Added npm package wrapper to enable installation via npm while maintaining the Deno binary distribution model. New Files: - package.json: npm package configuration with binary wrapper - bin/spark-wrapper.js: Detects platform and executes correct binary - scripts/install-binary.js: Downloads appropriate binary on npm install - .npmignore: Excludes source files from npm package - npmextra.json: npm extra configuration Updated: - readme.md: Added npm installation instructions How It Works: 1. User runs: npm install -g @serve.zone/spark 2. Postinstall script (install-binary.js) downloads the correct pre-compiled binary for the user's platform from Gitea releases 3. Binary is cached in dist/binaries/ 4. Wrapper script (spark-wrapper.js) executes the binary when user runs 'spark' command Supported via npm: - Linux (x64, ARM64) - macOS (Intel, Apple Silicon) - Windows (x64) This maintains the benefits of Deno compilation (no runtime deps) while providing familiar npm-based installation for users who prefer it.
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@serve.zone/spark 🔥
A powerful Deno-powered server management tool for the modern infrastructure
Spark is a comprehensive tool for maintaining and configuring servers at the OS level, with deep Docker integration and advanced task scheduling capabilities. Built for the serve.zone infrastructure, Spark serves as the backbone for @serve.zone/cloudly cluster management, handling everything from daemon orchestration to container lifecycle management.
✨ Features
- 🚀 Standalone Binary - No runtime dependencies, just download and run
- 🐳 Docker Integration - Native support for Docker services, stacks, secrets, and networks
- ⚙️ Daemon Management - Systemd integration for reliable service operation
- 📅 Task Scheduling - Cron-like task scheduling for automation
- 🔄 Auto-Updates - Self-updating capabilities for zero-downtime deployments
- 🔐 Secure Secrets - Docker secrets management for sensitive data
- 📊 Comprehensive Logging - Built-in logging with multiple severity levels
- 🎯 Mode Support - Cloudly and CoreFlow node operation modes
🚀 Installation
Quick Install (Recommended)
Install the latest version via our installation script:
curl -sSL https://code.foss.global/serve.zone/spark/raw/branch/master/install.sh | sudo bash
npm Install
Install via npm (automatically downloads the correct binary for your platform):
npm install -g @serve.zone/spark
Specific Version
curl -sSL https://code.foss.global/serve.zone/spark/raw/branch/master/install.sh | sudo bash -s -- --version v1.2.2
Manual Installation
Download the binary for your platform from the releases page and make it executable:
# Example for Linux x64
wget https://code.foss.global/serve.zone/spark/releases/download/v1.2.2/spark-linux-x64
chmod +x spark-linux-x64
sudo mv spark-linux-x64 /usr/local/bin/spark
Supported Platforms
- 🐧 Linux (x86_64, ARM64)
- 🍎 macOS (Intel, Apple Silicon)
- 🪟 Windows (x86_64)
🎯 Quick Start
Install as System Daemon
Set up Spark to run as a systemd service:
sudo spark installdaemon
This command:
- Creates a systemd service unit
- Enables automatic startup on boot
- Starts the Spark daemon immediately
Configure Operation Mode
Spark supports different operation modes for various use cases:
# For Cloudly cluster management
sudo spark asdaemon --mode cloudly
# For CoreFlow node management
sudo spark asdaemon --mode coreflow-node
View Logs
Monitor Spark daemon activity in real-time:
sudo spark logs
📖 CLI Reference
Core Commands
spark installdaemon
Installs Spark as a system daemon service. This sets up a systemd unit that automatically starts on boot.
sudo spark installdaemon
spark updatedaemon
Updates the daemon service configuration to the current Spark version.
sudo spark updatedaemon
spark asdaemon [--mode MODE]
Runs Spark in daemon mode. Requires a mode to be specified (either via --mode flag or from saved configuration).
sudo spark asdaemon --mode cloudly
Available modes:
cloudly- Manages Cloudly servicescoreflow-node- Manages CoreFlow node services
spark logs
Displays real-time logs from the Spark daemon service.
sudo spark logs
spark prune
Performs a complete cleanup of Docker resources and restarts services. Use with caution!
sudo spark prune
This command:
- Stops the Spark daemon
- Removes all Docker stacks
- Removes all Docker services
- Removes all Docker secrets
- Removes specified Docker networks
- Prunes the Docker system
- Restarts Docker
- Restarts the Spark daemon
Advanced Usage
Check Version
spark --version
Get Help
spark help
🔧 Programmatic Usage
While Spark is primarily designed as a CLI tool and daemon, you can also use it as a library in your Deno projects.
