Docker vs Kubernetes: let’s see how they differ

We still regularly hear the question: is it better to use Docker or Kubernetes? It’s one of the most persistent misunderstandings in the container ecosystem.

The short answer is: Docker and Kubernetes are not direct competitors. They sit at different layers of the same stack and most production environments use both. What has changed is the ecosystem around them: Kubernetes removed the dockershim, containerd became the de-facto runtime, Docker shipped a major Engine v29 release.

This updated guide is written for sysadmins and MSPs who need a current, accurate picture of where these two technologies stand in 2026 and how to choose between them.

What is Docker?

Docker is a containerization platform: a set of tools that lets you build container images, run them as isolated processes on a host (containers), and share them through registries such as Docker Hub or a private OCI-compliant registry.

The core component is the Docker Engine, a client/server application made of:

• a long-running daemon process (dockerd),
• a REST API for interacting with the daemon,
• the docker CLI.

Underneath the daemon, Docker has used containerd as its low-level runtime for several years. With Docker Engine v29, released at the end of 2025, this alignment has been completed: the containerd image store is now the default for new installations, and Docker has officially raised the minimum API version to 1.44 (Moby v25), making versions older than 25 end of life. For sysadmins this matters because the new daemon will refuse to accept clients running API 1.43 or below unless DOCKER_MIN_API_VERSION is explicitly overridden.

In day-to-day work, Docker in 2026 is still the tool of choice for:

• Building container images from a Dockerfile.
• Running single containers or local multi-container stacks via Docker Compose.
• Developer-side workflows on workstations (Docker Desktop on Windows, macOS and Linux).
• Pushing OCI-compliant images to registries that will then be pulled by orchestrators.

Worth noting for sysadmins working on Red Hat-derived distributions: Podman, the daemonless, rootless container engine maintained by Red Hat, has become the default container tool on RHEL, Fedora, Rocky Linux and AlmaLinux. It is largely CLI-compatible with Docker (alias docker=podman is a common starting point) and produces OCI images that work identically in Kubernetes. For Docker-based workflows you don’t need to switch, but on RHEL family hosts Podman is what you’ll find pre-installed.

Docker remains the dominant build tool and the OCI image format Docker popularized is consumed by virtually every orchestrator on the market, Kubernetes included.

What is Kubernetes?

Kubernetes (K8s) is an open-source container orchestration platform, originally developed at Google and now maintained by the Cloud Native Computing Foundation (CNCF). It provides a declarative API that describes what you want running (which workloads, how many replicas, on which nodes, exposed how) and a control loop that continuously reconciles the cluster state with that desired state.

Kubernetes handles the operational complexity that emerges when you scale containers across multiple hosts: scheduling, service discovery, load balancing, rolling updates, self-healing, secret and config management, horizontal autoscaling, storage abstraction and network policy enforcement.

Release cadence and supported versions

Kubernetes follows a release cadence of roughly four months (about three minor versions per year) with an N-2 support policy: only the three most recent minor versions receive security and bug fixes, for a total support window of about 14 months per release.

As of mid-2026, the supported versions are:

Version	Latest patch	Status	End of Life
1.37	1.37.0	Current stable	2027-10-28
1.36	1.36.4	Current stable	2027-06-28
1.35	1.35.8	Supported	2027-02-28
1.34	1.34.11	Maintenance mode (critical fixes only)	2026-10-27

With Kubernetes 1.37 shipped on 26 August 2026, version 1.34 entered maintenance mode on 27 August 2026 and drops out of the actively-maintained branches once it reaches end of life on 27 October 2026; anything on 1.33 or older should already be treated as a security liability in any environment you are responsible for. Always cross-check current support status against kubernetes.io/releases before planning an upgrade.

The container runtime: containerd, not Docker

Kubernetes nodes need a CRI-compliant container runtime to actually start containers in pods. Since Kubernetes v1.24 (May 2022) the built-in dockershim has been removed: kubelet now talks directly to the runtime via the Container Runtime Interface (CRI), and the dominant runtimes are containerd and CRI-O.

This is one of the most common sources of confusion in 2026. “Kubernetes removed Docker” doesn’t mean Kubernetes can no longer run Docker-built images – it can, because those images are OCI-compliant and any CRI runtime understands them. It means Kubernetes no longer ships a translation layer to drive the full Docker Engine as its runtime. The CRI runtime (containerd, CRI-O, or the Mirantis-maintained cri-dockerd if you really need it) replaces that role.

For sysadmins this is mostly a non-issue today: every managed service (EKS, GKE, AKS) has been containerd-only for years, and self-managed clusters built with kubeadm default to containerd as well.

So why does the “Docker vs Kubernetes” question keep coming up?

Two reasons.

First, Docker historically shipped its own orchestrator, Docker Swarm, which was a direct alternative to Kubernetes. So at one point the comparison was technically valid – for orchestration only. We’ll come back to Swarm in a moment.

