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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsContainerize each deployable part of the monorepo as its own image, build from the repository root so shared packages are available, and run the images with a production Docker Compose overlay. Put only the reverse proxy on the public network, keep databases and workers private, use immutable image tags, and update one service with a targeted Compose command instead of restarting the entire stack.
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What a production monorepo container setup looks like
A monorepo is one source repository containing multiple applications and shared packages. It becomes a reliable VPS deployment when you separate the repository’s deployable runtime units from the repository itself:
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- Each app or worker that runs independently has its own Dockerfile and image.
- Each Dockerfile can read the shared packages it needs because its build context is the repository root.
- Docker Compose describes the services, private networks, ports, health checks, restart policies, secrets, and volumes that make up one release.
- A reverse proxy is the only service exposed directly to the internet; databases and internal services stay on private Compose networks.
- Images are tagged with a commit SHA or release identifier so a known version can be restored.
This arrangement lets you change the web application without rebuilding a worker, while still allowing all services to be released together when a shared package or database migration requires it.
Choose the deployment boundary before writing Dockerfiles
Do not create one container per directory automatically. Create one image for every process that needs an independent lifecycle, scaling decision, port, or health check.
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Typical boundaries
- Web: serves HTTP requests or a frontend runtime.
- API: handles application requests and may have a different dependency set from the web server.
- Worker: consumes a queue or performs scheduled jobs without exposing a public port.
- Database: usually a separate managed service or a stateful Compose service with a persistent volume.
- Reverse proxy: terminates TLS and routes public hostnames to private application services.
A shared library is not normally a runtime service. Build it into the images that consume it. Split it into a separate service only when it is independently runnable.
Example repository layout
repo/
├── apps/
│ ├── web/
│ │ ├── Dockerfile
│ │ └── package.json
│ ├── api/
│ │ ├── Dockerfile
│ │ └── package.json
│ └── worker/
│ ├── Dockerfile
│ └── package.json
├── packages/
│ ├── config/
│ └── ui/
├── compose.yaml
├── compose.production.yaml
├── package.json
└── lockfile
The names are illustrative. Keep the same principle if your workspace uses another language or package manager: the build must be able to resolve workspace dependencies, and the final image must contain only what the selected process needs at runtime.
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Build each service with a multi-stage Dockerfile
A multi-stage build uses one stage to install dependencies and compile the selected app, then copies the production output and runtime dependencies into a smaller final stage. It keeps compilers, package caches, tests, and source files out of the runtime image.
Illustrative workspace Dockerfile
The following example assumes a JavaScript workspace and is intentionally a pattern rather than a universal requirement. Replace the base image, package-manager commands, build output, and start command with the equivalents for your stack.
FROM node:22-alpine AS build
WORKDIR /repo
# Copy lockfiles and workspace manifests first for better layer reuse.
COPY package.json package-lock.json ./
COPY apps/web/package.json apps/web/package.json
COPY packages/config/package.json packages/config/package.json
COPY packages/ui/package.json packages/ui/package.json
RUN npm ci
# Copy source only after dependency installation.
COPY . .
RUN npm run build --workspace=apps/web
FROM node:22-alpine AS runtime
WORKDIR /app
ENV NODE_ENV=production
# Install only production dependencies in the runtime stage.
COPY package.json package-lock.json ./
COPY apps/web/package.json apps/web/package.json
COPY packages/config/package.json packages/config/package.json
COPY packages/ui/package.json packages/ui/package.json
RUN npm ci --omit=dev
COPY --from=build /repo/apps/web/dist ./apps/web/dist
COPY --from=build /repo/packages ./packages
USER node
EXPOSE 3000
CMD ["node", "apps/web/dist/server.js"]
For a worker, keep the same dependency and build stages but use the worker’s build command and entry point. For a statically generated frontend, the runtime stage may contain only generated files and a small web server. Do not copy an entire source tree merely because it is convenient; copy the exact production artifacts your process reads.
Build-context rules that prevent monorepo failures
- Run the build with
.at the repository root as the context when shared packages live outside the app directory. - Set the Dockerfile path explicitly, for example
docker build -f apps/web/Dockerfile -t example/web:TAG .. - Keep the lockfile in the context and use the package manager’s lockfile mode for reproducible installs.
