Tag - Kubernetes

How Container Networking Affects Database Performance

How Container Networking Affects Database Performance

Percona has been investing in building and releasing Operators for Kubernetes to run traditional databases in a cloud-native fashion. The first two Kubernetes operators were for Percona Server for MongoDB and Percona XtraDB Cluster, chosen because they both feature replication systems that can be made to work effectively in a containerized world.
One of the […]

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How to Measure MySQL Performance in Kubernetes with Sysbench

MySQL Kubernetes Sysbench

As our Percona Kubernetes Operator for Percona XtraDB Cluster gains in popularity, I am getting questions about its performance and how to measure it properly. Sysbench is the most popular tool for database performance evaluation, so let’s review how we can use it with Percona XtraDB Cluster Operator.
Operator Setup
I will assume that you have […]

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Deploying the Percona Kubernetes Operator for XtraDB Cluster in Amazon (AWS)

Percona Kubernetes Operator for Percona XtraDB Cluster in AWS

Being that Amazon is one of the most-used cloud vendors, it is only natural that one may ask “How can Kubernetes be used in AWS?“. And the answer is – not that different than with other cloud vendors. What one needs is two things (and this applies universally): a Kubernetes cluster + the Percona […]

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Setup and Deploy Vitess on Kubernetes (Minikube) for MySQL – Part II of III

vitess kubernetes mysql

In this blog post, I’d like to share some experiences in setting up a Vitess environment for local tests and development on OSX/macOS. As previously, I have presented How To Test and Deploy Kubernetes Operator for MySQL(PXC) in OSX/macOS, this time I will be showing how to Run Vitess on Kubernetes.
Since running Kubernetes […]

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Introduction to Vitess on Kubernetes for MySQL – Part I of III

Vitess on Kubernetes for MySQL 1

In this blog post series, we will discuss an overview of Vitess technology. Vitess is a database clustering solution for horizontal scaling of data sets currently suitable to 250Gb – 300Gb in sizes*. It’s a proven technology used by several web-scale companies including YouTube. PlanetScale is the company behind developing and supporting this open-sourced […]

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