In short: K3s is a CNCF-certified Kubernetes distribution optimized for constrained environments (edge, IoT, labs). K8s refers to the original Kubernetes project, designed for large-scale production clusters. The choice depends on your available resources, deployment context, and operational workload.
K8s: Standard Kubernetes for Enterprise Environments
K8s is the abbreviation of Kubernetes, with the “8” representing the eight letters between the “K” and the “s”. It is the original open-source project maintained by the Cloud Native Computing Foundation (CNCF) and initially developed by Google.
Kubernetes is designed for large-scale production environments: multi-node clusters, high availability, integration with public clouds (AWS, GCP, Azure), or on-premises datacenters. Its control plane includes several separate components: API server, scheduler, controller manager, etcd, deployed independently, which provides maximum flexibility but requires significant operational expertise.
Typical requirements for a production control plane node: at least 2 vCPUs and 2 GB of RAM for Kubernetes components alone, excluding etcd and application workloads.
K3s: A CNCF-Certified Kubernetes Distribution, Not a Fork
K3s is a certified Kubernetes distribution, not an unofficial lightweight version or a fork. Created by Rancher Labs, it was donated to the CNCF in June 2020 and passes the same Sonobuoy conformance tests as all certified distributions. Any valid Kubernetes manifest works on K3s.
Its main goal is to drastically reduce the resources required to run Kubernetes in constrained environments (edge, IoT, CI/CD, labs) without giving up API compatibility.
What K3s Changes Compared to K8s
- A single binary under 70 MB (supporting x86, ARM64, ARMv7, and S390X), including the containerd runtime, Flannel CNI, a Traefik ingress controller, and a Klipper load balancer.
- SQLite as the default datastore in single-node mode instead of etcd. In high-availability configurations (minimum three server nodes), K3s can use embedded etcd or an external datastore (MySQL, PostgreSQL, external etcd).
- Alpha and beta components removed to reduce the attack surface and memory footprint.
Important point: K3s does not remove etcd; it makes it optional. In single-node mode, SQLite is sufficient. In high availability, embedded or external etcd is supported – although the latter is not officially supported by the K3s team.
Resource Footprint
K3s can run with as little as 512 MB of RAM on an agent node. According to the official documentation (updated May 2026), a server node (control plane) requires 2 GB of RAM and 2 CPU cores, excluding application workloads. A load-tested profile is available in the K3s resource profiling guide. It is worth noting that tests on hardware with 1 GB of total RAM showed instability across K3s, k0s, and MicroK8s when deploying real application workloads (even a lightweight Kubernetes cluster still consumes non-negligible control-plane resources).
Key Technical Differences
Datastore
| Scenario | K8s | K3s |
|---|---|---|
| Single-node | etcd required | SQLite by default |
| Multi-node High Availability | etcd | Embedded or external etcd (MySQL, PostgreSQL) |
Runtime and packaging
K8s no longer provides a default runtime since the removal of dockershim (v1.24, 2022). Starting with Kubernetes 1.24, you must install a CRI-compatible runtime (containerd or CRI-O). K3s embeds containerd directly into its binary.
Control Plane Architecture
In K8s, control plane components (API server, scheduler, controller manager) are separate processes. In K3s, they are merged into a single binary, which reduces overhead but limits some advanced isolation configurations.
Scalability
K3s is suitable for moderately sized clusters. In high-availability configurations (3 server nodes, 4 vCPU / 8 GB RAM), the official documentation indicates a capacity of around 1,200 agents. For very large clusters (several thousand nodes), K8s remains the reference.
