Is Docker Compose suitable for production?

For many small applications, yes, on a single server with automated deployments, monitoring and backups. Its limits are high availability across machines and automatic rescheduling after a server failure. If you need those, move to a PaaS or Kubernetes.

Do I need a container registry?

If you build images in CI and deploy them to servers, yes. Many Git platforms and cloud providers offer registries, including European providers. A PaaS that builds directly from your repository can make a separate registry unnecessary.

What about Docker Swarm or Nomad?

Both are lighter orchestrators than Kubernetes and still in use. Their ecosystems are smaller, and managed offerings are rare, so for most small teams the choice is between Compose, a PaaS and managed Kubernetes.

How do I handle databases?

Running a database in a container is possible, but you then own backups, upgrades and recovery. A managed database from your cloud provider is often worth the extra cost, especially for production data.

Container Deployment for Small Teams: 3 Practical Paths

Small teams can run containers in production without a dedicated platform team. There are three practical paths: Docker Compose on one or a few servers, a platform as a service (PaaS) that builds and runs your Dockerfile, or managed Kubernetes. Compose is the simplest and cheapest, a PaaS takes over most operations work, and Kubernetes is worth it once you run many services or need fine-grained scaling. The container image stays the same across all three, so you can move up a level when you outgrow the current one.

Option 1: Docker Compose on a server

Docker Compose describes several containers (app, worker, database, reverse proxy) in a single YAML file and starts them together. On a server, the documented command to start all services in the background is:

docker compose up -d

Source: Docker documentation, docker compose up.

Good for: one application or a handful of small ones, predictable load, a team that is comfortable with Linux.

You take care of: server updates, firewall, TLS certificates (for example through a reverse proxy), backups, monitoring and deployments. A simple CI job that builds the image, pushes it to a registry and runs the deployment on the server covers the last point.

Limits: everything runs on one machine. If it fails, the app is down until you restore it. Scaling means a bigger server.

A server from a European provider is enough to start; see the VPS comparison for developers.

Option 2: A PaaS with a Dockerfile

Most platforms as a service accept a Dockerfile or detect your language automatically. You connect a Git repository, and the platform builds the image, deploys it, provides HTTPS and restarts crashed processes. Rollbacks are usually one click.

There are two flavours:

Hosted PaaS such as Railway, Render, Fly.io, or European options like Clever Cloud, Scalingo and Koyeb. No servers to manage at all. Our Heroku alternatives comparison covers them.
Self-hosted PaaS such as Coolify, Dokku or CapRover on your own server. You keep server costs low and data on infrastructure you choose, but you remain responsible for the server itself. See self-hosted PaaS.

Good for: teams that want to focus on code, several apps or environments (staging, preview deployments), and predictable workflows.

Limits: less control over networking and infrastructure details, and on hosted platforms costs grow with usage.

Option 3: Managed Kubernetes

Kubernetes runs containers across many machines, restarts and reschedules them, scales them and routes traffic. With a managed service the provider runs the control plane. You describe your workloads in manifests and apply them, for example with the documented command:

kubectl apply -f deployment.yaml

Source: kubernetes.io, Deployments.

Good for: many services, teams that need uniform deployments across environments, workloads with strong scaling requirements, or organisations that want one platform across providers.

You take care of: manifests or Helm charts, ingress, certificates, secrets, monitoring and upgrades of your workloads, plus the knowledge to debug a cluster. Plan for real learning time.

The European options are compared in managed Kubernetes in Europe.

Decision table

Question	Compose	PaaS	Managed Kubernetes
Number of services	few	few to many	many
Operations effort	medium	low	high
High availability across servers	no	depends on platform	yes
Cost at small scale	lowest	low to medium	medium to high
Learning curve	low	low	steep

Good practices for every path

Build images in CI, not on your laptop, and tag them with the Git commit.
Keep secrets out of images. Use environment variables or the platform’s secret store.
Run as non-root inside the container where possible and keep base images up to date.
Log to standard output so the platform can collect logs.
Back up data volumes and databases, and test restores regularly.
Health checks let the platform restart unhealthy containers automatically.

Our recommendation

Start with the simplest option that meets your requirements today. For a single product team that is usually a PaaS, hosted or self-hosted, or Compose on a well-maintained server. Move to Kubernetes when you can name the specific problem it solves. Splitting your application into many services is a separate decision; read microservices vs. monolith before you go there.