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The dependable pattern is GitLab repository → CI runner → tests and build → protected deploy job → SSH to a dedicated VPS user → an idempotent server-side deployment script. The runner can copy a build with rsync and then invoke the script over SSH. This keeps production credentials out of the repository, makes deployments auditable in GitLab, and gives the server one repeatable place to validate configuration, run migrations, restart the application and report failure.
The procedure below is provider-neutral. It assumes a Linux VPS reachable by SSH, a GitLab Runner, and an application that can be started or reloaded by a script on the server.
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A GitLab pipeline should not log in as root and run a long sequence of ad-hoc commands. Instead, the pipeline performs disposable CI work, while the VPS performs only the narrowly defined release operation:
- GitLab checks out the commit.
- A test job runs the project test suite.
- A build job produces a known artifact, such as
dist/. - After those jobs pass, a protected production job starts an SSH agent, loads a dedicated deployment key, transfers the artifact, and calls a script on the VPS.
- The VPS script installs or unpacks the exact release, validates configuration, performs any required migration, restarts or reloads the service, runs a health check and exits non-zero if anything fails.
Give the deployment job an environment named production. GitLab then records deployment history against that environment. Use a resource group for production so two deployment jobs cannot change the same server concurrently.
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Prerequisites and decisions
- A GitLab project containing a working
.gitlab-ci.yml. - A Linux VPS reachable over SSH, normally TCP port 22 or an explicitly configured alternative.
- A non-root user dedicated to deployments. It should have only the permissions required by the deployment script.
- A GitLab Runner, commonly with the Docker or shell executor. Assign a clear tag to the runner intended for production deployment.
- A deployment directory on the VPS and a repeatable server-side script.
- A service manager or process supervisor already configured on the VPS, such as a system service, container compose project or another documented start command.
Decide before writing the pipeline whether the server will receive files from the runner or pull an immutable artifact. This guide uses runner-to-server rsync because it is simple and works for static files and many application bundles. A versioned release-directory variant is shown later for safer rollback.
Prepare the VPS
Create a dedicated deploy user
Create a user that is not root, enable SSH access for that user, and grant only the filesystem and service permissions it needs. Keep administrative operations in a script reviewed by an administrator. If the service manager requires elevated commands, allow only those exact commands through a narrowly scoped privilege rule rather than granting unrestricted sudo access.
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Choose a stable path, for example /srv/myapp, and create it with ownership that lets the deploy user replace the release files without changing unrelated parts of the server. Keep the application configuration outside the transferred artifact when possible. Secrets should be supplied by the VPS environment or a secret manager, not committed to GitLab.
Install and test the deployment script
Place a script such as /srv/myapp/deploy.sh on the VPS. It should be executable by the deploy user, fail on errors and be safe to run repeatedly. A minimal structure is:
#!/usr/bin/env bash
set -Eeuo pipefail
APP_DIR=/srv/myapp
RELEASE_DIR="$APP_DIR/dist"
# Validate that the transferred artifact is present.
test -d "$RELEASE_DIR"
test -f "$RELEASE_DIR/RELEASE.txt" || true
# Install dependencies or run migrations here, if this application needs them.
# Keep each operation ordered and repeatable.
# Replace this with the service command for your application.
sudo systemctl reload myapp.service
# Replace this URL and check with the application's real health endpoint.
if ! curl --fail --silent --show-error http://127.0.0.1:8080/healthz >/dev/null; then
echo "Health check failed" >&2
exit 1
fi
The example is deliberately generic: replace the service name, dependency installation, migration commands and health endpoint. The important behavior is that a missing artifact, failed migration, unsuccessful restart or failed health check returns a non-zero status so GitLab marks the deployment failed.
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Set up a dedicated SSH key
Use a key pair created solely for automation. GitLab’s SSH guidance recommends storing private keys securely, avoiding personal keys for automated jobs and rotating deployment keys regularly.
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- Generate the pair on an administrator-controlled workstation or another approved secure host. Use a modern key type supported by your OpenSSH installation, and protect the private key while it is at rest.
- Append the public key to the deploy user’s
~/.ssh/authorized_keyson the VPS. Set the directory to mode700and the file to mode600. - Test the key manually as the deploy user before involving CI. Confirm that it can reach the intended host and execute only the expected deployment entry point.
- In GitLab, open Settings → CI/CD → Variables and add the private key as a File variable named
SSH_PRIVATE_KEY. Mark it Protected and scope it to the production environment. - Add the server host key as a protected variable, for example
VPS_KNOWN_HOSTS. Obtain it through a trusted administrative process and verify the fingerprint out of band. Do not make production jobs silently accept an unknown host key.