- Add a root
.dockerignorethat excludes.git, local dependency directories, test output, editor files, and environment files containing secrets. - Do not put runtime secrets in build arguments or image layers; image history can expose them.
Build arguments are appropriate for non-secret compile-time switches. Runtime configuration belongs in Compose environment variables or a secrets mechanism on the VPS.
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Define a development Compose file and a production overlay
Compose is the declarative model for defining services and networks and managing them with the docker compose CLI. A useful pattern is to keep fast development defaults in compose.yaml and add production changes in compose.production.yaml.
Base Compose file
services:
web:
build:
context: .
dockerfile: apps/web/Dockerfile
environment:
API_URL: http://api:4000
depends_on:
api:
condition: service_healthy
networks: [private]
api:
build:
context: .
dockerfile: apps/api/Dockerfile
environment:
DATABASE_HOST: db
depends_on:
db:
condition: service_healthy
networks: [private]
worker:
build:
context: .
dockerfile: apps/worker/Dockerfile
environment:
DATABASE_HOST: db
depends_on:
db:
condition: service_healthy
networks: [private]
db:
image: postgres:16
environment:
POSTGRES_DB: app
POSTGRES_USER: app
POSTGRES_PASSWORD: change-me-in-production
volumes:
- db-data:/var/lib/postgresql/data
healthcheck:
test: ["CMD-SHELL", "pg_isready -U app -d app"]
interval: 10s
timeout: 5s
retries: 5
networks: [private]
networks:
private:
driver: bridge
volumes:
db-data:
The development file can use source mounts, local builds, debug ports, and relaxed settings. Treat the database password above as a placeholder for local development only; production credentials must come from the VPS environment or a secrets facility.
Production overlay
services:
web:
image: registry.example.com/team/web:${IMAGE_TAG}
build: null
environment:
NODE_ENV: production
restart: always
expose:
- "3000"
healthcheck:
test: ["CMD-SHELL", "wget -qO- http://localhost:3000/health || exit 1"]
interval: 15s
timeout: 5s
retries: 3
api:
image: registry.example.com/team/api:${IMAGE_TAG}
build: null
restart: always
expose:
- "4000"
worker:
image: registry.example.com/team/worker:${IMAGE_TAG}
build: null
restart: always
db:
restart: always
env_file:
- .env.production
proxy:
image: caddy:2
ports:
- "80:80"
- "443:443"
volumes:
- ./Caddyfile:/etc/caddy/Caddyfile:ro
- caddy-data:/data
- caddy-config:/config
depends_on:
web:
condition: service_healthy
networks: [private, public]
networks:
public:
driver: bridge
volumes:
caddy-data:
caddy-config:
The exact proxy image and configuration are design choices. The important boundary is that only the proxy publishes host ports. Use expose or private-network service discovery for application containers, and do not publish database ports to the VPS interface unless an operational need has been assessed and protected.
Apply the merged configuration
docker compose -f compose.yaml -f compose.production.yaml config
docker compose -f compose.yaml -f compose.production.yaml up -d
Run config first to inspect the merged result, including interpolated variables, before starting anything. In production, remove source-code volume bindings, set production environment values, reduce development logging, and keep restart policies explicit. Never mount the repository into a production container as a substitute for building an image.
Tag and distribute images for repeatable releases
Use an immutable tag such as a commit SHA or release tag for every image. A floating tag such as latest makes it difficult to identify what is running and weakens rollback.
Recommended CI sequence
- Determine which workspaces are affected by the change.
- Run linting, unit tests, and integration tests for those workspaces and any dependents.
- Build the web, API, and worker images from the repository root, using their respective Dockerfiles.
- Tag every image with the same release identifier, or with service-specific tags that all contain the same commit SHA.
- Push the images to a container registry.
- Record the image tags as release metadata so the VPS can be returned to that exact version.
A GitHub Actions workflow can use service containers for a database, cache, or other dependency during tests. Workflows that use container or service containers require a Linux runner. A job that runs directly on the host needs explicit port mappings when it connects to a service container. Keep CI credentials scoped to the registry and repository, and do not copy production secrets into test logs.
