specific deploy, the CLI orchestrates a multi-step pipeline that takes your project from source code to a running production environment.
Authentication
Verifies you are logged in to Specific Cloud. If not, your browser opens for login. Subsequent deploys reuse the saved session.
Local build testing
Runs your build commands locally to catch errors before deploying. This gives you fast feedback without waiting for a cloud build.
Cloud builds
Your code is built in the cloud based on the
Dependencies are cached for faster rebuilds when only source code changes.
build blocks your coding agent defined. Multiple builds run in parallel to minimize total build time.Specific supports node, python, go, rust, and java runtimes and automatically detects your dependency manager:| Base | Detected Files | Install Command |
|---|---|---|
node | package-lock.json | npm ci |
node | yarn.lock | yarn install --frozen-lockfile |
node | pnpm-lock.yaml | pnpm install --frozen-lockfile |
node | package.json only | npm install |
python | requirements.txt | pip install -r requirements.txt |
python | Pipfile.lock | pipenv install --deploy --system |
python | poetry.lock | poetry install |
python | pyproject.toml | pip install . |
go | go.mod | go mod download |
Secrets and config
If any secrets or config values are missing, you are prompted to enter them. You can enter values while builds are still running — no need to wait.
Resource provisioning
Infrastructure resources are provisioned as needed: databases, object storage, Redis, and real-time sync engines. Resources are created once and reused across deploys.
Service deployment
Services are rolled out. If your coding agent has defined deploy hooks, they run at this stage:
pre_deployruns before the service starts. The primary use case is database migrations — if the hook fails, the deployment is automatically aborted.post_deployruns after the service is live. Use this for cache warming, notifications, or other post-deployment tasks.
If any step fails, the deployment is aborted and the error is shown in the terminal. Fix the issue and run
specific deploy again.