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CLI Commands Reference

Commands you use most live at the top. Advanced and experimental commands are listed at the bottom.

deployml doctor

Check that required tools are installed and authenticated. Optionally checks enabled APIs and IAM roles on a project.

deployml doctor
deployml doctor --project-id YOUR_GCP_PROJECT_ID

Options:

  • --project-id, -j: GCP project to probe for enabled APIs and IAM role coverage.

The doctor checks: tool versions for docker, terraform, gcloud, bq; gcloud auth and Application Default Credentials; Infracost (optional); and for a given project, required APIs and IAM roles.

deployml init

Enable required GCP APIs for a project and create a local docker/ folder plus a runnable config.yaml starter. Run once per project.

deployml init --provider gcp --project-id YOUR_GCP_PROJECT_ID

Options:

  • --provider, -p: Cloud provider. Currently gcp is fully supported. aws and azure write skeleton configs.
  • --project-id, -j: GCP project ID.
  • --path: Directory where the project is initialized. Defaults to current directory.
  • --overwrite: Overwrite an existing docker/ folder or config.yaml.

The generated config.yaml includes a provider.image_tag field set to the deployml version. Override this to pin to a specific build tag.

deployml build-images

Build Docker images and push them to GCP Artifact Registry. Reads project ID, region, and image_tag from config.yaml by default.

deployml build-images --create-repo

Options:

  • --config-path, -c: Path to config YAML file. Default config.yaml.
  • --docker-root, -d: Folder containing subfolders with Dockerfiles. Default is the built-in deployml docker directory.
  • --gcp-project, -p: GCP project ID. Default inferred from config.
  • --region: GCP region. Default inferred from config.
  • --repository: Artifact Registry repository name. Default mlops-images.
  • --tag, -t: Image tag. Default reads config.provider.image_tag, falls back to v{deployml_version}.
  • --create-repo: Create the Artifact Registry repository on first run.
  • --dry-run: Print commands without executing.
  • --platform: Local build platform. Defaults to the host architecture so images run on a local minikube node, including arm64 Macs. Pass linux/amd64 only when building locally for a manual amd64 push. Ignored in GCP Cloud Build mode.

Builds run on Cloud Build, so a local Docker daemon is not required for GCP mode. In local mode a daemon probe runs first and the build targets the host architecture.

deployml deploy

Deploy infrastructure from a YAML config file. Prompts for confirmation by default.

deployml deploy --verbose
deployml deploy --verbose --yes

Options:

  • --config-path, -c: Path to config YAML. Default config.yaml.
  • --verbose, -v: Stream Terraform logs to stdout. Without this you get a progress bar.
  • --yes, -y: Skip the [y/N] deploy confirmation. Required for non-interactive scripts.
  • --generate-only, -g: For the GKE flow, render the Kubernetes manifests without applying them, so you can review and then apply with gke-apply.

Before any cloud work, deploy validates the config shape and, for GCP, preflights both gcloud auth and Application Default Credentials. A missing ADC fails fast with gcloud auth application-default login guidance instead of an opaque "default credentials not found" at apply. A malformed stack entry also fails here with a clear message rather than crashing mid-deploy.

First-time deploy takes about 20 minutes because Cloud SQL Postgres provisioning is slow.

deployml get-urls

Print service URLs from the last deployment and write them to a .env file. Database credentials are masked.

deployml get-urls
deployml get-urls --show-secrets

Options:

  • --config-path, -c: Path to config YAML. Default config.yaml.
  • --env-path: Where to write the .env. Default .env.
  • --show-secrets: Additionally fetch and print the Grafana admin password and the Cloud SQL Auth Proxy connection command.

deployml destroy

Tear down all infrastructure for a given config. Also removes the Artifact Registry repo and the Cloud Build staging bucket created by build-images, so a destroyed project leaves no billing residue. Pass --keep-images when other workspaces in the same project share those images.

deployml destroy --yes

Options:

  • --config-path, -c: Path to config YAML. Default config.yaml.
  • --clean-workspace: Remove the local .deployml/ workspace folder after destroy.
  • --yes, -y: Skip both the destroy confirmation and the Terraform state cleanup prompt. Also auto-confirms image cleanup.
  • --workspace: Override the workspace name from config.
  • --keep-images: Keep the Artifact Registry repo and the Cloud Build staging bucket. Use when other workspaces in the same project still run on those images.
  • --repository: Artifact Registry repo to delete. Default mlops-images. Match the --repository you passed to build-images.

On partial failure, Terraform state is preserved and the command prints recovery instructions including gcloud asset search-all-resources for finding residual resources.

Config file reference

Top-level fields used by deploy and destroy:

name: string                       # workspace name. defaults to "default" if omitted
provider:
  name: gcp | aws | azure
  project_id: string               # required for gcp
  region: string                   # required for gcp
  image_tag: string                # optional. default v{deployml_version}
deployment:
  type: cloud_run | cloud_vm | gke # required
stack:
  - <stage_name>:
      name: mlflow | fastapi | grafana | feast | cron
      params: {}                   # tool-specific

Supported stage names: experiment_tracking, artifact_tracking, model_registry, model_serving, model_monitoring, feature_store, workflow_orchestration.

Advanced and experimental commands

These exist in the CLI but are not part of the documented happy path. Use at your own risk and inspect the source.

  • deployml generate: Interactive YAML generator. Less useful since init now writes a runnable config. Pass --force, -f to overwrite an existing config.yaml without the confirm prompt.
  • deployml status: Stub. Reports deployment status of current workspace.
  • deployml terraform: Run raw terraform actions (plan, apply, destroy) on a rendered workspace.
  • deployml teardown: Manage scheduled auto-teardown jobs.
  • deployml vm: Placeholder for VM deployment.
  • deployml mlflow-init, deployml mlflow-deploy: MLflow-only minikube flow. mlflow-init provisions a PersistentVolumeClaim by default with --persistent-storage so the sqlite backend and artifacts survive pod restarts, with --pvc-size to size it and --ephemeral-storage to opt out. mlflow-deploy takes --namespace, -n to isolate the stack.
  • deployml minikube-init, deployml minikube-deploy: Local Kubernetes flow for testing without GCP. minikube-deploy takes --namespace, -n. Build local images with build-images in local mode, which targets the host architecture so they run on the minikube node.
  • deployml gke-cluster-create: Create a GKE cluster. Autopilot by default with --region; pass --standard for a small zonal cluster.
  • deployml gke-init, deployml gke-deploy, deployml gke-apply, deployml gke-destroy: GKE deployment path. MLflow on GKE provisions a PersistentVolumeClaim by default so experiment data survives pod restarts. Deploy commands take --namespace, -n, and MLflow and FastAPI must share a namespace for in-cluster service DNS to resolve. gke-destroy removes the deployed manifests including the PVC and the referenced gcr.io image so nothing keeps billing, with --keep-images to retain images for a quick redeploy and --delete-cluster to remove the cluster. See the GKE flow notes in the tutorial.

The fully supported and tested path is GCP Cloud Run via init, build-images, deploy, get-urls, destroy.