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Virtual machines and containers solve different problems. A VM virtualizes a whole machine; a container packages an application and its libraries and shares the host's operating system kernel. Neither is better in general, and plenty of healthy environments run both.
| Virtual machine | Container | |
|---|---|---|
| Isolation | Strong, separate operating system | Process-level, shares the host kernel |
| Start-up time | Minutes | Seconds or less |
| Density | Lower: each VM carries a full OS | Higher: many per host |
| Best for | Legacy software, Windows servers, strict isolation | Modern services, microservices, repeatable deployments |
| Operating cost | Patching each OS | Image builds, registry, orchestration |
When Kubernetes is overkill
Kubernetes is powerful and also a lot to run. If you have a handful of services and one team, a managed container service such as Amazon ECS on Fargate or AWS App Runner gives you containers without cluster administration. Many small teams spend more time maintaining a cluster than shipping product.
When Kubernetes earns its keep
- Many services owned by several teams, each deploying on its own schedule.
- A need for portability across clouds or on-site and cloud together.
- Heavy autoscaling or batch workloads that benefit from bin-packing.
- An ecosystem need: service mesh, operators or tooling that assumes Kubernetes.
Container habits that pay off
- Containerize first with Docker, then choose where to run it. The image is the portable part.
- Use small base images, run as a non-root user and scan images in the pipeline.
- One process per container, with configuration from environment variables or a secrets service.
- Pin image versions (ideally by digest) so a rebuild never changes what you deploy.
- Keep stateful systems, such as databases, on a managed service unless you have a strong reason not to.