K3s vs K8s Comparison Table
| Criterion | K3s | K8s |
|---|---|---|
| CNCF certification | Yes (certified distribution) | Yes (original project) |
| Binary size | < 100 MB | Not applicable (separate components) |
| Default datastore | SQLite (single-node) / etcd (high availability) | etcd |
| Embedded runtime | containerd | No (to be installed separately) |
| ARM support | Yes (ARM64, ARMv7) | Yes (depends on the distribution) |
| Default ingress | Traefik (included) | No (to be deployed separately) |
| API compatibility | Required APIs certified by the CNCF | Reference implementation (original project) |
| Documented max scalability | ~1200 agents (High Availability 3 servers) | Several thousand nodes |
| Main use case | Edge, IoT, lab, CI/CD | Enterprise, cloud, datacenters |
| Operational complexity | Low | High |
| Alpha/beta components | Removed | Included |
Use Cases: Which One Should You Choose?
Choose K3s if:
- You deploy on constrained hardware (Raspberry Pi, industrial appliances, edge servers with limited RAM).
- You manage remote IoT or edge clusters, potentially in disconnected environments.
- You need a development or CI cluster that starts quickly, including on modest hardware.
- You want an operational cluster with minimal initial configuration.
Choose K8s (or an enterprise distribution) if:
- You orchestrate hundreds or thousands of production nodes.
- Your workloads require advanced cloud-native integrations (storage, load balancers, IAM) provided by hyperscalers.
- You need alpha or beta API components unavailable in K3s.
- Your organization has a dedicated SRE team operating clusters.
Hybrid Use Cases: K3s and K8s Together
K3s and K8s are not mutually exclusive. Several hybrid architectures are documented in production:
Fleet Management with Rancher
Edge K3s clusters are managed from a central control plane running on K8s or RKE2. The Home Depot (large American retailer with more than 2,300 stores) manages its sites using K3s supervised through Rancher.
K3s for Dev and Staging, K8s for Production
API compatibility guarantees that manifests and Helm charts tested on K3s work in production on an enterprise cluster. This parity reduces surprises when promoting environments.
CI/CD
Test pipelines run on K3s (low cost, fast startup) while production environments use managed K8s clusters.
Managed Kubernetes: A Third Path
Neither K3s nor K8s solves the question of daily operations: updates, certificates, control plane monitoring, or failure management. This is precisely what managed Kubernetes solutions cover.
Hyperscalers (EKS, GKE, AKS) provide this management within their own clouds. But managed solutions also exist outside these ecosystems, especially for organizations that want to retain control over their data and choose sovereign Kubernetes, or even French-operated Kubernetes.
Clever Kubernetes Engine (CKE) is Clever Cloud’s managed Kubernetes service, designed for teams already using Kubernetes and wanting to delegate control plane management (updates, high availability, monitoring) without being constrained to a single hyperscaler. CKE explicitly targets teams that are not fully covered by the traditional PaaS model (multi-runtime use cases, non-twelve-factor workloads, or the need for granular resource control).
FAQ
Is K3s a Kubernetes fork?
No. K3s is a CNCF-certified Kubernetes distribution. It passes Sonobuoy conformance tests and supports the same APIs as K8s. It is not maintained separately from Kubernetes: it follows upstream Kubernetes releases.
Can K3s Be Used in Production?
Yes, with some nuances. K3s is documented for production workloads in constrained environments (edge, IoT). For large-scale clusters or critical workloads with high SLA requirements, K8s (or an enterprise distribution such as RKE2) is more appropriate.
Does K3s Support Helm?
Yes. K3s includes an integrated Helm controller and is compatible with any valid Helm chart.
What Is the Difference Between K3s and K3d?
K3d is a tool that runs K3s inside Docker containers. It further simplifies the creation of local K3s clusters for development, but it is not intended for production use.
Does K3s Run on ARM?
Yes. ARM64 and ARMv7 are natively supported, which explains its popularity on Raspberry Pi devices and industrial appliances.
Managed Kubernetes vs Self-Hosted K3s: Which One Should You Choose?
Self-hosted K3s gives you full control but makes you responsible for operations (updates, security, high availability). Managed Kubernetes delegates this responsibility to an operator, at the cost of dependency on that provider. The choice depends on your operational resources and control requirements.