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Containerize a monorepo by treating every deployable app or worker as its own runtime unit. Give each unit a multi-stage Dockerfile whose build context is the repository root, define the services and their private networks, health checks, secrets, and volumes in Docker Compose, then deploy immutable image tags to a VPS behind a reverse proxy. A production override removes development mounts, supplies production settings, and adds restart and logging policies.
The safest operating pattern is to build and test in CI, push images to a registry, pull a chosen commit tag on the VPS, and recreate only the service that changed. Keep state in persistent volumes or managed services, and retain the previous image tag so a failed release can be reversed.
What a Dockerized monorepo deployment looks like
A monorepo is one source repository containing multiple workspaces or applications. Typical examples are a web frontend, an API, a background worker, and shared packages. Containerization should not turn that repository into one indivisible container. Instead, map each independently deployable process to a Compose service and image.
Docker describes Compose as a YAML model for defining an application’s services and networks and managing them with the docker compose CLI. That model fits a monorepo because the repository can remain unified while the runtime remains separated:
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- Build units: each app or worker has a Dockerfile and a clearly defined production command.
- Runtime units: Compose starts, networks, checks, and restarts those containers independently.
- Shared code: workspace packages are copied into the build context only when a service needs them.
- State: databases and uploaded files live in named volumes or external managed services, not in disposable image layers.
Compose can also be extended with Docker Buildx Bake for declarative, coordinated builds. That is useful when several services share dependency installation or need consistent build metadata, but ordinary Compose builds are sufficient for a small VPS.
Choose the service boundaries before writing Dockerfiles
Start with the processes that must run in production, not with the folders in the repository. A package containing shared UI components is not a service; a worker that consumes a queue is. A service boundary should answer three questions: what command starts it, what files it needs at runtime, and what network or persistent data it requires.
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repo/
apps/
web/
package.json
src/
api/
package.json
src/
worker/
package.json
src/
packages/
config/
database/
ui/
package.json
lockfile
compose.yaml
compose.production.yaml
The exact directories and package manager are repository decisions. The important property is that a service build can resolve the shared packages it imports. If apps/api imports packages/database, building with apps/api as the context will usually hide the package it needs. Use the repository root as the context and restrict what enters it with a root .dockerignore.
Keep dependency installation repeatable
Commit the lock file and make the Docker build use the lock-file-enforcing install mode of your package manager. Copy workspace manifests and the lock file before application source so Docker can reuse the dependency layer when only source files change. Never rely on an uncommitted local dependency tree or a developer’s global package installation.
Build each service with a multi-stage Dockerfile
A multi-stage Dockerfile separates compilation from execution. The build stage contains compilers, package-manager caches, and development dependencies. The runtime stage receives only the production output and runtime dependencies. This reduces attack surface and avoids shipping source files and build tools.
What every Dockerfile should establish
- A base image and operating-system assumptions that are suitable for your language runtime.
- A working directory and a non-root runtime user where the application supports it.
- Deterministic dependency installation from the lock file.
- A build command that targets one app while allowing imports from required workspace packages.
- A production-only dependency set and the compiled output needed by the start command.
- An explicit
CMDor entrypoint that does not depend on a development watcher.
Illustrative multi-stage pattern
# apps/api/Dockerfile
FROM runtime-base AS build
WORKDIR /repo
COPY package.json lockfile ./
COPY apps/api/package.json apps/api/package.json
COPY packages packages
RUN install-command --frozen-lockfile
COPY apps/api apps/api
RUN build-command --workspace apps/api
FROM runtime-base AS production
WORKDIR /app
ENV NODE_ENV=production
COPY --from=build /repo/apps/api/dist ./dist
COPY --from=build /repo/node_modules ./node_modules
COPY --from=build /repo/apps/api/package.json ./package.json
USER app
CMD ["runtime", "dist/server.js"]
runtime-base, install-command, and build-command are deliberately generic: the cited guidance does not prescribe a language, package manager, or universal base image. Replace them with the commands your repository already uses. If your package manager creates a pruned deployment directory, copy that directory instead of the full dependency tree. If native modules are compiled, build and run with compatible system libraries.
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One Dockerfile per deployable app or a parameterized file?
