spark-pulse 1.11.1

Web UI for spark-vllm-docker — recipe management, deployment, and monitoring for DGX Spark

Spark Pulse

Spark Pulse is a web control plane for spark-vllm-docker. It brings recipe discovery, deployment management, live monitoring, cache cleanup, and configuration into one interface for NVIDIA DGX Spark hardware.

License: MIT — Copyright © 2026 Kharkevich Engineering Lab

Disclaimer: This project is not sponsored by, endorsed by, or affiliated with NVIDIA Corporation or any of its subsidiaries. NVIDIA, DGX, and related trademarks are property of their respective owners.

Features

• Recipe browsing - Explore deployment recipes, model variants, and mod combinations in a clean catalog view.
• Deployment jobs - Launch deployments, watch live logs, inspect status, and stop running jobs from the UI.
• Real-time monitoring - Track GPU, CPU, RAM, and disk usage with streaming updates.
• Cache management - Review and clean Hugging Face, wheel, ccache, Triton, and related caches.
• Settings and auth - Configure the backend path, defaults, and OIDC authentication.
• MCP server - Expose the same operations to Model Context Protocol clients and automation.

Screenshots

Recipes

Browse available deployment recipes, inspect model details, and compare supported variants at a glance.

Jobs

Monitor deployments, stream logs, and manage running jobs without leaving the dashboard.

Monitoring

Watch GPU, CPU, and disk usage in real time alongside active GPU processes.

Installation

Install the published package from PyPI:

python3 -m pip install spark-pulse

This installs the spark-pulse command-line interface.

Usage

Start the web app after installation:

spark-pulse start

Then open the UI in your browser. The default port is 8100 unless you changed it in configuration.

Common runtime commands:

# Start the MCP server for assistants and automation
spark-pulse mcp

# Install and manage the app as a systemd service
spark-pulse install
spark-pulse status
spark-pulse start-service
spark-pulse stop-service
spark-pulse uninstall

Add --user to any of the service commands if you want a user-scoped systemd unit.

Authentication is optional. When enabled, Spark Pulse redirects users through your configured OIDC provider and protects the UI and API routes.

Configuration

Spark Pulse reads settings from config.yaml (bundled with the package) and merges user overrides from ~/.config/spark-pulse/settings.json. Environment variables take highest priority.

config.yaml Reference

Key	Type	Default	Description
spark_vllm_path	string	/tmp/spark-vllm-docker	Absolute path to the spark-vllm-docker installation directory.
webui_port	int	8100	TCP port the web UI listens on.
default_container	string	vllm-node	Default Docker container name for deployments.
default_gpu_mem_util	float	0.8	Default GPU memory utilization fraction (0.0–1.0).
default_port_range_start	int	9000	Start of the ephemeral port range for deployments.
default_port_range_end	int	9100	End of the ephemeral port range for deployments.
job_retention_days	int	7	Number of days to retain completed job records.
cluster_enabled	bool	false	Enable multi-node cluster mode.
mcp_enabled	bool	true	Enable the MCP server endpoint.
mcp_path	string	/mcp	HTTP path for the MCP server.
mcp_api_token	string	(empty)	Optional API token to protect MCP requests.
auth_enabled	bool	false	Enable OIDC authentication.
oidc_provider_url	string	(empty)	OIDC provider URL (e.g. https://keycloak.example.com/realms/myrealm).
oidc_client_id	string	(empty)	OIDC client ID.
oidc_client_secret	string	(empty)	OIDC client secret — stored securely in ~/.config/spark-pulse/secrets.json.

Environment Variable Overrides

The following environment variables override their corresponding config keys:

Environment Variable	Config Key	Description
SPARK_VLLM_PATH	spark_vllm_path	Override the spark-vllm-docker path.
WEBUI_PORT	webui_port	Override the web UI port.

File Locations

File	Purpose
config.yaml	Bundled defaults (read-only, overwritten on package update).
~/.config/spark-pulse/settings.json	Persistent user overrides (survives package updates).
~/.config/spark-pulse/secrets.json	Securely stored secrets (mode 0600).

Example: Enabling OIDC Authentication

# config.yaml or settings.json
auth_enabled: true
oidc_provider_url: https://keycloak.example.com/realms/myrealm
oidc_client_id: spark-pulse

Then set the client secret via the UI Settings page or directly in secrets.json:

{
  "oidc_client_secret": "your-secret-here"
}

Development Mode with Mock OIDC Provider

For local development, Spark Pulse ships with convenience scripts that start a mock OIDC provider alongside the dev server. This lets you test the full SSO login flow without a real identity provider.

Full stack (backend + frontend with hot-reload):

./scripts/run-dev-oidc-full.sh

This script:

1. Starts the mock OIDC provider on http://localhost:9400
2. Creates ~/.config/spark-pulse/settings.json and secrets.json with dev credentials
3. Launches the backend with --reload (serves both API and built frontend)

Backend only (for API testing):

./scripts/run-dev-oidc.sh

Dev credentials (both scripts):

• Provider URL: http://localhost:9400
• Client ID: spark-pulse-dev
• Client Secret: dev-secret

To stop, press Ctrl+C — the scripts clean up all background processes.

Development

Clone the repository and install local development dependencies:

python3 -m pip install -e ".[dev]"

Build the frontend and run the app locally:

cd web && npm install && npm run build && cd ..
./scripts/run-dev-server.sh

Useful development commands:

./scripts/run-backend.sh
./scripts/run-production.sh
./scripts/build-ui.sh
pytest
python -m build

API

The app exposes REST endpoints under /api/* for recipes, deployments, memory, cache, and settings, plus /auth/* routes for OIDC login and session handling.

License

MIT. See LICENSE.