Django is a popular framework for Python application developers. It includes packages which make tasks like authorization and content administration easier. Django supports a number of databases including MySQL which makes it possible to run a Django application over Vitess without having to change the application code. Let’s take a look at how to combine the strengths of these two open source frameworks. We built this example using Vitess operator. You can see the details of the implementation in the blog post Vitess Operator for Kubernetes.
Editor’s Note: Because our bloggers have lots of useful tips, every now and then we update and bring forward a popular post from the past. Today’s post was originally published on November 26, 2019.
It’s not uncommon these days for us to use a high availability stack for MySQL consisting of Orchestrator, Consul and ProxySQL. You can read more details about this stack by reading Matthias Crauwels’ blog post How to Autoscale ProxySQL in the Cloud as well as Ivan Groenwold’s post on MySQL High Availability With ProxySQL, Consul and Orchestrator. The high-level concept is simply that Orchestrator will monitor the state of the MySQL replication topology and report changes to Consul which in turn can update ProxySQL hosts using …[Read more]
Kubernetes operators are meant to simplify the deployment and management of applications. Our Percona Kubernetes Operator for Percona XtraDB Cluster serves the purpose, but also provides users the flexibility to fine-tune their MySQL and proxy services configuration.
The document Changing MySQL Options describes how to provide custom
configuration to the operator. But what would happen if you made a mistake and specified the wrong parameter in the configuration?
I already deployed my Percona XtraDB Cluster and deliberately submitted the wrong
spec: ... pxc: configuration: …[Read more]
Kubernetes has been a big trend for a while now, particularly well-suited for microservices. Running your main databases on Kubernetes is probably NOT what you are looking for. However, there’s a niche market for them. My colleague Stephen Thorn did a great job explaining this in The Criticality of a Kubernetes Operator for Databases. If you are considering running your database on Kubernetes, have a look at it first. And, if after reading it you start wondering how the Operator works, Stephen also wrote an Introduction to Percona Kubernetes Operator for Percona XtraDB Cluster (PXC), which presents the Kubernetes architecture and how the Percona Operator simplifies the deployment of a …[Read more]
Our recent survey showed that many organizations saw unexpected growth around cloud and data. Unexpected bills can become a big problem, especially in such uncertain times. This blog post talks about how Kubernetes scaling capabilities work with Percona Kubernetes Operator for Percona XtraDB Cluster (PXC Operator) and can help you to control the bill.
Kubernetes is a container orchestrator and on top of it, it has great scaling capabilities. Scaling can help you to utilize your cluster better and do not waste money on excessive capacity. But before scaling we need to understand what capacity is and how Kubernetes manages CPU and memory resources.
There are two resource concepts that you should be aware of: …[Read more]
Introduction # In this blog, I would like to explore Vitess Operator for Kubernetes. This post demonstrates the sample implementation of Vitess in Kubernetes topology. I also explore common DBA tasks by demonstrating how they are handled in the Vitess ecosystem. Vitess, out of the box, comes with a lot of tools and utilities that one has to either incorporate or develop to manage MySQL topology. Let’s take a look at the capabilities of Vitess in these areas and demonstrate how they are performed under the operator realm.
In my talk on Percona Live (download the presentation), I spoke about how we can use Percona Kubernetes Operators to deploy our own Database-as-Service, based on fully OpenSource components and independent from any particular cloud provider.
Today I want to mention an important tool that I use to test our Operators: ChaosMesh, which actually is part of CNCF and recently became GA version 1.0.
ChaosMesh seeks to deploy chaos engineering experiments in Kubernetes deployments which allows it to test how deployment is resilient against different kinds of failures.
Obviously, this tool is important for Kubernetes Database …[Read more]
Kata containers are containers that use hardware virtualization technologies for workload isolation almost without performance penalties. Top use cases are untrusted workloads and tenant isolation (for example in a shared Kubernetes cluster). This blog post describes how to run Percona Kubernetes Operator for Percona XtraDB Cluster (PXC Operator) using Kata containers.
Prepare Your Kubernetes Cluster
Setting up Kata containers and Kubernetes is well documented in the official github repo (cri-o, …[Read more]
One of the most exciting storage-related features in Kubernetes is Volume snapshot and clone. It allows you to take a snapshot of data volume and later to clone into a new volume, which opens a variety of possibilities like instant backups or testing upgrades. This feature also brings Kubernetes deployments close to cloud providers, which allow you to get volume snapshots with one click.
Word of caution: for the database, it still might be required to apply fsfreeze and FLUSH TABLES WITH READ LOCK or
LOCK BINLOG FOR BACKUP
It is much easier in MySQL 8 now, because as with atomic DDL, MySQL 8 should provide crash-safe consistent snapshots without additional locking.
Let’s review how we can use this feature with Google Cloud Kubernetes Engine and …[Read more]
In Percona Kubernetes Operator for Percona XtraDB Cluster (PXC) versions prior to 1.5.0, there were two methods for upgrading PXC clusters, and both of these use built-in StatefulSet update strategies. The first one is manual (OnDelete update strategy) and the second one is semi-automatic (RollingUpdate strategy). Since the Kubernetes operator is about automating the database management, and there are use cases to always keep the database up to date, a new smart update strategy was implemented.
Smart Update Strategy
The smart update strategy can be used to enable automatic context-aware upgrades of PXC clusters between minor versions. One of the use cases for automatic upgrades is if you want to get security …[Read more]