A file variable is exposed to the job as a temporary file path, which is why the pipeline below passes $SSH_PRIVATE_KEY to ssh-add. Never print that variable, run shell tracing around it, or write it into an artifact.
Define protected GitLab variables
Keep production infrastructure identifiers and credentials out of the repository. In Settings → CI/CD → Variables, define these values and protect them so they are available only to protected branches or tags.
| Variable | Type | Purpose | Example value |
|---|---|---|---|
SSH_PRIVATE_KEY |
File | Dedicated private key for the VPS deploy user | Temporary file path supplied by GitLab |
VPS_KNOWN_HOSTS |
Variable | Verified SSH host-key line(s) | One or more entries from a trusted fingerprint check |
VPS_HOST |
Variable | DNS name or address of the production VPS | vps.example.net |
VPS_USER |
Variable | Non-root deployment account | deploy |
VPS_PORT |
Variable | SSH port | 22 or your configured port |
DEPLOY_PATH |
Variable | Application directory on the VPS | /srv/myapp |
Environment-scoping the variables to production prevents a staging job from receiving production credentials. Protected variables are delivered only to protected refs, so protect the default production branch or use an explicitly protected release tag.
Choose and constrain the GitLab Runner
| Executor | Strength | Risk or trade-off | Good use |
|---|---|---|---|
| Docker | Each job runs in an isolated container with a predictable tool image. | The image must contain, or install, the required SSH and transfer tools. | Most build and deployment jobs. |
| Shell | Uses tools already installed on the runner host. | Job commands run directly on that host; a compromised job has a larger blast radius. | Controlled, dedicated runner machines. |
| SSH executor | Runner infrastructure executes jobs on a remote machine by design. | It is a different architecture from opening an SSH session inside a normal deploy job and adds another trust boundary. | Organizations that deliberately operate remote runner hosts. |
Tag the production job, for example with production-deploy, and register that tag only on the runner intended to handle production. A tagged job runs only where all its tags are present. Treat self-managed runners as part of the production trust boundary: isolate them from unrelated projects, avoid privileged containers and avoid sharing the host PID namespace unless a narrowly justified requirement has been reviewed.
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Create the pipeline
The following provider-neutral pipeline has test, build and deploy stages. The deploy job runs only for the default branch, waits for successful earlier stages, records a production environment and serializes deployments with resource_group.
stages: [test, build, deploy]
test:
stage: test
script:
- ./ci/test.sh
build:
stage: build
script:
- ./ci/build.sh
artifacts:
paths:
- dist/
deploy_production:
stage: deploy
tags:
- production-deploy
environment:
name: production
resource_group: production
rules:
- if: '$CI_COMMIT_BRANCH == $CI_DEFAULT_BRANCH'
before_script:
- command -v ssh-agent >/dev/null || (apt-get update -y && apt-get install -y openssh-client rsync)
- eval "$(ssh-agent -s)"
- chmod 400 "$SSH_PRIVATE_KEY"
- ssh-add "$SSH_PRIVATE_KEY"
- mkdir -p ~/.ssh && chmod 700 ~/.ssh
- printf '%sn' "$VPS_KNOWN_HOSTS" > ~/.ssh/known_hosts
- chmod 600 ~/.ssh/known_hosts
script:
- rsync -az --delete -e "ssh -p ${VPS_PORT:-22}" dist/ "$VPS_USER@$VPS_HOST:$DEPLOY_PATH/dist/"
- ssh -p "${VPS_PORT:-22}" "$VPS_USER@$VPS_HOST" "$DEPLOY_PATH/deploy.sh"
What each job does
Test calls a repository-owned script so the same checks can be run locally and in CI. Make that script return a failure code when tests fail.
Build creates dist/ and publishes it as a job artifact. The deploy job receives the artifact from the successful build rather than rebuilding production code with different inputs.
Deploy installs OpenSSH and rsync only when the selected image does not already provide them, starts an agent, loads the file variable, writes the verified host key, transfers the artifact and invokes the VPS script. The explicit SSH port works with either the default port or a custom value.
Adjust the transfer command
rsync -az --delete synchronizes the destination with the artifact: files removed from the build are removed from the destination as well. Use it only when the target directory contains nothing that must be preserved independently, such as user uploads or runtime-generated data. Store those data directories outside dist/, or omit them with an appropriate exclusion.
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For a large artifact or a network policy that forbids runner-to-server transfer, publish the build to an internal artifact store and have the VPS download a specific immutable version. The security requirements remain the same: authenticated access, checksum or signature verification, a non-root deploy account and an idempotent server script.
