Deployment Guide

NodeTool supports multiple deployment targets driven by a single deployment.yaml configuration. The nodetool deploy command family builds container images, applies configuration, and manages the lifecycle of remote services across self-hosted hosts, RunPod serverless, and Google Cloud Run.

Quick Reference: What Do You Want to Do?

I want to… What you need
Run NodeTool on my own server → Self-Hosted Deployment with proxy
Deploy to RunPod for GPU access → RunPod Deployment with Docker + RunPod API key
Deploy to Google Cloud Run → GCP Deployment with gcloud CLI
Use Supabase for auth/storage → Supabase Integration
Set up TLS/HTTPS → See Self-Hosted or Proxy Reference
Configure environment variables → Deployment Configuration

Common Deployment Goals

I want to deploy NodeTool to my own server

  1. Set up your configuration — create a deployment.yaml: 
    nodetool deploy init
nodetool deploy add my-server --type self-hosted
  2. Configure host details — edit ~/.config/nodetool/deployment.yaml with your host, SSH user, and image settings
  3. Build and deploy: 
    nodetool deploy apply my-server
  4. Verify: nodetool deploy status my-server

See Self-Hosted Deployments for full details.

I want to run workflows on GPU via RunPod

  1. Get your RunPod API key from runpod.io
  2. Set up deployment: 
    export RUNPOD_API_KEY="your-key"
nodetool deploy add my-runpod --type runpod
  3. Configure GPU settings in deployment.yaml (gpu_types, gpu_count)
  4. Deploy: 
    nodetool deploy apply my-runpod

See RunPod Deployments for full details.

I want to deploy to Google Cloud

  1. Authenticate with gcloud: gcloud auth login
  2. Set up deployment: 
    nodetool deploy add my-gcp --type gcp
  3. Configure region, CPU/memory in deployment.yaml
  4. Deploy: 
    nodetool deploy apply my-gcp

See GCP Deployments for full details.

I want to use Supabase for authentication and storage

  1. Create a Supabase project at supabase.com
  2. Create storage buckets (assets, assets-temp)
  3. Add to your deployment config: 
    env:
  SUPABASE_URL: https://your-project.supabase.co
  SUPABASE_KEY: your-service-role-key
  AUTH_PROVIDER: supabase
  ASSET_BUCKET: assets
  4. Deploy: nodetool deploy apply <name>

See Using Supabase for full details.

Deployment Workflow

  1. Initialize configuration

    nodetool deploy init
nodetool deploy add <name>

    These commands scaffold deployment.yaml using the schema defined in src/nodetool/config/deployment.py. Each entry specifies a type (self-hosted, runpod, or gcp), container image details, environment variables, and target-specific options.

  2. Review & plan

    nodetool deploy list
nodetool deploy show <name>
nodetool deploy plan <name>

    Planning validates the configuration, renders the effective proxy files (for self-hosted targets), and shows pending actions without mutating remote resources.

  3. Apply & monitor

    nodetool deploy apply <name>
nodetool deploy status <name>
nodetool deploy logs <name> [--follow]
nodetool deploy destroy <name>

    apply builds/pushes container images, provisions infrastructure, updates proxy configuration, and records deployment state in the local cache (src/nodetool/deploy/state.py). Status and logs surface the remote service health.

Deployment Configuration

deployment.yaml accepts the following top-level keys (see SelfHostedDeployment, RunPodDeployment, and GCPDeployment in src/nodetool/config/deployment.py):

  • type – target platform (self-hosted, runpod, gcp)
  • image – container image name/tag/registry
  • paths – persistent storage paths (self-hosted)
  • container – port, workflows, GPU configuration (self-hosted)
  • proxy – proxy services (self-hosted; see the Proxy Reference)
  • runpod / gcp – provider specific compute, region, scaling and credential options
  • env – environment variables injected into the deployed containers

Store secrets (API keys, tokens) in secrets.yaml or environment variables; the deployer merges them at runtime without writing them to disk.

RunPod Deployments

The RunPod deployer (src/nodetool/deploy/deploy_to_runpod.py) builds an AMD64 Docker image, pushes it to your registry, and optionally creates RunPod templates/endpoints through GraphQL.