Second, Docker Desktop bundles a local single-node Kubernetes cluster, and many developers learn both tools at the same time. The result is that “Docker” and “Kubernetes” end up mentioned in the same breath as if they were interchangeable, even though they live at different layers:

Layer	Tool
Image format and registry	OCI / Docker Hub / private registries
Image build	Docker, Buildah, Kaniko, BuildKit
Container runtime (low level)	containerd, CRI-O, runc
Single-host runtime + tooling	Docker Engine
Multi-host orchestration	Kubernetes, Docker Swarm

Docker operates on the bottom three layers. Kubernetes lives at the top.

Where Docker Swarm fits in 2026

Docker Swarm is Docker’s own orchestration mode, built directly into Docker Engine and driven via the standard Docker CLI. A cluster is initialised with a single `docker swarm init`, services are deployed using the same Compose file format developers already know, and the operational model is intentionally minimal: manager nodes, worker nodes, services, tasks. No separate control plane to install, no YAML manifests beyond Compose, no CRDs.

For years this made Swarm the obvious “lightweight” alternative to Kubernetes. In 2026 the picture is more nuanced. Swarm is still maintained, still ships with Docker Engine, and still runs production workloads – but it has received very little in the way of new features compared to the pace of the Kubernetes ecosystem, and the role of “simple orchestrator for small clusters” has largely shifted to lightweight Kubernetes distributions like K3s and MicroK8s (covered later in this guide).

For a sysadmin or MSP evaluating Swarm today, the honest summary is this:

• Reasonable choice for small, stable environments where simplicity is the point: a handful of services across two or three nodes, internal tools, homelabs, or estates where the team already knows Docker and doesn’t want to take on Kubernetes operationally.
• Not the default choice for new projects of meaningful size, multi-tenant deployments, or anything that needs the wider CNCF ecosystem (Helm charts, operators, service mesh, GitOps tooling like Argo CD or Flux).
• Worth keeping in mind if you inherit an existing Swarm cluster: it’s not broken and you don’t necessarily need to migrate it tomorrow, but new investments are better directed elsewhere.

Kubernetes is much more complex than Swarm and provides far more functionality, especially around scale, security primitives, and the surrounding ecosystem. The trade-off is the same it was in 2022 – simplicity vs. capability – but the centre of gravity in the industry has clearly moved.

How Docker and Kubernetes actually work together

In a typical 2026 pipeline the two technologies are stacked, not chosen between:

1. Build. A developer writes a Dockerfile and uses Docker (or BuildKit) to build an OCI image locally.
2. Test. The image is run locally via docker run or docker compose, or against the single-node Kubernetes cluster bundled with Docker Desktop.
3. Push. CI pushes the image to a registry (Docker Hub, GHCR, ECR, GAR, Harbor, Artifactory).
4. Deploy. A Kubernetes-native tool (kubectl, Helm, Argo CD, Flux) deploys the image to a cluster.
5. Run. Kubernetes pulls the image via containerd on each node and runs it inside pods, handling scheduling, scaling, health checks and rollout.

Docker dominates step 1-2; Kubernetes dominates step 4-5; the registry in step 3 is technology-neutral.

Choosing the right tool: a practical guide for sysadmins and MSPs

For the kind of audience we usually write for at The Solving – system administrators, MSPs, IT teams that maintain heterogeneous customer estates – the question is rarely “Docker or Kubernetes?” in isolation. It’s more often “how much orchestration do I actually need, and where do I run it?”

Use Docker on its own when

• A workload runs on a single host and you don’t need automatic failover across nodes.
• You’re packaging an application to ship to customers as a container image without prescribing how they orchestrate it.
• You’re running utility workloads on a sysadmin workstation or a small server: a private DNS, a Wireguard endpoint, a Vaultwarden instance, a few Compose stacks.
• You’re doing local development and CI builds.

Docker Compose alone covers a surprisingly large amount of small-to-medium MSP scenarios.

Use Kubernetes when

• You need to run workloads across multiple nodes with automatic rescheduling on failure.
• You need horizontal autoscaling driven by metrics or events.
• You’re managing dozens to hundreds of services that benefit from a declarative, GitOps-driven workflow.
• You need multi-tenancy with proper isolation, RBAC and network policies.
• The customer’s compliance or platform engineering requirements explicitly mandate it.

Lightweight Kubernetes for MSPs and edge sites

If the workload genuinely needs orchestration but a full upstream Kubernetes cluster is overkill – typically the case at branch offices, edge sites, customer premises and small MSP-managed environments – there are now mature, CNCF-conformant lightweight distributions:

• K3s (Rancher / SUSE). The most widely adopted lightweight distribution. Single binary, opinionated defaults (Traefik as ingress, ServiceLB), SQLite or embedded etcd as the datastore. Production-ready and used at scale in telco edge deployments.
• MicroK8s (Canonical). Snap-based, with a strong add-on system (microk8s enable ingress prometheus). Excellent fit if you’re already standardised on Ubuntu.
• K0s (Mirantis). Single self-contained binary with very few host-OS dependencies; a strong choice for immutable or air-gapped deployments.
• Minikube. Still the reference choice for local development and learning, not for production.

