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Containerize a monorepo by treating every deployable app or worker as its own runtime unit. Give each unit a Dockerfile whose build context is the repository root, build production images with immutable commit or release tags, and use Docker Compose to run those images with private networks, health checks, secrets, restart policies, and persistent storage. On the VPS, pull the selected tags and start a production Compose overlay; expose only a reverse proxy to the internet.
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This design lets you rebuild or redeploy one service without restarting unrelated services, while keeping shared workspace packages available during the build. It does not make a single VPS highly available: the host, its disk, and its provider remain one failure domain.
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A monorepo is a source-code organization, not a deployment unit. Your repository may contain a web application, an API, background workers, scheduled jobs, and shared libraries. Deployable components should become separate images and separate Compose services. Shared code is compiled into the image for the service that uses it; it is not mounted from the source tree in production.
Compose supplies the runtime model: a YAML file defines services, networks, volumes, environment, health checks, and dependencies, and the docker compose CLI creates and starts that model. A production stack commonly contains:
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- A reverse-proxy service that terminates HTTPS and routes public requests.
- One or more application services, such as
webandapi. - Workers or schedulers that consume private queues or call the API.
- A database with persistent storage, or a connection to an external managed database.
- Optional cache, queue, and log-collection services.
Put application services and stateful services on a private Compose network. Attach only the reverse proxy to the public-facing network. Do not publish database or cache ports on the VPS host unless an operational requirement demands it.
Organize the monorepo for independent builds
Each service needs a clear build target and a defined runtime command. A typical layout is:
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apps/
web/
api/
worker/
packages/
ui/
config/
package.json
package-lock.json
compose.yaml
compose.production.yaml
.dockerignoreThe exact directories and package manager depend on your project. The important property is that a service can be selected without losing the shared packages it imports. Keep the dependency lock file at the workspace root when the package manager resolves dependencies from that root.
Set the build context at the repository root
In Compose, use the repository root as the build context and select the service-specific Dockerfile. A context limited to apps/web cannot see packages/ui or a root lock file, which causes missing imports or non-reproducible dependency resolution.
services:
web:
build:
context: .
dockerfile: apps/web/DockerfileExclude files that do not belong in a build context
A root .dockerignore keeps source-control metadata, local dependencies, test output, and environment files out of the context. This improves build speed and prevents accidental secret inclusion.
.git
.gitignore
**/node_modules
**/.cache
**/dist
**/coverage
.env*
Dockerfile*
compose*.yamlAdjust the patterns for your toolchain. If a generated artifact is required by a build, create it in a dedicated build step rather than relying on an ignored local copy.
Use a multi-stage Dockerfile for every deployable service
A multi-stage Dockerfile separates dependency installation and compilation from the final runtime. The runtime stage should contain only the production output and the libraries needed to execute it. This reduces attack surface and avoids shipping compilers, test fixtures, and source files unnecessarily. There is no universal image-size target; the useful result is a runtime image containing only what that service needs.
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The following example assumes a Node-style workspace. Replace the commands with the equivalent for your language and package manager.
FROM node:22-bookworm AS build
WORKDIR /repo
COPY package.json package-lock.json ./
COPY apps/web/package.json apps/web/package.json
COPY packages/ui/package.json packages/ui/package.json
RUN npm ci
COPY apps/web apps/web
COPY packages packages
RUN npm run build --workspace=apps/web
FROM node:22-bookworm-slim AS runtime
WORKDIR /app
ENV NODE_ENV=production
COPY --from=build /repo/apps/web/dist ./dist
COPY --from=build /repo/node_modules ./node_modules
COPY --from=build /repo/apps/web/package.json ./package.json
USER node
EXPOSE 3000
CMD ["node", "dist/server.js"]Copy lock files and workspace manifests before the rest of the source so Docker can reuse the dependency layer when application code changes. Verify that the runtime image does not copy development credentials or a local .env file. Run the process as a non-root user where the runtime supports it.