Separate Dockerfiles make ownership and debugging obvious. A parameterized Dockerfile can reduce duplication when all apps share the same toolchain, but it must still produce an independently tagged image and an independently testable start command. Do not combine unrelated long-running processes into one container merely to avoid maintaining two files; Compose is the process supervisor at the application level.
Use a strict build context
A root .dockerignore should normally exclude Git metadata, local dependency directories, test artifacts, editor files, logs, and environment files containing secrets. Do not exclude a shared package that a build needs. The build context determines what Docker can copy, so an over-aggressive ignore rule can create a build that succeeds locally but fails in CI.
Model development and production separately with Compose
Keep a convenient development file and layer production changes on top. The production file should describe operational differences, not duplicate the entire application definition. Docker’s production guidance lists common changes: remove application-code volume bindings, bind different host ports, set production environment variables, reduce logging verbosity, add a restart policy such as restart: always, and add operational services when needed.
Development Compose file
services:
web:
build:
context: .
dockerfile: apps/web/Dockerfile
command: dev-command
volumes:
- .:/repo
ports:
- "3000:3000"
depends_on:
api:
condition: service_healthy
api:
build:
context: .
dockerfile: apps/api/Dockerfile
command: dev-api-command
volumes:
- .:/repo
expose:
- "4000"
db:
image: postgres:version
volumes:
- db-data:/var/lib/postgresql/data
volumes:
db-data:
Use a concrete database image version selected and maintained by your team; the architecture does not establish a universal version. Development bind mounts are useful for hot reload but are inappropriate on a production VPS because they expose source code and make the running container depend on the host checkout.
Production override
services:
web:
image: ghcr.io/your-org/monorepo-web:${IMAGE_TAG}
build: null
command: production-web-command
volumes: []
ports: []
environment:
NODE_ENV: production
restart: always
depends_on:
api:
condition: service_healthy
api:
image: ghcr.io/your-org/monorepo-api:${IMAGE_TAG}
build: null
command: production-api-command
volumes: []
restart: always
db:
restart: always
proxy:
image: reverse-proxy-image
ports:
- "80:80"
- "443:443"
The image names and commands above are examples to adapt. In production, publish only the reverse proxy’s HTTP and HTTPS ports. Keep the database, API, and worker on private Compose networks. A service can be reachable by its Compose service name without exposing a host port.
Merge and inspect the effective configuration
Start the merged production stack with:
docker compose -f compose.yaml -f compose.production.yaml up -dBefore applying it, render the merged file and inspect image tags, ports, mounts, environment interpolation, and network membership. This catches an override that accidentally leaves a source bind mount or publishes a database port. Keep secrets in the VPS environment or a dedicated secrets mechanism rather than committing them to either Compose file.
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Build and distribute immutable images
For a repeatable release, build images in CI, test them, push them to a registry, and deploy a tag that identifies the commit or release. An immutable tag lets you answer exactly which source revision is running and gives you a known target for rollback. Avoid a mutable latest tag as the only production reference.
Recommended CI sequence
- Detect changed workspaces and run linting and tests for the affected apps and their shared packages.
- Build each deployable image with the repository root as context.
- Run container-level checks, including startup and health-check behavior.
- Tag each image with the commit SHA or release identifier and push it to the registry.
- Publish the image metadata needed by the deployment, such as the tag and digest.
GitHub Actions can run these jobs, and GitHub service containers can supply databases, caches, and other dependencies for workflow tests. Workflows that use container or service containers require a Linux runner; a direct host job needs explicit port mappings to reach a service container. Those CI constraints do not change how the images run on the VPS, but testing the same Compose assumptions reduces release surprises.
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| Decision | Build on VPS | Build in CI and pull |
|---|---|---|
| Source exposure | Repository and build secrets reside on the server. | Server needs images and deployment configuration, not a full source checkout. |
| Server load | Compilation competes with production services for CPU, memory, disk, and network. | Build resources are isolated from the VPS. |
| Repeatability | Depends on the server’s toolchain and cache state. | Uses a controlled runner and a recorded image tag or digest. |
| Rollback | Requires rebuilding an older revision unless old images are retained. | Pull the previous immutable image tag. |
| Operational complexity | Fewer registry steps, but more credentials and build tooling on the host. | Requires registry authentication and CI configuration. |
For most production monorepos, CI builds plus registry pulls provide the clearer audit trail. A VPS build can be reasonable for a private, low-change project, but keep the same lock-file discipline and retain a previous known-good image.