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In-place release
The sample copies files into one directory and reloads the service. It is easy to understand, but a process may observe a partially updated tree if it reads files while rsync is still running. It also needs a separate backup procedure for rollback.
Versioned release directories
A safer pattern creates a directory such as /srv/myapp/releases/$CI_COMMIT_SHA, transfers the complete artifact there, validates it, then atomically switches a current symlink and reloads the service. Keep the previous release directory until the health check succeeds. If the new release fails, point current back to the previous version and reload again.
Pass the commit identifier to the script as an argument or write it into the artifact. Never let the script infer “latest” from an uncontrolled directory listing; deploy the exact commit that passed CI.
Migrations and configuration
Run database migrations in a controlled order and make them compatible with the application version being started. Validate required environment variables before stopping a healthy service. Configuration syntax checks should happen before the symlink switch or restart so a bad configuration does not replace a working release.
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Prevent overlapping and outdated deployments
resource_group: production makes production deployments share one concurrency lock. Without serialization, two pipelines can transfer different artifacts simultaneously, restart the service in an unpredictable order or leave the server reporting the older commit after the newer pipeline finishes.
Use rules so only the intended production ref can deploy. For higher-risk systems, require a manual approval job or a protected branch promotion. Decide what should happen when a newer pipeline supersedes an older one: cancel or prevent outdated jobs where your GitLab settings allow it, and ensure a queued older job cannot overwrite a newer release after waiting.
Secure the runner and deployment boundary
- Use a dedicated production runner tag and do not allow unrelated projects to schedule on that runner.
- Do not enable privileged container mode or host PID sharing unless the requirement is explicit, controlled and reviewed.
- Keep the private key protected, environment-scoped and out of logs and artifacts.
- Rotate the key and remove old public keys from
authorized_keyswhen personnel, runners or infrastructure change. - Monitor SSH access and deployment history. A failed job should be investigated rather than rerun blindly.
- Limit the deploy user’s filesystem and service permissions. A deployment key should not provide interactive administrative access.
- Verify the VPS host key instead of using options that accept every unknown host.
Verify the first deployment
- Run the test and build jobs on a branch and confirm that the artifact contains exactly the files expected in production.
- Protect the production branch or tag, create the production-scoped variables and check that an unprotected test branch cannot access them.
- Run an SSH connectivity test from the selected runner using the deploy key and verified
known_hosts; do not print secret values. - Trigger the production pipeline from the permitted ref. Confirm that the deploy job waits for test and build success.
- On the VPS, inspect the service status, application logs and health endpoint. Confirm the running commit or release identifier.
- Review GitLab’s production environment history and retain the job log without exposing credentials.
- Deliberately test a failure in a non-production environment: a missing artifact, failed health check or rejected migration should produce a non-zero script exit and a failed GitLab job.
Troubleshoot common failures
Permission denied (publickey)
- Confirm that the public key is in the correct deploy user’s
authorized_keys. - Check ownership and modes on
~/.sshandauthorized_keys. - Verify that the job uses the file variable path, not the variable contents as a literal filename.
- Confirm that the runner can reach the configured host and port and that the VPS firewall permits it.
Host-key verification fails
Regenerate VPS_KNOWN_HOSTS through a trusted fingerprint check and update the protected variable. Do not “fix” the failure by disabling strict host-key checking.
rsync cannot write the destination
Check the deploy user’s ownership of the deployment directory, available disk space and whether the destination path exists. If the service writes uploads into that tree, move uploads outside the synchronized directory or define a deliberate exclusion.
The script succeeds but the service is unhealthy
Make the script fail when the health endpoint fails. Inspect service logs, environment variables, migration output and listening ports. A restart command that returns success does not prove that the application finished starting.
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Check branch rules, queued pipelines and the resource group. Record the commit SHA in each release and ensure an older queued deployment cannot run after a newer one without an explicit promotion decision.
Quick Recap
Operational checklist
- Non-root deploy user exists and has only required permissions.
- Dedicated automation key is installed and protected; personal keys are not reused.
- Production variables are protected and scoped to the production environment.
- Host-key verification is enabled with a trusted
known_hostsvalue. - Runner tags select an isolated production runner.
- Tests and build complete before deploy.
- Deployment is serialized with a production resource group.
- Server script is idempotent, validates configuration, handles migrations, checks health and returns failure correctly.
- Release identity and rollback procedure are documented and tested.
- Runner, SSH and GitLab environment access are monitored and keys are rotated.
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