One of the nice things about the "plug and play" approach of MaxScale is that people constantly find ways of using it that were not originally envisaged when we designed MaxScale. One such configuration that I have heard of from multiple sources is using monitoring outside of MaxScale itself. This post will discuss a little about how monitoring works and how it can be moved outside of MaxScale. In particular a simplified example will be presented which shows how to use the notification mechanism in Galera to control MaxScale's use of the nodes in a Galera cluster.
How can we find extra ways to test MaxScale? It‘s now working its way through a beta program, heading for general release. As part of the team responsible for its development, I’ve been looking for ways to find obscure bugs. Several approaches are involved, including unit tests and system tests. But another thing we wanted to try was to put a real life application, written by other people, in front of MaxScale.
The MaxScale team have been working hard fixing bugs and improving performance. On Friday we released a update of MaxScale, the pluggable proxy for MySQL and MariaDB, I wanted to write a little about a few of those changes. I will not mention every change, there are release notes that give the list of bugs fixed in this version, but rather highlight a couple of performance related changes and describe the rationale behind them. However before I start on the two items I wanted to discuss just a quick note to say that this version introduces cmake as the means to build MaxScale.
Tonight I will give a presentation on Max Scale (An Advanced Proxy for MySQL) for the Chicago MySQL Meetup
How to Install MaxScale and MariaDB 5.5 Galera cluster with Severalnines Cluster Control on Amazon Virtual Private Cloud
This blog post will show how to Install MaxScale and MariaDB 5.5 Galera Cluster with Severalnines Cluster Control on Amazon Virtual Private Cloud.
The steps in this blog:
- How to setup Amazon Virtual Private Cloud
- How to prepare the MariaDB Galera Cluster nodes and to set the subnet routings
- How to install MariaDB Galera 3 node cluster in the private subnet of an AWS VPC using Severalnines Cluster Control
- How to build MaxScale from git source on the Cluster Control node
MaxScale, an open-source database-centric router for MySQL and MariaDB makes High Availability possible by hiding the complexity of backends and masking failures. MaxScale itself however is a single application running in a Linux box between the client application and the databases - so how do we make MaxScale High Available? This blog post shows how to quickly setup a Pacemaker/Corosync environment and configure MaxScale as a managed cluster resource. We will guide you step by step on how to enable basic High Availability by setting up three Linux Centos 6.5 servers with MaxScale.
MaxScale for MariaDB and MySQL hides the complexity of database scaling from the application. To streamline building MaxScale from source and running the test suite, you can automate the process with some useful tools to meet your needs. I have created a Vagrant / Puppet setup I'd like to share with you.
MaxScale 1.0 from SkySQL is now in Beta and there are some cool features in it, I guess some adventurous people has already put it into production. There are still some rough edges and stuff to be fixed, but it is clearly close to GA. One thing missing though are something to manage starting and stopping MaxScale in a somewhat controlled way, which is what this blog is all about.
Here we take a look at how one of the example filters supplied with the MaxScale 1.0 beta can answer that simplest of profiling questions - "Which of my database queries run within the MySQL server for the longest time?".
Let's assume you want to start an automatically expanding and shrinking MySQL replication cluster with up-to seven database servers. This blog shows how to setup up and start MaxScale to work with a master and a single slave and, when needed, how it adapts to the changing cluster configurations. While the set up here is simple similar behavior can be applied in bigger and more complex scenarios.