Prepare the VPS safely
A single VPS is a single failure domain. A provider outage, disk failure, kernel maintenance, or an operator mistake can affect every service on it. Preparation should therefore cover access, network exposure, storage, and recovery before the first release.
Host setup checklist
- Install Docker Engine and the Compose plugin on a supported Linux distribution.
- Create a restricted deployment user; avoid running routine deployment commands as an unrestricted personal account.
- Use SSH keys and apply the provider’s operating-system security updates.
- Configure the firewall to allow SSH and the web ports required by the reverse proxy, while blocking database and internal service ports from the public internet.
- Create a controlled directory for production Compose files and the environment file, with permissions that limit who can read secrets.
- Point DNS records at the VPS and verify that the reverse proxy will answer for the intended hostnames.
- Authenticate to the image registry from the deployment account, using the narrowest token permissions available.
Reverse proxy and TLS
Put Caddy, Nginx, Traefik, or a managed edge proxy at the public boundary. The proxy terminates HTTPS, routes hostnames or paths to private Compose services, and is the only component that needs public web ports. Choose one proxy and configure certificate storage persistently; do not expose each application container directly just because it has a listening port.
Secrets and configuration
Keep database passwords, signing keys, registry credentials, and API tokens outside Git. Supply non-secret configuration through the production environment and use the platform’s secrets mechanism for sensitive values. Review the rendered Compose configuration carefully: interpolation can expose an empty variable or a secret in logs if a command prints its environment.
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Deploy the stack on the VPS
Deploy from a directory containing the production Compose files and the environment values that select the release tag. The following sequence assumes CI has already pushed the images.
- Connect to the VPS as the restricted deployment user and change to the deployment directory.
- Authenticate to the registry:
docker login <registry>. - Set
IMAGE_TAGto the approved commit or release tag in the environment file. Keep the prior tag recorded separately for rollback. - Pull the selected images:
docker compose pull. - Apply both files:
docker compose -f compose.yaml -f compose.production.yaml up -d. - Check service state with
docker compose psand inspect startup output withdocker compose logs --tail=200. - Confirm every health check is passing, the proxy obtains or renews certificates, and an external request reaches the expected service.
Do not call a deployment zero-downtime unless the design actually keeps an available instance while the new one starts and health checks gate traffic. A single-container recreation normally creates a brief interruption, even when the command itself returns quickly.
Health checks that are useful
- The web service should expose a lightweight endpoint that verifies the process is ready to serve requests.
- An API check should fail when required configuration is missing, but avoid making a temporary third-party outage prevent the process from starting unless that dependency is essential.
- A worker check should demonstrate that the worker loop is alive; a process that is running but permanently blocked is not healthy.
- Database readiness should be checked separately from application health so startup ordering does not masquerade as data loss.
Compose health checks help express readiness, but they are not a backup strategy, a load balancer, or a guarantee of zero downtime.
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When only the web image changes, do not recreate the database, proxy, or unrelated workers. Docker’s documented targeted pattern is:
docker compose build web
docker compose up --no-deps -d webThe first command rebuilds the web image; the second recreates only that service and skips dependency recreation. Use this form when the VPS builds from a local checkout.
Registry-based targeted release
- Build and push the new web image in CI under a new immutable tag.
- Update the production environment so the web service references that tag. If all services share one tag variable, use separate variables when independent release cadence matters.
- Pull the new image:
docker compose pull web. - Recreate only the web service with
docker compose up --no-deps -d web. - Wait for the web health check, then test through the reverse proxy and inspect logs.
If the service needs a schema change, run the reviewed database migration as an explicit release step. There is no universal migration command: use the migration tool and compatibility sequence defined by that application. Design migrations so the old and new application versions can coexist during a rolling or staged update.
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Persistence, backups, and resource controls
Database storage
Attach a named volume to a database or use a managed database. A PostgreSQL service with a mounted volume keeps data across container replacement, but a volume on the same VPS is still vulnerable to disk loss and host failure. Managed PostgreSQL can be swapped in through configuration when recovery requirements exceed a single host.
