In a single-node cluster, or with Pods that are limited to a dedicated Node, node-mounted volumes can be a great fit. Now persistent data can be made available to any Pod running on that Node, but the limitation should be immediately clear: Only Pods on that Node can access the data. If you need data to persist beyond the lifespan of a particular Pod, you might consider using a volume mounted at the Node level. Pod-mounted volumes are most suited to temporary caches and other short-term uses that you don’t expect to last any longer than a given Pod-for example, this technique can be used to mount a Secret to a Pod (which we’ll discuss in depth in the next lesson). But you’re never going to store, say, user account data this way, because as soon as the Pod is erased, any data the container has written will be gone. If the container is replaced within the Pod-for example, if it has failed and been automatically replaced-the new container will still have access to the volume. This approach is relatively simple-and has its uses-but your data won’t be very durable. Volumes mounted to PodsĬontainers within a Pod can mount a writable volume at the Pod layer, similar to the way a Docker container might mount a volume on a host system. Let’s start at the top of the pyramid and decide which solution will be most suitable for our purposes. You can think of these approaches as steps on a pyramid, with the duration and reliability of data persistence running more or less inverse to the complexity of the solution. This is a little out of step with the philosophy and assumptions of Kubernetes, but it’s a fundamental requirement that the system has to be able to handle.Īnd so it can! There are various ways in which Kubernetes can persist data, at varying degrees of persistence and complexity. For stateless applications-apps that don’t store or modify changeable data-this is perfect.īut most apps are stateful : they change into different states as users or clients create, update, or delete data that may persist over time. In Kubernetes, containers are typically presumed to be ephemeral and immutable, which is to say that we expect any given container to be short-lived, replaceable, and unchanging in its contents. Running a Stateful Web App at Scale on Kubernetes How to Use StatefulSets and Create a Scalable MySQL Server on Kubernetes How to Use Kubernetes Secrets with Environment Variables and Volume Mounts Persistent Data and Storage with Kubernetes ← You are here Setting Up a Kubernetes Learning Environment We’ll start with one of the thornier challenges of decomposition: how to persist data in Kubernetes. The monolithic To Do app is built on Node.js and MySQL, using a MySQL database to store user account data and tasks. This will give us a hands-on, project-based approach to learning major concepts in Kubernetes development such as Volumes, Secrets, and Ingress. Specifically, we will decompose a simple To Do app with a web client and functionality for users to create accounts, log in, and save their own notes. In the next few lessons, we’re going to work step-by-step to break down a monolith into dedicated Services running on Kubernetes. If you’re a developer whose organization is moving to Kubernetes, there’s a pretty good chance that you’re going to spend some time decomposing existing monolithic applications into microservices that take advantage of Kubernetes’ capabilities. These lessons assume a basic familiarity with the Linux command line and a Unix-like operating system-beyond that, you don’t need any special preparation to get started. In this series, we’ll break down core cloud native concepts, challenges, and best practices into short, manageable exercises and explainers so you can learn five minutes at a time. One of the biggest challenges for implementing cloud native technologies is learning the fundamentals-especially when you need to fit your learning into a busy schedule.
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