Photo by Hu Shengcai on Unsplash

Photo by Hu Shengcai on Unsplash

A Hands-On Comparison of K3s, MicroK8s, and Vanilla K8s

Out of the Box

Article from ADMIN 91/2026
By , By
We look at full-scale Kubernetes and alternative lightweight distributions in edge computing environments.

Kubernetes has emerged as the benchmark for managing containerized and microservices applications within cloud-native environments. Its capacity to manage substantial workloads effectively across thousands of nodes, on-premises clusters, and multicloud configurations has rendered it indispensable for contemporary DevOps methodologies. At its essence, Kubernetes automates the deployment, scaling, and lifecycle management of containers, providing both developers and operators a robust framework.

Nonetheless, as the demand for containerization extends beyond data centers into resource-constrained and edge environments, full-scale Kubernetes, often referred to as vanilla K8s (referred to as K8s throughout this article), might prove to be excessive. In scenarios where simplicity, speed, and a reduced footprint are paramount, lightweight Kubernetes distributions such as K3s and MicroK8s present viable alternatives (see the "Naming Note" box). Each distribution presents its own set of tradeoffs concerning installation, system prerequisites, features, and performance.

Naming Note

The word Kubernetes comes from the Greek word meaning "helmsman" or "pilot," symbolizing its role in steering containerized workloads. The abbreviation "K8s" is a numeronym, where the "8" represents the eight letters between "K" and "s" in "Kubernetes." The K8s distribution refers to the unmodified, upstream version maintained by the Cloud Native Computing Foundation (CNCF), serving as the reference implementation. The name "K3s" is a play on K8s, implying it is "five less" than K8s both numerically and metaphorically. It reflects that K3s is designed to be five times lighter in terms of binary size, memory usage, and deployment complexity, making it ideal for edge and resource-constrained

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