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Pull-based VPS release
After CI has pushed the images, place the production Compose files and an environment file in a controlled directory on the VPS. Set IMAGE_TAG to the release you intend to run, authenticate to the registry, and pull only those images.
docker login registry.example.com
export IMAGE_TAG=2026-04-04-a1b2c3d
docker compose -f compose.yaml -f compose.production.yaml pull
docker compose -f compose.yaml -f compose.production.yaml up -d
If your registry or deployment process does not permit shell exports, put the variable in the protected environment file consumed by Compose. Restrict that file’s permissions and exclude it from version control.
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Prepare the VPS safely
- Install Docker Engine and the Compose plugin from the distribution-supported instructions for the VPS operating system.
- Create a deployment user with only the access required to run the release process. Use SSH keys rather than shared passwords and avoid routine work as root.
- Configure the firewall to permit SSH and the web ports needed by the reverse proxy. Do not open database or internal application ports publicly.
- Create a deployment directory owned by the deployment user. Store the Compose files, proxy configuration, and protected production environment file there.
- Point DNS records at the VPS and configure the reverse proxy for the required hostnames and TLS certificates.
- Authenticate to the image registry, set the intended immutable tag, pull the images, and start the merged Compose project.
- Confirm health checks, inspect logs, and test an external request before considering the release complete.
A single VPS is one failure domain. A provider outage, disk failure, kernel maintenance, or host upgrade can affect every service at once. If the recovery requirement is higher than one host can provide, move the database to managed storage or separate critical components across hosts rather than treating Compose as high availability.
Handle persistence, secrets, and backups
Database state
Containers are replaceable; database data is not. Use a named volume for a database that must run on the VPS, or use a managed database configured through environment variables. The volume must be included in your backup plan, and restoration must be tested on a separate instance or temporary location.
No universal backup frequency, retention period, or recovery-time target fits every application. Choose those values from the amount of data the business can lose and the time it can tolerate without service, then verify that the chosen schedule and storage actually meet them.
Secrets
- Keep database passwords, signing keys, registry tokens, and API credentials out of Git and Dockerfiles.
- Supply them through a protected VPS environment file or a secrets mechanism supported by your deployment design.
- Use separate credentials for development, CI, and production.
- Check logs and image history for accidental secret exposure.
Operational controls
- Use structured logs and configure a retention policy so logs do not fill the VPS disk.
- Add health checks that test the process a proxy or orchestrator actually needs, not merely whether a port is open.
- Set CPU and memory limits appropriate to the VPS capacity, and monitor for out-of-memory kills and disk pressure.
- Use restart policies for expected process failures, but investigate a crash loop instead of allowing endless restarts to hide an application defect.
- Monitor host resources, container health, certificate renewal, volume usage, and backup success.
Deploy one service without restarting the whole stack
For a locally built production image, Docker’s targeted pattern is:
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docker compose build web
docker compose up --no-deps -d web
The first command rebuilds the web image. The second recreates only web and does not recreate its dependencies. Use the merged production files when your project requires them:
docker compose -f compose.yaml -f compose.production.yaml build web
docker compose -f compose.yaml -f compose.production.yaml up --no-deps -d web
For a registry-based release, build and push the new image in CI, change IMAGE_TAG to the new immutable value, pull the image, and recreate only the selected service:
docker compose -f compose.yaml -f compose.production.yaml pull web
docker compose -f compose.yaml -f compose.production.yaml up --no-deps -d web
Run database migrations as an explicit, reviewed release step when the application needs them. There is no universal migration command: use the migration tool defined by the application, check whether the change is backward compatible, and decide whether the migration must run before or after the new container starts.
Do not call a targeted restart zero-downtime deployment automatically. Whether requests remain available depends on the proxy, process startup time, health checks, connection draining, and whether more than one healthy application instance exists. A single replacement container can still create a short interruption.
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Post-deployment checks
- Run
docker compose pswith the production files and confirm every expected service is healthy or intentionally running without a health check. - Inspect recent logs for startup errors, failed migrations, authentication failures, and repeated restarts.
- Request the public hostname through the reverse proxy and exercise a representative authenticated and unauthenticated path.
- Confirm the worker can reach its queue or database and that the database volume is mounted at the expected path.
- Check that the running image digest or tag matches the release record.
Rollback sequence
- Identify the last known-good immutable image tag.
- Set
IMAGE_TAGto that tag in the protected production environment. - Pull the old images and apply the production Compose files.
- Re-run health checks and the smoke tests used for the failed release.
