What is the difference between containers and virtual machines?
A virtual machine (VM) is a complete computer emulated in software: a hypervisor gives it virtual hardware, and it boots its own operating system and kernel. A container is an isolated group of processes that shares the kernel of the host it runs on, so it carries only the application and its libraries. Containers are smaller and start faster. VMs provide a stronger isolation boundary.
How containers and virtual machines differ
Both let several applications share the same physical hardware, but they separate them at different layers. NIST’s Application Container Security Guide (SP 800-190) puts it this way: VMs “use a hypervisor that provides hardware-level isolation”, and each VM “includes a complete guest OS”. With containers, “multiple apps share the same OS kernel instance but are segregated from each other”.
On Linux, that segregation comes from kernel features: namespaces give each container its own view of processes, network interfaces and file systems, and control groups (cgroups) limit how much CPU and memory it can use. Every container on a host still makes its system calls to the same kernel.
| Virtual machine | Container | |
|---|---|---|
| Isolation layer | Hypervisor, hardware virtualization | Host kernel features (namespaces, cgroups) |
| Operating system | Own guest OS and kernel per VM | Shares the host kernel |
| Image contents | Full OS plus application | Application, libraries and metadata |
| Startup | Boots a kernel and init system | Starts a process |
| Density per host | Lower, each VM reserves memory for its OS | Higher, no per-instance OS overhead |
| OS mix on one host | Linux and Windows VMs side by side | Linux hosts run only Linux containers |
| Typical tooling | KVM, VMware ESXi, Hyper-V, Proxmox VE | containerd, CRI-O, Docker Engine, Kubernetes |
Security boundary differences
The shared kernel is the main security difference. NIST SP 800-190 states that containers “do not offer as clear and concrete of a security boundary as a VM”, and that a shared kernel “invariably results in a larger inter-object attack surface than seen with hypervisors”. A kernel vulnerability or a misconfigured privileged container can let a process reach the host and every other container on it.
For that reason, NIST recommends that you only group containers “with the same purpose, sensitivity, and threat posture on a single host OS kernel”. Workloads you do not trust, such as customer-submitted code or code written by AI agents, need either separate nodes or a sandboxed runtime. The options are compared in how to isolate untrusted workloads.
Why most Kubernetes nodes are VMs
Containers did not replace VMs. In most clusters they run on top of them. The Kubernetes documentation on node autoscaling notes that “most commonly, the resources backing the Nodes are Virtual Machines”. Most cloud compute is sold as VMs, and the hypervisor gives each node a hard boundary from other tenants on the same hardware.
NIST describes the same pattern: organizations “use VMs to deploy, partition, and manage their hardware, while using containers to package their apps”. Running nodes directly on physical servers removes the hypervisor layer, which teams consider for GPU and latency-sensitive workloads. The trade-offs are covered in Kubernetes on bare metal vs virtual machines.
The middle ground
The line between the two has blurred. Kubernetes lets you choose a different runtime per Pod through RuntimeClass, stable since Kubernetes 1.20. The documentation names the use case directly: Pods that need “a high level of information security assurance” can run “in a container runtime that uses hardware virtualization”.
- Kata Containers is an open-source container runtime that starts each Pod inside a lightweight VM with its own guest kernel. Pods keep using standard images and manifests.
- gVisor is an application kernel that intercepts a container’s system calls and handles them in user space, so the workload never talks to the host kernel directly. Its OCI runtime is called
runsc. - KubeVirt goes the other way and runs full virtual machines as Kubernetes objects, next to containers in the same cluster.
KubeVirt is the usual path for teams that want one platform for both VMs and containers. See whether Kubernetes can run virtual machines and the blog post on Proxmox vs Kubernetes for how the platforms compare.
When to use each
Choose a container when:
- The application runs on Linux and you control or trust its code.
- You deploy often and want fast startup, small images and the same artifact in every environment.
- You want an orchestrator such as Kubernetes to handle scaling and failover.
Choose a virtual machine when:
- The workload needs its own kernel, a specific kernel version or a different operating system such as Windows.
- You run code you do not trust and need a hardware isolation boundary.
- The software is a packaged appliance or legacy system that expects a full OS.
Many platforms use both: VMs or bare-metal servers as Kubernetes nodes, containers for applications and a sandboxed runtime for the few workloads that need a VM boundary.
Containers and VM isolation on Cloudfleet
Cloudfleet Kubernetes Engine (CFKE) offers Kata Containers as a managed runtime. Once it is enabled on a cluster, a Pod moves into its own lightweight VM by setting runtimeClassName: kata. See Kata Containers in the documentation.