Tag images so every release is reversible
Build each service with an immutable tag, such as a Git commit SHA or release identifier. A mutable tag such as latest makes it difficult to prove what is running and to roll back. Record the exact tag deployed with the Compose configuration or release metadata.
Separate development Compose from production Compose
Use a base Compose file for common service definitions and a production override for deployment-specific settings. Docker’s production guidance identifies several useful changes: remove application-code volume bindings, bind different host ports, set production environment values, reduce log verbosity, add a restart policy such as restart: always, and add supporting services such as a log aggregator.
Development file
services:
web:
build:
context: .
dockerfile: apps/web/Dockerfile
volumes:
- .:/repo
ports:
- "3000:3000"
environment:
NODE_ENV: development
networks: [private]
db:
image: postgres:16
environment:
POSTGRES_DB: app
POSTGRES_USER: app
POSTGRES_PASSWORD: local-only-password
ports:
- "5432:5432"
volumes:
- db-data:/var/lib/postgresql/data
networks: [private]
volumes:
db-data:
networks:
private:Production override
services:
web:
image: registry.example.com/example/web:${APP_TAG}
build: null
volumes: []
environment:
NODE_ENV: production
restart: always
expose:
- "3000"
networks:
- private
- public
healthcheck:
test: ["CMD", "wget", "--spider", "--quiet", "http://localhost:3000/health"]
interval: 30s
timeout: 5s
retries: 3
start_period: 20s
db:
restart: always
networks: [private]
healthcheck:
test: ["CMD-SHELL", "pg_isready -U app -d app"]
interval: 10s
timeout: 5s
retries: 5
proxy:
image: caddy:2
restart: always
ports:
- "80:80"
- "443:443"
volumes:
- ./Caddyfile:/etc/caddy/Caddyfile:ro
- caddy-data:/data
- caddy-config:/config
depends_on:
web:
condition: service_healthy
networks:
- public
- private
volumes:
caddy-data:
caddy-config:
networks:
public:
private:The example uses a Caddy reverse proxy, but Nginx, Traefik, or a managed edge proxy can fill the same role. Keep your database on the private network and omit a host ports mapping in production. Use expose or the internal network for service-to-service traffic.
Supply secrets without committing them
Keep production secrets in the VPS environment, a protected environment file, or a secrets facility. Do not commit passwords, API keys, signing keys, or database URLs to the monorepo. Restrict the deployment user and the permissions on the directory containing the production environment file. If your platform supports mounted secrets, prefer them for credentials that should not appear in ordinary environment inspection.
Build and publish images in CI
A repeatable flow is to test the affected workspaces, build images in CI, push immutable tags to a registry, and let the VPS pull the selected tag. GitHub Actions can run linting and tests; its service containers can provide databases, caches, and other dependencies for workflow jobs. Workflows that use container or service containers require a Linux runner, and a workflow job running directly on the host needs explicit port mappings for those services.
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- Determine which workspaces changed and run their lint, unit, integration, and build checks.
- Authenticate the CI job to your container registry using a short-lived or tightly scoped token.
- Build each affected Dockerfile with the repository root as context.
- Tag every image with the commit SHA; optionally add a human-readable release tag that points to the same digest.
- Push the images and record their digests as release metadata.
- Require review for database migrations and production configuration changes.
A registry-based deployment can use GitHub Actions with the GitHub Container Registry, but another OCI-compatible registry works as long as the VPS can authenticate and pull from it. Never make the production host depend on an uncommitted working tree or an unreviewed local build.
Prepare the VPS safely
Install Docker Engine and the Compose plugin on a supported Linux distribution. Package names and installation commands vary by distribution, so follow the vendor’s current instructions for that operating system.
- Create a dedicated deployment account with only the permissions needed to run the release process. Disable direct administrative login where your provider permits it and use SSH keys rather than passwords.