Import from Deno
import { Spark } from 'https://code.foss.global/serve.zone/spark/raw/branch/master/mod.ts';
Basic Usage
import { Spark } from './mod.ts';
// Create a Spark instance
const spark = new Spark();
// Start the daemon programmatically
await spark.daemonStart();
Task Scheduling
Schedule automated tasks using the built-in task manager:
import { Spark } from './mod.ts';
const spark = new Spark();
// Define a custom task
const backupTask = {
name: 'daily-backup',
taskFunction: async () => {
console.log('Running backup...');
// Your backup logic here
},
};
// Schedule it to run daily at 2 AM
spark.sparkTaskManager.taskmanager.addAndScheduleTask(
backupTask,
'0 2 * * *'
);
Service Management
Manage Docker services programmatically:
import { Spark } from './mod.ts';
const spark = new Spark();
// Add a service to manage
spark.sparkUpdateManager.services.push({
name: 'my-app',
image: 'code.foss.global/myorg/myapp',
url: 'myapp',
environment: 'production',
port: '3000',
secretJson: {
API_KEY: 'secret-value',
DATABASE_URL: 'postgresql://...',
},
});
// Start managing services
await spark.sparkUpdateManager.start();
Configuration Management
Access and modify Spark's configuration:
import { Spark } from './mod.ts';
const spark = new Spark();
// Write configuration
await spark.sparkConfig.kvStore.writeKey('mode', 'cloudly');
// Read configuration
const mode = await spark.sparkConfig.kvStore.readKey('mode');
console.log(`Current mode: ${mode}`);
Logging
Use Spark's built-in logger for consistent logging:
import { logger } from './ts/spark.logging.ts';
// Log at different levels
logger.log('info', 'Application starting...');
logger.log('ok', 'Service deployed successfully');
logger.log('warn', 'High memory usage detected');
logger.log('error', 'Failed to connect to database');
logger.log('success', 'Backup completed');
🏗️ Architecture
Core Components
┌─────────────────────────────────────────┐
│ Spark Instance │
├─────────────────────────────────────────┤
│ │
│ ┌─────────────────────────────────┐ │
│ │ SparkConfig │ │
│ │ - KV Store │ │
│ │ - Mode Configuration │ │
│ └─────────────────────────────────┘ │
│ │
│ ┌─────────────────────────────────┐ │
│ │ SparkTaskManager │ │
│ │ - Cron Scheduling │ │
│ │ - Task Execution │ │
│ └─────────────────────────────────┘ │
│ │
│ ┌─────────────────────────────────┐ │
│ │ SparkServicesManager │ │
│ │ - Docker Integration │ │
│ │ - Service Updates │ │
│ │ - Secret Management │ │
│ └─────────────────────────────────┘ │
│ │
│ ┌─────────────────────────────────┐ │
│ │ SmartDaemon │ │
│ │ - Systemd Integration │ │
│ │ - Service Lifecycle │ │
│ └─────────────────────────────────┘ │
│ │
└─────────────────────────────────────────┘
Key Classes
Spark- Main orchestrator class that coordinates all componentsSparkConfig- Handles configuration storage and retrievalSparkTaskManager- Manages scheduled tasks and automationSparkServicesManager- Manages Docker services and updatesSparkInfo- Provides project and version information
🔄 Update Management
Spark includes self-updating capabilities:
import { Spark } from './mod.ts';
const spark = new Spark();
// Check for and apply updates
await spark.sparkUpdateManager.updateServices();
The update manager:
- Pulls latest Docker images
- Manages service rollouts
- Handles zero-downtime deployments
- Manages Docker secrets securely
🐳 Docker Integration
Service Definition
const serviceDefinition = {
name: 'api-server',
image: 'code.foss.global/myorg/api',
url: 'api',
environment: 'production',
port: '8080',
secretJson: {
JWT_SECRET: 'your-jwt-secret',
DB_PASSWORD: 'your-db-password',
},
};
spark.sparkUpdateManager.services.push(serviceDefinition);
Stack Management
Spark manages Docker stacks for complex multi-service deployments:
# View running stacks
docker stack ls
# Spark manages these automatically
🛠️ Development
Prerequisites
- Deno v2.x or later
Running from Source
# Clone the repository
git clone https://code.foss.global/serve.zone/spark.git
cd spark
# Run directly
deno run --allow-all mod.ts
# Run tests
deno test --allow-all test/
# Type check
deno check mod.ts
# Format code
deno fmt
# Lint
deno lint
Building Binaries
Compile for all supported platforms:
bash scripts/compile-all.sh
Binaries will be output to dist/binaries/.