- Investigate and correct the failed release before attempting another forward deployment.
Application code rollback does not automatically undo a database schema change. Design migrations so the previous application can continue to operate when possible, or document a separately reviewed data-recovery procedure.
Decide where each deployment responsibility belongs
| Decision | Option A | Option B | Operational consequence |
|---|---|---|---|
| Build location | Build on the VPS | Build in CI | VPS builds are simple but consume production CPU and depend on source checkout and build tools; CI builds keep production hosts smaller and make releases reproducible when the image is stored in a registry. |
| Image distribution | Pull an immutable image from a registry | Check out source and build locally | Registry pulls make the running artifact explicit and speed redeployments; local builds reduce registry dependence but require source credentials, toolchains, and a clean build environment on the VPS. |
| Ingress | Reverse proxy on the VPS | Managed edge proxy | A local proxy centralizes routing and TLS on the host; a managed edge can absorb more edge responsibility but adds an external dependency and configuration layer. |
| State | Named volume on the VPS | Managed database or object storage | Local state is straightforward but shares the VPS failure domain; managed state can improve recovery options and is swappable through configuration. |
| Release trigger | Manual pull and Compose command | Automated SSH or pull-based agent | Manual releases are easy to audit but depend on an operator; automation improves repeatability and must be protected with narrowly scoped credentials. |
| Recovery | Single-host backup and restore | Multi-host redundancy | Single-host recovery is less complex but cannot remove host-level downtime; redundancy costs more operational effort and is justified only by the recovery requirement. |
Troubleshoot the failures that are specific to monorepos
“File not found” for a shared package
The Docker build context is probably an app subdirectory, so Docker cannot see the workspace package. Build from the repository root and point -f at the app’s Dockerfile. Check that the package is copied before the install or build command and that the root lockfile is present.
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Dependencies install but the app cannot start
Compare the build-stage output with the runtime-stage copy list. A production dependency, generated client, native library, or workspace package may have been left behind. Start a shell in the runtime image, inspect the expected paths, and add only the missing runtime artifact rather than copying the entire repository.
Compose starts the API before the database is usable
Container start order is not the same as application readiness. Add a database health check and a conditional dependency, and make the API retry its connection during startup. A health check should represent a usable dependency, not merely a running container.
The proxy returns a gateway error
Confirm that the proxy and target service share a Compose network, that the proxy uses the Compose service name and container port, and that the target health check passes. Do not use localhost inside the proxy container to reach another service; there, localhost refers to the proxy itself.
The new image is not running
Check the interpolated configuration with docker compose ... config, verify that IMAGE_TAG is set in the shell or environment file used by the command, pull the tag explicitly, and inspect the service’s image field with docker compose ps. A stale tag or an omitted production override can leave the old image in place.
The VPS runs out of disk space
Inspect image layers, stopped containers, log files, and volume usage. Remove only unreferenced artifacts after confirming that the rollback image is still available. Set log retention and monitor the database volume separately; deleting unused images must never be confused with deleting persistent data.
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- Every independently deployed app or worker has a Dockerfile.
- Each build uses the repository root context when it needs shared packages.
- Lockfiles are present and dependency installation is reproducible.
- Dockerfiles use a build stage and a minimal runtime stage where the stack supports it.
- Production images are tagged immutably and retained for rollback.
- The production Compose overlay removes source mounts and development-only settings.
- Only the reverse proxy publishes host ports.
- Internal services use private networks and explicit health checks.
- Secrets are supplied outside the repository and image layers.
- Database data is on a persistent volume or managed service, with tested backups.
- The VPS has a restricted deployment user and a firewall allowing only required traffic.
- CI tests affected workspaces, builds images, and pushes the selected tags.
- Deployment logs, service health, resource usage, and certificate status are monitored.
- A documented rollback tag and procedure exist before the first production release.
- Migration compatibility and recovery behavior are reviewed for every schema-changing release.
Final deployment sequence
Build each runtime unit from the monorepo root, test and tag the images in CI, push those immutable tags to a registry, and configure the VPS to pull them through a production Compose overlay. Keep ingress public and application dependencies private, persist database state independently from containers, verify health after every change, and use up --no-deps -d SERVICE when a single service can be released safely. This gives a small VPS the repeatable release and rollback behavior of a larger platform without pretending that one host provides redundancy.
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