- Configure the firewall to allow SSH from the administration sources you need and allow web traffic on ports 80 and 443. Keep database, cache, and application ports closed to the public internet.
- Create a controlled deployment directory, such as
/srv/myapp, owned by the deployment account. Store the Compose files, reverse-proxy configuration, and protected production environment file there. - Point DNS records at the VPS address. Confirm that the records resolve before requesting certificates through the reverse proxy.
- Install log rotation and basic host monitoring. Keep enough free disk space for the current images, the previous release, database volume growth, and Docker’s build cache.
A single VPS is a single failure domain. A provider outage, disk failure, kernel maintenance, or a mistaken upgrade can interrupt every service on that host. Use a separate database host or managed database when the application cannot tolerate that risk.
Deploy a release with Compose
After CI has published the selected image tags, connect to the VPS and run the release in a controlled directory.
cd /srv/myapp
docker login <registry>
docker compose pull
docker compose -f compose.yaml -f compose.production.yaml up -dThe two files are merged in order, so values in compose.production.yaml override the base file. Confirm which configuration Docker will use before starting it:
docker compose -f compose.yaml -f compose.production.yaml configAfter startup, check service state and the health endpoints:
docker compose ps
docker compose logs --tail=200 proxy web api workerReplace the service list with the names in your project. Do not declare success merely because containers are running: a process can be alive while unable to reach its database or serve requests. Verify the reverse proxy can obtain or renew certificates, make a real HTTP request through the public hostname, and inspect application and database logs.
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Keep the previous release for rollback
Retain the previous immutable tag until the new release has passed its verification window. A rollback changes the image tag in the production environment or Compose configuration and repeats the pull-and-up sequence. Rollback is safest when database changes remain backward-compatible with both the old and new application versions.
Run migrations as an explicit release step
When an application requires a schema migration, run it as a reviewed, observable step rather than hiding it in a container start command. The correct command is framework-specific. Confirm that the migration completed, then start or update application services. For risky changes, use an expand-and-contract approach so old and new images can temporarily coexist.
Redeploy only one service
Compose can rebuild and recreate a selected service without recreating its dependencies. For a locally built image, Docker’s targeted pattern is:
docker compose build web
docker compose up --no-deps -d web--no-deps prevents Compose from recreating dependency services. Use the service name exactly as it appears in the Compose file. This is appropriate when the change is isolated and the existing database, cache, and network contracts remain valid.
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docker compose pull web
docker compose up --no-deps -d webPulling only web avoids downloading unrelated images. If the service’s configuration, network membership, volumes, or dependency conditions changed, review the merged configuration and update those definitions before recreating it.
When a one-service update is unsafe
- A database migration changes a schema that the old service still reads.
- The new image requires an environment variable absent from the VPS.
- The service contract changed and workers or clients still send the old request format.
- The service owns a shared volume whose contents are not compatible with the new version.
- The health check passes but a required downstream dependency is unavailable.
In those cases, deploy a coordinated release, migrate compatibly, or roll back to the last known-good tag.
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Persist data and plan recovery
Containers are replaceable; databases and uploaded files are not. Use a named volume for a self-hosted database or connect to an external managed database. The volume must be outside the application container lifecycle:
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volumes:
postgres-data:
services:
db:
image: postgres:16
volumes:
- postgres-data:/var/lib/postgresql/dataBack up volumes and test restoration on a separate environment. Docker’s production guidance does not define a universal backup frequency, retention period, or recovery-time target, so choose those from the data’s business impact. Document where backups are stored, who can restore them, and how to validate that the restored database is usable.
Object storage is generally preferable to a local container volume for user uploads when the application can support it. If files must remain on the VPS, include them in the backup and capacity plan. A backup that has never been restored is an assumption, not a recovery strategy.
