can use to evaluate Group Replication.

This environment provides also a module that can be used to deploy GR on any other environment managed by Puppet.

The repository is available on my github account: mysqlGR-vagrant

This is a quick demo on how to use it:

Tadam ! You have a MySQL Group of 3 members ready to use !

Docker presents new levels of portability and ease of use when it comes to deploying systems. We have for some time now released Dockerfiles and scripts for MySQL products, and are not surprised by it steadily gaining traction in the development community.…

Docker has been consuming my life in the last few weeks. I have half a dozen projects in progress that use containers in some fashion, including my Visualizing MySQL’s Performance Schema project.

Since I prefer to work from a Mac laptop, I have to utilize a Linux Virtual Machine (VM) which runs the Docker daemon. Luckily, Docker Machine makes this a very simple process.

However, interacting both with Docker and Docker Machine does introduce some additional commands that I would rather simplify for the repeatable use-cases I’ve come across. With BASH aliases, this is not a problem.

Is My Docker Environment Setup?

When …