Containerization solutions aim to provide viable flexibility to containerize and ship application code. However, complex application deployments and infrastructure automation demand a good container orchestration tool.
Additionally, to deploy applications with complex architectures, container orchestration has to be done with proper plumbing. A proper DevOps orchestration tool caters to these demands to achieve faster application delivery cycles and scale according to the application resource requirements.
Reigning over half of the orchestration environment, Kubernetes has become the de facto container orchestration tool for DevOps. With its release in 2014, Kubernetes adoption has increased substantially owing to its excellent scheduler built and resource manager that helps to deploy containers in a more efficient way and are highly accessible, and offers many functionalities that native docker tools don’t provide.
According to CNCF’s Cloud Native Landscape, there are more than 109 tools to manage containers. However 89% consumers use different forms of Kubernetes. Even competitors in the field upon failing to impress their audience switched to Kubernetes container orchestration programs for their users.
This raises an important question:
What exactly is k3d?
k3d is a wrapper to set up a lightweight Kubernetes cluster using the Docker engine. The nodes are set up in the form of containers emulating real-life clusters in a condensed way. And all of this can be done in just 3-4 commands. To set up a local k3d’s cluster, check out their official website.
Initially, it used to be quite difficult for most beginners to set up a local cluster from scratch and its command-line tool kubectl. However, spending more time trying to figure out how to set up a Kubernetes cluster wouldn’t be very productive, as most organizations that intend to use this orchestration tool or who are using it may have already launched the tool and may also be using kubectl to deploy, scale and debug applications.
How do users leverage k3d?
Experienced users usually only need to evaluate a new application that has been released. Generally, they are lightweight and are tested out locally just before deploying them to production. It is at this stage of the process that k3d becomes useful, to easily set up the application to test out its features before deploying it.
Over time, k3d has evolved into an operational tool to test some Kubernetes features in an isolated environment. With k3d one can easily create multi-node clusters, deploy changes on top or simply halt a node and see how Kubernetes reacts and possibly reschedules the app to other nodes.
Additionally, k3d can be used in continuous integration systems to quickly spin up a cluster, deploy a test stack on top of it and run integration tests. It provides hassle-free decommission on the cluster as a whole, with no leftovers.
k3d or minikube: What technology should you bank on?
minikube is undoubtedly one of the most popular local Kubernetes clusters. On proper usage and analysis of both k3d and minikube, certain key differences that we came across are highlighted below:
- Ease of installation: k3d, no doubt, is much easier to install and get started with than minikube. While minikube installation is not necessarily hard, it cannot be compared with the extremely simple installation of k3d.
- Hardware requirements: k3d is extremely lightweight and as such takes away minimal performance while running when compared to minikube.
- Learning: minikube is a single node cluster that sometimes limits certain learnings like scheduling concepts. A k3d can run a multi-node cluster which gives better exposure to learnings.