Kubernetes aims to be the go-to orchestration system for distributed applications. The platform has gained popularity among developers and enterprises as it offers a scalable solution for running complex database infrastructures.
It supports stateful workloads using its API objects that manage multi-sharded leader and follower architectures, stable unique network identifiers, and persistent storage. It also enables dynamic additions and deletions of resources, ensuring a consistent deployment across all environments.
Getting Started
Kubernetes has become the standard for managing containerized systems in the cloud. It simplifies lifecycle management and provides tools for deploying, scaling, and auto-scaling containers. It also has a feature for storing data in stateful sets, a flexible way to manage databases. Kubernetes, however, needs to gain a greater understanding of how different database systems function and can create complexities that must be mitigated with careful management.
To run Cassandra on Kubernetes, you need a k8s cluster, open source or commercial, and the kubectl command-line tool. Once you have this, you can start by installing a cast operator. This will provide a translation layer pairing what Kubernetes needs to function with the required database system. Several operators are in the market, with five distinct maturity levels.
Cassandra is a popular choice for enterprise applications because it offers the scalability and strength of a distributed database. It has been used by companies like Apple, Spotify, CapitalOne, and Mcdonald’s to ensure that their services can be accessed anytime and anywhere. Bringing it together with Kubernetes enables these two technologies to work seamlessly, keeping data closer to the business and driving for superior performance. This is known as a hybrid architecture. Knowing your options when integrating a Cassandra database into your cloud-native application is essential.
Deploying Cassandra
Cassandra is a highly available database that can handle a large amount of data across multiple nodes. It is a distributed system, meaning it can store data in many different places to prevent any one location from being lost. It also uses replication to ensure that any changes to data are always reflected across the whole cluster. Even if a single node fails, other nodes will still have the same data, so the application can continue working.
Cassandra can be deployed on-premises or in a cloud provider, such as Google Kubernetes Engine (GKE), Amazon Elastic Compute Cloud (ECC), Pivotal Container Service (PKS), and more. It can be used as a multi-datacenter environment, which allows you to scale out for peak times such as Black Friday sales or a new product launch.
Cassandra is an excellent choice for a database on Kubernetes because of its ability to be easily scaled and low latency. It is a highly reliable database used by thousands of companies, including Netflix, Twitter, Reddit, and Apple, to handle their data. Kubernetes provides an excellent platform for managing these databases, with features that make it easy to deploy and scale up your Cassandra instances. In this tutorial, you will use to create a Cassandra cluster on GKE with three nodes on the same rack.
Managing Cassandra
As infrastructure systems are increasingly standardized on Kubernetes, managing the lifecycle of your containerized system is getting much more accessible. But the problem becomes more complex when you include your database. With long boot times and the fact that Cassandra is very picky about its filesystem and network topology (storing a copy of its database inside each node), keeping your data consistent can be challenging. This is especially true if a server orchestration system handles containers failing by spawning new ones. In that case, a new instance may come up with existing filesystem and network information which can cause it to crash or write inconsistent data.
One of the things that makes Cassandra an ideal data platform is its multiple-replica mechanism. It keeps copies of each token range across nodes and in different locations, so if some nodes fail (or even whole data centers), other nodes can step in. This enables you to build ‘always-on’ applications with zero downtime, where users can access the same data pools.
To make this application deployment easy, you need a way to deploy and manage your Cassandra cluster within Kubernetes. The good news is that several viable solutions are now to help you do this, both open-source and fully-featured SaaS. We recommend checking out a solution like our Kubernetes Operator for Cassandra. It allows you to express Cassandra concepts, such as data centers and nodes, using Kubernetes resources,, Pods, and the Kubernetes controller.
Monitoring Cassandra
Cassandra is a highly scalable database that can handle hundreds of terabytes of data across multiple data centers. Its nonrelational design allows it to perform reads quickly and is ideal for applications that must process high volumes of writes in real-time.
However, deploying and managing Cassandra in Kubernetes can be challenging. Several different tools can help, from open-source projects to fully-featured SaaS solutions. However, finding a solution that works well in your environment can be complex.
Unlike other databases that use a master-slave architecture, Cassandra uses peer-to-peer communication between units in a cluster to share and manage data. This eliminates a single point of failure and is one of the key features that distinguishes Cassandra from its competitors.
While Cassandra is highly scalable, it requires significant resources to run correctly. In addition, it is essential to monitor the performance of your Cassandra cluster to ensure that all nodes are operating correctly.
These open-source solutions allow you to gather and analyze Cassandra metrics. It also provides a comprehensive, customizable monitoring solution for Apache Cassandra. It can give valuable node-level and cluster metrics, including the number of requests per second each node receives. Sign up for a free trial today to learn more about our platform and see how it can improve your application performance.
