IoT Embedded
IoT Embedded

Essential HomeLab Applications: Node-RED, Databases, and the Tools That Matter

Explore the essential applications powering Alpha Bits' HomeLab infrastructure. Learn about Node-RED for automation, database strategies with PostgreSQL/Redis/InfluxDB, monitoring with Grafana, and how these tools integrate to create a productive, cost-effective development environment on Raspberry Pi hardware.

Alpha Bits

Alpha Bits

Engineering Team

Sep 8, 2025
8 min read
Essential HomeLab Applications: Node-RED, Databases, and the Tools That Matter

With our hardware humming, networking seamless, and CasaOS managing our containers beautifully, it's time to talk about the applications that actually make our HomeLab useful. After three years of experimentation, we've settled on a core set of services that power everything from client projects to daily operations.

Today, I'll walk you through the essential applications running in our Alpha Bits HomeLab, why we chose each one, and the real-world configurations that make them work together as a cohesive system.

The Philosophy: Purpose-Built, Not Kitchen Sink

Early in our HomeLab journey, I made the classic mistake of deploying every interesting application I found. Media servers, monitoring tools, development environments, automation platforms – if it had a Docker container, I probably tried it.

The result was a sprawling mess of services that consumed resources, required constant maintenance, and provided little actual value. I spent more time managing the infrastructure than using it for productive work.

Our current approach is different: every application must serve a specific purpose in our business operations or learning objectives. If it doesn't contribute to client work, team productivity, or skill development, it doesn't get deployed.

The Core Stack: Applications That Earn Their Keep

Node-RED: The Swiss Army Knife of Automation

If I had to pick one application that best represents the power of HomeLab infrastructure, it would be Node-RED. This visual programming tool has become the nervous system of our entire operation.

What Node-RED Does for Us:

  • IoT Data Processing - Collecting sensor data from client deployments
  • API Integration - Connecting disparate systems and services
  • Workflow Automation - Automating repetitive business processes
  • Data Pipeline Management - ETL processes for analytics and reporting
  • Notification Systems - Alerts, reports, and status updates

Real-World Example: We have a Node-RED flow that monitors our client's manufacturing equipment, processes sensor data in real-time, stores it in InfluxDB, triggers alerts for anomalies, and generates daily reports sent via email. The entire pipeline runs on a Raspberry Pi 4 and handles thousands of data points per hour.

Deployment via CasaOS:

Node-RED is available in the CasaOS app store with ARM optimization. The deployment includes:

  • Persistent data volumes for flows and configurations
  • Environment variables for security settings
  • Network configuration for MQTT and HTTP endpoints
  • Automatic restart policies

Why Node-RED Over Alternatives:

We've tried traditional programming approaches, cloud automation platforms, and other workflow tools. Node-RED wins because:

  • Visual programming is accessible to non-developers
  • Massive library of pre-built nodes
  • Excellent ARM performance
  • Active community and continuous development
  • Perfect for rapid prototyping and iteration

Database Infrastructure: PostgreSQL + Redis + InfluxDB

Data is the lifeblood of any modern application, and our database strategy reflects the diverse needs of our projects.

PostgreSQL - The Reliable Workhorse

PostgreSQL serves as our primary relational database for:

  • Directus CMS data
  • Client application databases
  • User management and authentication
  • Business logic and transactional data

Running on our Pi-Data device with 8GB RAM, PostgreSQL handles multiple databases and concurrent connections without breaking a sweat. The ARM64 builds are mature and performant.

Redis - Speed When It Matters

Redis provides caching and session management:

  • API response caching
  • Session storage for web applications
  • Real-time data sharing between services
  • Queue management for background jobs

The memory efficiency of Redis makes it perfect for Raspberry Pi deployments where RAM is precious.

InfluxDB - Time-Series Excellence

For IoT and monitoring data, InfluxDB is unmatched:

  • Sensor data from client deployments
  • System performance metrics
  • Application analytics and usage tracking
  • Environmental monitoring data

InfluxDB's compression and query performance make it ideal for high-frequency data ingestion on ARM hardware.

Directus: Headless CMS That Actually Works

We've covered Directus in previous posts, but it deserves mention here as a critical application. Running in Docker via CasaOS, Directus provides:

  • Content management for our website and blog
  • API backend for client projects
  • Admin interface for non-technical team members
  • Flexible data modeling without custom development

The fact that Directus runs beautifully on ARM architecture makes it perfect for our distributed setup.

Monitoring and Observability: Grafana + Uptime Kuma

Grafana - Beautiful Data Visualization

Grafana connects to our various data sources to provide:

  • System performance dashboards
  • IoT sensor data visualization
  • Business metrics and KPIs
  • Client project monitoring

The ability to create custom dashboards and share them with clients has been invaluable for demonstrating value and maintaining transparency.