Make the stack observable and resilient
Health checks and restart behavior
Define a health check that exercises a lightweight endpoint and reports dependency failures accurately. Use restart policies for transient crashes, but do not use restarts to conceal a deterministic configuration error. A failing health check should be visible in docker compose ps and in your monitoring.
Logs
Write structured logs to standard output and let Docker’s logging configuration or a log collector manage retention. Reduce development-level verbosity in production. Include request identifiers and service names so a request crossing the proxy, API, and worker can be traced.
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Resource controls
Set CPU and memory limits appropriate to the VPS size, then monitor actual usage. An unconstrained worker can starve the reverse proxy or database. Leave headroom for image pulls, rolling replacement, and filesystem operations; there is no responsible universal CPU or RAM number without workload, provider, region, and date.
Security updates
Rebuild base images and dependencies regularly, scan images in CI, remove unused packages, and patch the host. Keep the Docker socket inaccessible to application containers unless a narrowly reviewed automation requires it.
Choose a deployment approach by risk and operations
The right workflow depends less on monorepo size than on where you want builds, state, ingress, and release control to live.
Quick Recap
| Decision axis | Option A | Option B | What to evaluate |
|---|---|---|---|
| Build location | Build on the VPS | Build in CI | VPS builds are simple but consume host CPU, disk, and credentials; CI keeps production hosts focused on running images. |
| Image distribution | Source checkout and local build | Registry pull | Registry pulls provide immutable tags and a clear rollback point; local builds require a trusted, reproducible checkout. |
| Ingress | Caddy | Nginx, Traefik, or managed edge proxy | Compare certificate automation, routing features, operational familiarity, and where TLS is terminated. |
| State | Local named volume | Managed database or object storage | Local state is straightforward but tied to one host; managed services can improve durability and recovery options. |
| Release control | Manual pull over SSH | Automated SSH or pull-based agent | Automation improves repeatability but must protect credentials and provide an auditable rollback path. |
| Recovery | Single-host backup and restore | Multi-host redundancy | Choose according to tolerated downtime, data loss, budget, and operational capacity. |
Troubleshoot the failures that matter
| Symptom | Likely cause | Checks and fix |
|---|---|---|
| Build cannot find a shared package | The build context is an app subdirectory. | Set context: . at the repository root, copy the workspace manifests, and verify the Dockerfile paths. |
| Production container sees source changes | A development bind mount survived into the override. | Remove the source volume in compose.production.yaml; rebuild and recreate the service. |
| Proxy returns 502 | The upstream is unhealthy, listening on the wrong port, or on another network. | Inspect health status and logs, use the Compose service name and internal port, and ensure proxy and app share a network. |
| Database data disappears | The database used a container filesystem or an incorrectly mounted path. | Attach a named or external volume, inspect mounts, and restore from a tested backup if necessary. |
| New image was not deployed | The VPS still references a mutable tag or did not pull the new digest. | Use an immutable tag, run docker compose pull service, inspect the image ID, and recreate the service. |
| Service constantly restarts | Invalid environment, failed migration, missing dependency, or an overly strict health check. | Read logs before changing the restart policy; validate configuration and dependency reachability, then correct the release. |
| Host disk fills | Old images, unbounded logs, database growth, or build cache. | Set retention, rotate logs, remove unused images deliberately, monitor volume growth, and preserve the tags needed for rollback. |
Production checklist
- Every deployable app and worker has an independently buildable Dockerfile.
- Build contexts include shared workspace packages and lock files.
- Images use multi-stage builds and run without development source mounts.
- CI tests affected workspaces and publishes immutable image tags.
- The VPS pulls a selected tag through a controlled deployment account.
- Only the reverse proxy is publicly exposed; internal services use private networks.
- Secrets are outside version control and protected on the host.
- Health checks, restart policies, structured logs, and resource limits are configured.
- Database and upload data use persistent or managed storage.
- Backups have a documented retention policy and a tested restore procedure.
- The previous image remains available for rollback.
- Migration steps are reviewed and run explicitly.
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