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Backups and restoration
Back up database data and important volumes to storage that is independent of the VPS. Docker’s production guidance does not establish a universal backup frequency, retention period, or recovery-time target; choose those values from the application’s acceptable data loss and downtime. Test restoration, not just backup creation, and document where the restored service obtains its credentials and configuration.
Logs, limits, and monitoring
- Emit structured logs and set a retention policy so a busy service cannot fill the VPS disk.
- Use restart policies for expected process failures, while monitoring repeated restarts instead of treating them as a fix.
- Set memory and CPU limits appropriate to the VPS size; there is no universal CPU or RAM number for every monorepo.
- Monitor disk space, memory pressure, container health, certificate expiry, and database connectivity.
- Keep operational logs separate from application secrets and redact tokens before exporting logs.
Compare the important deployment choices
| Axis | Option A | Option B | How to decide |
|---|---|---|---|
| Build location | Build on the VPS | Build in CI | Prefer CI when host capacity, repeatability, or source isolation matters. |
| Image distribution | Source checkout and local build | Registry pull | Use registry pulls for immutable tags and simpler rollback. |
| Ingress | Self-hosted Caddy, Nginx, or Traefik | Managed edge proxy | Choose based on certificate automation, control, and provider dependency. |
| State | Local named volume | Managed database or object storage | Use managed state when host failure or maintenance cannot be tolerated. |
| Release trigger | Manual pull and SSH | Automated SSH or pull-based agent | Start manually; automate only after approvals, secrets, and rollback are defined. |
| Recovery | Single-host backup and restore | Multi-host redundancy | Match the design to the required recovery time and failure tolerance. |
Troubleshoot common failures
The image build cannot find a shared package
Check the build context and ignore rules first. The context should normally be the repository root, and the Dockerfile must copy the workspace manifests and shared package directories required by the selected app. Rebuild with plain progress output so a missing copy step is visible.
Compose starts the API before the database is ready
A container start event is not the same as database readiness. Add a database health check and make dependent services wait for the healthy condition where supported. The application should still retry transient connection failures rather than assuming one successful connection attempt.
The production container still shows source files or live reloads
Inspect the merged Compose configuration. A development bind mount may still be inherited from the base file, or the production override may not have replaced the command. Remove source mounts, select the production command, and rebuild the image if the runtime stage copied development artifacts.
The proxy returns a gateway error
Verify that the proxy uses the Compose service name and the container’s internal listening port, not a host-published port that was removed in production. Check the target service health, inspect its logs, and confirm both services share a private network.
A new release fails immediately
Stop treating the failed tag as the only option. Record the container logs and health-check result, set the environment back to the previous known-good immutable tag, pull it, and recreate the affected service. Investigate configuration, migrations, and image architecture before attempting the release again.
Rollback and ongoing operating practice
A rollback is safest when it changes only the failed service and uses an image that has already run successfully. Keep previous tags available in the registry and do not prune them until the retention period required by your recovery plan has passed. If a migration has changed the database schema, an application rollback may require a backward-compatible migration or a separately reviewed data restoration; reverting a container alone cannot undo incompatible data changes.
Review the stack after each release: confirm the running image tag, health status, logs, volume mounts, firewall exposure, and backup freshness. As the monorepo grows, split Compose files or deployment projects when services need different release permissions, maintenance windows, or failure domains. A single VPS remains a practical starting point, but move state or replicas to separate infrastructure when one-host recovery no longer meets the application’s requirements.
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Quick Recap
Production checklist
- Every deployable app and worker has an independently buildable Dockerfile.
- The root build context and lock file produce repeatable dependency installation.
- Runtime images contain production output and dependencies, not source bind mounts or development watchers.
- Compose defines private networks, health checks, restart behavior, secrets handling, and persistent storage.
- Only the reverse proxy is publicly exposed.
- CI tests affected workspaces, builds images, and publishes immutable commit or release tags.
- The VPS can authenticate to the registry and deploy with the merged production files.
- Logs, resource usage, disk space, certificates, and health checks are monitored.
- Database and volume backups are independent of the host, and restoration has been tested.
- The previous image tag and a documented rollback procedure are available before release.
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