Compile for Specific Platform
# Linux x64
deno compile --allow-all --output spark-linux-x64 --target x86_64-unknown-linux-gnu mod.ts
# macOS ARM64
deno compile --allow-all --output spark-macos-arm64 --target aarch64-apple-darwin mod.ts
🔐 Security
Permissions
Spark requires the following Deno permissions:
--allow-net- API communication, Docker socket access--allow-read- Configuration files, project files--allow-write- Logs, configuration updates--allow-run- systemctl, Docker commands--allow-env- Environment variables--allow-sys- System information
Secrets Management
Always use Docker secrets for sensitive data:
const serviceWithSecrets = {
name: 'secure-app',
image: 'myapp:latest',
secretJson: {
API_KEY: Deno.env.get('API_KEY')!,
DB_PASSWORD: Deno.env.get('DB_PASSWORD')!,
},
};
🐛 Troubleshooting
Service Won't Start
Check the daemon status:
sudo systemctl status smartdaemon_spark
View recent logs:
sudo journalctl -u smartdaemon_spark -n 100
Docker Issues
Verify Docker is running:
sudo systemctl status docker
Check Docker socket permissions:
sudo ls -la /var/run/docker.sock
Configuration Issues
Check current mode:
# Run spark programmatically
deno run --allow-all -e "
import { Spark } from './mod.ts';
const s = new Spark();
const mode = await s.sparkConfig.kvStore.readKey('mode');
console.log('Mode:', mode);
"
📝 Examples
Automated System Maintenance
import { Spark } from './mod.ts';
const spark = new Spark();
// Schedule weekly system updates
const updateTask = {
name: 'system-update',
taskFunction: async () => {
const shell = new Deno.Command('bash', {
args: ['-c', 'apt-get update && apt-get upgrade -y'],
});
await shell.output();
},
};
// Every Sunday at 3 AM
spark.sparkTaskManager.taskmanager.addAndScheduleTask(
updateTask,
'0 3 * * 0'
);
await spark.daemonStart();
Multi-Service Deployment
import { Spark } from './mod.ts';
const spark = new Spark();
// Add multiple services
const services = [
{
name: 'frontend',
image: 'code.foss.global/myorg/frontend',
url: 'frontend',
port: '80',
environment: 'production',
},
{
name: 'backend',
image: 'code.foss.global/myorg/backend',
url: 'backend',
port: '3000',
environment: 'production',
secretJson: {
DATABASE_URL: Deno.env.get('DATABASE_URL')!,
},
},
{
name: 'worker',
image: 'code.foss.global/myorg/worker',
url: 'worker',
environment: 'production',
},
];
services.forEach(svc => spark.sparkUpdateManager.services.push(svc));
await spark.daemonStart();
🤝 Support
For issues, questions, or contributions:
License and Legal Information
This repository contains open-source code that is licensed under the MIT License. A copy of the MIT License can be found in the license file within this repository.
Please note: The MIT License does not grant permission to use the trade names, trademarks, service marks, or product names of the project, except as required for reasonable and customary use in describing the origin of the work and reproducing the content of the NOTICE file.
Trademarks
This project is owned and maintained by Task Venture Capital GmbH. The names and logos associated with Task Venture Capital GmbH and any related products or services are trademarks of Task Venture Capital GmbH and are not included within the scope of the MIT license granted herein. Use of these trademarks must comply with Task Venture Capital GmbH's Trademark Guidelines, and any usage must be approved in writing by Task Venture Capital GmbH.
Company Information
Task Venture Capital GmbH Registered at District court Bremen HRB 35230 HB, Germany
For any legal inquiries or if you require further information, please contact us via email at hello@task.vc.
By using this repository, you acknowledge that you have read this section, agree to comply with its terms, and understand that the licensing of the code does not imply endorsement by Task Venture Capital GmbH of any derivative works.