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This article mainly introduces "how many clusters are needed for K8S to run an application". In daily operation, I believe many people have doubts about how many clusters are needed for K8S to run an application. The editor consulted all kinds of materials and sorted out simple and easy-to-use operation methods. I hope it will be helpful to answer the question of "how many clusters does K8S need to run an application?" Next, please follow the editor to study!

The problem lies.

As a software creator, you should develop and run multiple applications. Also, you should run multiple instances of these applications in different environments-for example, you should have development, testing, and production environments. So, the combination of different environments and applications, we can get a "matrix":

In the above example, there are 3 applications and 3 environments, and the pairwise are combined into 9 application instances. Each application instance is a separate deployment unit that can be run independently.

Note that an application instance may consist of multiple components, such as front end, back end, database, and so on. In a microservice application, an application instance will consist of all microservices.

So as a Kubernetes user, you will encounter some problems at this time:

Should all application instances be run in one cluster?

Or should each application instance have a separate cluster?

Or should we combine the above two?

All of these are effective methods-Kubernetes is a flexible system that doesn't directly tell you how to use a particular one.

With regard to the matching of clusters, you have the following options:

A large shared cluster

Many small disposable clusters

Each application has a cluster

There is a cluster in each environment

The first two methods are the extremes of large clusters and small clusters, respectively, and their size relationships are as follows:

All in all, if a cluster contains a large number of nodes and Pod, it can be defined as larger than another cluster. For example, a cluster with 10 nodes and 100Pod is larger than a cluster with 1 node and 10 Pod.

After clarifying the concepts and options, let's start now!

A large shared cluster

This approach means running all your workloads in a cluster:

In this way, we can use the cluster like a common infrastructure platform-- no matter what you need to run, you can deploy it to an existing Kubernetes cluster.

There is a concept of namespaces in Kubernetes that logically separate parts of the cluster from each other. In the above cases, you can create a separate namespace for each application instance.

At this point, the study of "how many clusters does K8S need to run an application" is over. I hope to be able to solve everyone's doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

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