Requirements

  • Docker (with Buildx for multi-arch builds) and registry credentials
  • RUNPOD_API_KEY in the environment
  • Optional: tuned GPU constraints (gpu_types, gpu_count, idle_timeout, etc.)

Key configuration fields

  • template_id / endpoint_id – existing resources to update (or leave empty to create)
  • compute_type, gpu_types, gpu_count – choose CPU/GPU fleets
  • workers_min / workers_max – autoscaling bounds
  • env – runtime settings exposed to the container

CLI shortcuts

  • nodetool deploy apply <name> – orchestrates build → push → template/endpoint updates
  • nodetool deploy logs <name> – streams RunPod logs (requires endpoint ID in deployment state)
  • nodetool deploy destroy <name> – tears down templates/endpoints (leaves images untouched)

Google Cloud Run Deployments

src/nodetool/deploy/deploy_to_gcp.py and google_cloud_run_api.py manage the Cloud Run flow:

  1. Validate gcloud authentication, project, and enabled APIs
  2. Build/push the container to Artifact Registry or GCR
  3. Deploy or update the Cloud Run service

Requirements

  • Docker and Google Cloud SDK (gcloud) authenticated
  • GOOGLE_CLOUD_PROJECT (and optionally GOOGLE_APPLICATION_CREDENTIALS)
  • Enabled services: Cloud Run, Artifact Registry or Container Registry, Cloud Build (if used)

Key configuration fields

  • service_name, region, registry – Cloud Run identifiers
  • cpu, memory, gpu_type, gpu_count – resource allocation
  • min_instances, max_instances, concurrency, timeout – scaling behavior
  • service_account – runtime identity (required for private resources)
  • gcs_bucket / gcs_mount_path – attach Cloud Storage volumes if needed
  • allow_unauthenticated – set to true for public endpoints (omit to require IAM auth)

Operational commands

  • nodetool deploy status <name> – shows the current Cloud Run URL and revision
  • nodetool deploy logs <name> – tails Cloud Run logs via gcloud
  • nodetool deploy destroy <name> – deletes the Cloud Run service

Self-Hosted Deployments

Self-hosted targets pair a NodeTool worker container with the Docker-aware proxy described in Self-Hosted Deployment and Proxy Reference. Deployment state tracks the running container ID, generated bearer tokens, and hashed proxy configuration to avoid redundant restarts.

Quick checklist

  • Populate host, ssh.user, and image fields in deployment.yaml
  • Configure proxy services (port 80/443 by default) with TLS certificates or ACME settings
  • Mount persistent volumes (workspace, caches) through the services[].volumes map
  • Provide worker_auth_token or let the proxy generate one on first deploy

Apply with nodetool deploy apply <name>; the deployer copies proxy files, restarts containers when configuration changes, and runs health checks before reporting success.

Using Supabase

Supabase can provide both authentication and object storage in your deployment.

1) Configure environment variables in your deployment target:

SUPABASE_URL=https://your-project.supabase.co
SUPABASE_KEY=your-service-role-key
ASSET_BUCKET=assets
# Optional for temporary assets
ASSET_TEMP_BUCKET=assets-temp

# Select authentication provider (none|local|static|supabase)
AUTH_PROVIDER=supabase

2) Create the buckets in Supabase Storage (e.g. assets, assets-temp).

  • For direct public URLs, set the buckets to public in the Supabase dashboard.
  • For private buckets, extend the adapter to sign URLs or front with a proxy that performs signing.

3) Deploy and verify:

  • Logs should show “Using Supabase storage for asset storage”.
  • Run a workflow that saves an image/dataframe and confirm links resolve under …/storage/v1/object/public/<bucket>/….
  • If using Supabase auth (AUTH_PROVIDER=supabase), send Authorization: Bearer <supabase_jwt>.

Notes:

  • If S3 variables are set alongside Supabase, NodeTool prefers Supabase when SUPABASE_URL/SUPABASE_KEY are present.
  • For local development without Supabase/S3, NodeTool uses the filesystem backend.