Uptime Kuma - Service Monitoring Made Simple

Uptime Kuma monitors all our services and provides:

  • HTTP/HTTPS endpoint monitoring
  • Database connection checks
  • SSL certificate expiration alerts
  • Beautiful status pages for clients

The lightweight nature and beautiful interface make it perfect for HomeLab environments.

Development and Productivity Tools

Code-Server - VS Code in the Browser

Running VS Code in a browser might sound crazy, but it's incredibly useful:

  • Consistent development environment across devices
  • Access to our codebase from anywhere
  • No need to sync configurations between machines
  • Perfect for quick edits and configuration changes

FileBrowser - Web-Based File Management

FileBrowser provides secure file access:

  • Upload/download files to any Pi
  • Edit configuration files directly
  • Share files with team members
  • Backup and restore operations

Integration Patterns: How Everything Works Together

The real power of our HomeLab comes from how these applications integrate:

Data Flow Example: IoT Monitoring Pipeline

  1. Sensors send data via MQTT to Mosquitto broker
  2. Node-RED processes and enriches the data
  3. InfluxDB stores time-series data
  4. PostgreSQL stores device metadata and configurations
  5. Grafana visualizes data in real-time dashboards
  6. Uptime Kuma monitors the entire pipeline

Content Management Workflow

  1. Directus provides content creation interface
  2. PostgreSQL stores content and metadata
  3. Redis caches frequently accessed content
  4. Node-RED handles webhook notifications
  5. Cloudflare Tunnel exposes APIs to the public

Deployment Strategies and Best Practices

1. Resource Allocation

We distribute applications based on resource requirements:

  • CPU-intensive: Node-RED flows, data processing
  • Memory-intensive: Databases, caching layers
  • I/O-intensive: File management, backup operations
  • Network-intensive: API gateways, monitoring

2. Data Persistence Strategy

  • Critical data: USB SSDs with regular backups
  • Cache data: Local storage with automatic cleanup
  • Log data: Centralized logging with rotation
  • Configuration: Version controlled and backed up

3. Security Considerations

  • Network segmentation: Internal services on ZeroTier only
  • Authentication: Strong passwords and API keys
  • Updates: Regular container updates via Watchtower
  • Monitoring: Alert on unusual activity or failures

Performance Insights: What Actually Works on ARM

After running these applications for months, here are the performance insights:

Excellent ARM Performance:

  • Node-RED: Handles complex flows without issues
  • Redis: Memory efficiency is perfect for Pi constraints
  • Uptime Kuma: Lightweight and responsive
  • FileBrowser: Fast file operations

Good ARM Performance:

  • PostgreSQL: Solid performance with proper tuning
  • Grafana: Some lag with complex dashboards
  • Directus: Good for moderate traffic

Requires Optimization:

  • InfluxDB: Benefits from SSD storage
  • Code-Server: Better on higher-memory Pis

Cost Analysis: Open Source Excellence

One of the best aspects of our application stack is the cost:

  • Node-RED: Free, open source
  • PostgreSQL: Free, open source
  • Redis: Free, open source
  • InfluxDB: Free tier sufficient for our needs
  • Directus: Free, open source
  • Grafana: Free, open source
  • Uptime Kuma: Free, open source

Total software cost: $0/month

Compare this to equivalent cloud services, and the savings are substantial while maintaining full control over our data and infrastructure.

Lessons Learned and Recommendations

1. Start Small, Scale Gradually

Don't try to deploy everything at once. Start with one or two core applications and add others as you identify specific needs.

2. Monitor Resource Usage

Use CasaOS's monitoring to understand which applications consume the most resources. This helps with optimization and capacity planning.

3. Document Everything

Keep detailed notes on configurations, integrations, and customizations. This documentation becomes invaluable during troubleshooting or migrations.

4. Plan for Failure

Critical applications should have backup strategies and failover plans. Test these regularly to ensure they work when needed.

5. Embrace the Community

The open-source communities around these applications are incredible resources. Don't hesitate to ask questions or contribute back when you can.

What's Next?

We've covered the foundation of our HomeLab: hardware, networking, container management, and essential applications. In our final post of this series, we'll look ahead to future developments, advanced topics, and the roadmap for expanding our infrastructure.

We'll also discuss how to take these concepts and apply them to your own projects, whether you're building a personal HomeLab or implementing similar solutions for clients.

Have questions about specific application configurations, integration patterns, or deployment strategies? Drop us a line – the beauty of HomeLab is in the experimentation and learning, and I'm always happy to share detailed configurations or troubleshooting tips.

Next up: "HomeLab Future: Advanced Topics and What's Coming Next"