All three distributions are designed to fit comfortably within 1-2 GB of RAM on a single-node setup – a fraction of what a full upstream control plane requires – making them viable on a Raspberry Pi, a fanless industrial PC, or a small VM. Exact memory footprints depend on enabled add-ons and storage backend, so benchmark against your own workload before sizing.

For an MSP, the practical implication is that you can now deploy a CNCF-certified Kubernetes cluster at a customer site, on hardware you’d normally consider too small for orchestration, and manage it remotely with the same kubectl and GitOps tooling you use everywhere else.

Managed Kubernetes: EKS, GKE, AKS

When the cluster lives in a public cloud, the three managed services dominate:

• Amazon EKS. Most flexible, least opinionated. Pairs well with Karpenter for fast node autoprovisioning. EKS Anywhere extends the model to on-premises.
• Google GKE. Often cited as the best “pure” Kubernetes experience, given Google originated the project. GKE Autopilot fully manages the data plane: you only define pods, Google handles nodes. Strongest for AI/ML workloads thanks to TPU support.
• Azure AKS. Three pricing tiers for the control plane: Free (no SLA, intended for dev/test), Standard (financially-backed SLA on the Kubernetes API server, the default for production workloads) and Premium (adds Long-Term Support, extending maintenance for a given Kubernetes version up to 2 years). Tight integration with Entra ID (formerly Azure AD), Azure Monitor and Azure DevOps. Azure Arc extends AKS management to on-premises and edge through a single control plane.
• Red Hat OpenShift. Worth a separate mention for enterprise and regulated environments: OpenShift is a CNCF-certified Kubernetes distribution with an opinionated platform layer on top (built-in CI/CD, internal registry, developer console, stricter security defaults). Available self-managed (OpenShift Container Platform) or as managed services on AWS (ROSA), Azure (ARO), Google Cloud and IBM Cloud. Common choice in finance, healthcare and public sector where Red Hat support contracts and compliance certifications matter.

All four support the current Kubernetes minor versions, with GKE typically the fastest to adopt new releases, followed by AKS, EKS and OpenShift, which intentionally trails upstream to allow for additional hardening and certification. 

Security and operational considerations for 2026

A few things have shifted enough since 2022 to be worth flagging explicitly:

• Supply chain security is now table stakes. Image signing (Cosign / Sigstore), SBOM generation (docker scout sbom, syft) and admission controllers that enforce signed images are no longer optional in regulated environments. Docker’s hardened image initiative and policies like Kyverno or OPA Gatekeeper on the Kubernetes side are the standard responses.
• Runtime CVEs affect both worlds. Docker Engine v29 closed three serious vulnerabilities in docker cp (CVE-2026-41567, CVE-2026-41568, CVE-2026-42306) that allowed a malicious container to execute host binaries or write to arbitrary host paths, and Docker Desktop received an urgent fix earlier in the cycle for CVE-2025-9074 (CVSS 9.3), a container-to-host takeover. Kubernetes isn’t insulated either: every CRI runtime ultimately spawns containers via runc, so a container-escape CVE in runc (such as CVE-2024-21626, fixed in runc 1.1.12) propagates identically to any cluster relying on it. The practical takeaway is that “we only use Docker, not Kubernetes” – or vice versa – doesn’t move you to a safer surface. Both stacks share the same OCI/runc lineage downstream, and both need the same patching discipline.
• API versioning and skew matter. With Docker Engine v29 raising the minimum API to 1.44 and Kubernetes enforcing the N-2 support policy strictly, “we haven’t upgraded in two years” is no longer a tenable position. Plan a regular upgrade cadence, ideally tied to a GitOps flow.
• Backup and disaster recovery don’t disappear in containers. Stateless workloads are easy; stateful workloads (databases in StatefulSets, persistent volumes) still need a real backup strategy. Velero is the canonical Kubernetes-native option; for the host side, the underlying VMs and persistent storage need to be covered by a backup solution at the infrastructure layer as well.

The practical takeaway for sysadmins and MSPs

The original “Docker vs Kubernetes” framing was misleading in 2022 and it’s still misleading in 2026 – only now the picture underneath has evolved.

• Docker is the build tool and single-host runtime almost everyone uses, and Engine v29 plus the containerd image store has consolidated its place in the stack.
• Kubernetes is the orchestrator that the industry has standardised on for anything beyond a single host, with three actively supported minor versions and a four-month release cadence.
• Docker Swarm still exists and still works, but it has stopped being the obvious answer to “I want simple orchestration”; lightweight Kubernetes distributions have largely taken that role.
• Lightweight K8s (K3s, MicroK8s, k0s) are how MSPs and sysadmins bring real orchestration to small sites and edge devices in 2026.
• Managed K8s (EKS, GKE, AKS, OpenShift) is how most organisations consume Kubernetes in the cloud, and which one you pick is driven more by the rest of your cloud footprint, vendor relationships and compliance requirements than by Kubernetes itself.

For a sysadmin or MSP starting today, the recommendation hasn’t really changed: get comfortable with Docker first, because it’s the universal entry point to containerization, and learn enough Kubernetes – starting from a lightweight distribution like K3s – to operate the orchestration layer that has become the de-facto standard for production container workloads.