K3s, despite its impressive feature set and Kubernetes compliance, is designed to run on surprisingly little hardware.
Let’s see K3s in action on a Raspberry Pi 4 with 4GB of RAM. We’ll start by installing K3s and then observe its resource footprint.
# Install K3s
curl -sfL https://get.k3s.io | sh -
# Wait a minute for the agent to start
sleep 60
# Check resource usage of the k3s process
ps aux | grep k3s
You’ll likely see output similar to this, with the k3s server process consuming very little CPU and memory:
root 1234 0.2 0.5 123456 23456 pts/0 Sl+ 10:00 0:01 /usr/local/bin/k3s server
...
The k3s server process, which is the core of the K3s control plane, typically idles with a CPU usage well under 1% and memory consumption in the tens of megabytes. This efficiency is a deliberate design choice by Rancher Labs.
K3s achieves this by stripping out legacy, optional, or cloud-provider-specific features found in full Kubernetes distributions. It bundles critical components like containerd, Flannel (or Cilium), CoreDNS, and Traefik (or Nginx) into a single binary. This consolidation reduces the number of separate processes and inter-process communication overhead. Furthermore, K3s uses SQLite as its default database, which is significantly lighter than etcd, especially for smaller deployments.
The primary problem K3s solves is making Kubernetes accessible for edge computing, IoT, CI/CD pipelines, and development environments where traditional Kubernetes clusters would be overkill and too resource-intensive. It provides a fully functional, certified Kubernetes API but with a drastically reduced footprint.
The key levers you control in K3s are primarily through its configuration options during installation or via its configuration file (/etc/rancher/k3s/config.yaml). You can specify different network plugins, ingress controllers, disable features like the embedded etcd (if you intend to use an external database), or configure storage drivers. For instance, to use Cilium instead of Flannel, you’d pass --flannel-backend=none --kube-controller-manager-arg no-leader-election=true --kube-scheduler-arg no-leader-election=true --cluster-cidr 10.42.0.0/16 --service-cidr 10.43.0.0/16 --kube-apiserver-arg service-node-port-range=1-65535 --kube-controller-manager-arg node-cidr-mask-size-ipv4=24 --kube-controller-manager-arg node-cidr-mask-size-ipv6=112 --kube-proxy-arg mode=iptables --disable servicelb --disable traefik --disable local-storage --disable coredns --disable metrics-server --disable snapshot-controller --disable cert-manager --disable CSI-Driver-etcd --disable CSI-Driver-local-path --disable CSI-Driver-nfs --disable CSI-Driver-smb --disable network-policy --disable kubernetes-version=v1.27.3+k3s1 --disable admission-controllers=ValidatingAdmissionWebhook,MutatingAdmissionWebhook --disable cloud-controller to the installation script or add these to config.yaml. While many of these are for disabling features to reduce the footprint even further, you can also enable specific components or change their configurations.
When K3s starts, it initializes a k3s server process. This process is responsible for running the Kubernetes API server, controller manager, scheduler, and etcd (or SQLite). It also manages the lifecycle of the containerd runtime and the CNI plugin. The magic of its low resource usage comes from carefully selecting and compiling essential Kubernetes components, optimizing their startup, and using efficient defaults for internal services like its embedded database.
The fact that K3s bundles containerd directly into its binary means you don’t have a separate docker daemon or containerd service running independently. This integration streamlines resource management and reduces the overall system overhead. The k3s server process itself is a Go binary that orchestrates these components, making it a single, efficient entry point for managing your cluster.
Many users are surprised to learn that K3s uses a SQLite database by default, which is embedded within the k3s server process itself. This avoids the need for a separate, resource-hungry etcd cluster, which is a common bottleneck in larger Kubernetes deployments. For production environments requiring higher availability, K3s also supports external databases like PostgreSQL, MySQL, and etcd, but the default SQLite is remarkably capable for many use cases and significantly contributes to the minimal resource footprint.
The next step after getting your K3s cluster running efficiently is understanding how to deploy applications to it and manage their resources.