some work on sound anf noise suppression and research into netdata

2025-06-19 21:15:24 +02:00 · 2025-06-19 21:15:24 +02:00 · 076c38d829
commit 076c38d829
parent bc3d199cca
4 changed files with 626 additions and 3 deletions
--- a/dotfiles/README.md
+++ b/dotfiles/README.md
@ -5,7 +5,9 @@ This directory contains per-user configurations and dotfiles for the Home-lab in
 ## Directory Organization

 ### `geir/`
+
 Primary user configuration for geir:
+
 - `user.nix` - NixOS user configuration (packages, groups, shell)
 - `dotfiles/` - Literate programming dotfiles using org-mode
  - `README.org` - Main literate configuration file
@ -14,7 +16,9 @@ Primary user configuration for geir:
  - `editors/` - Editor configurations (neovim, vscode)

 ### Future Users
+
 Additional user directories will follow the same pattern:
+
 - `admin/` - Administrative user for system management
 - `service/` - Service accounts for automation
 - `guest/` - Temporary/guest user configurations
@ -22,21 +26,27 @@ Additional user directories will follow the same pattern:
 ## User Configuration Philosophy

 ### NixOS Integration
+
 Each user has a `user.nix` file that defines:
+
 - User account settings (shell, groups, home directory)
 - User-specific packages
 - System-level user configurations
 - Integration with home lab services

 ### Literate Dotfiles
+
 Each user's `dotfiles/README.org` serves as:
+
 - Single source of truth for all user configurations
 - Self-documenting setup with rationale
 - Auto-tangling to generate actual dotfiles
 - Version-controlled configuration history

 ### Multi-Machine Consistency
+
 User configurations are designed to work across machines:
+
 - congenital-optimist: Full development environment
 - sleeper-service: Minimal server access
 - Future machines: Consistent user experience
@ -44,7 +54,9 @@ User configurations are designed to work across machines:
 ## Dotfiles Structure

 ### `dotfiles/README.org`
+
 Main literate configuration file containing:
+
 - Shell configuration (zsh, starship, aliases)
 - Editor configurations (emacs, neovim)
 - Development tool settings
@ -52,6 +64,7 @@ Main literate configuration file containing:
 - Machine-specific customizations

 ### Subdirectories
+
 - `emacs/` - Generated Emacs configuration files
 - `shell/` - Generated shell configuration files
 - `editors/` - Generated editor configuration files
@ -59,6 +72,7 @@ Main literate configuration file containing:
 ## Usage Examples

 ### Importing User Configuration
+
 ```nix
 # In machine configuration
 imports = [
@ -67,12 +81,14 @@ imports = [
 ```

 ### Adding New User
+
 1. Create user directory: `users/newuser/`
 2. Copy and adapt `user.nix` template
 3. Create `dotfiles/README.org` with user-specific configs
 4. Import in machine configurations as needed

 ### Tangling Dotfiles
+
 ```bash
 # From user's dotfiles directory
 cd users/geir/dotfiles
--- a/research/netdata-home-lab-research.md
+++ b/research/netdata-home-lab-research.md
@ -0,0 +1,607 @@
+# Netdata Research: Metrics Aggregation for Home Lab
+
+*Research conducted June 19, 2025*
+
+## Executive Summary
+
+Netdata is a highly viable metrics aggregation solution for your home lab infrastructure. It offers real-time monitoring with per-second granularity, minimal resource usage, and excellent scalability through its Parent-Child architecture. The recent addition of a beta MCP (Model Context Protocol) server makes it particularly interesting for integration with AI tooling and your existing workflow.
+
+## Key Advantages for Home Lab Use
+
+### 1. **Real-Time Monitoring Excellence**
+
+- **Per-second metrics collection** - True real-time visibility
+- **1-second dashboard latency** - Instant feedback for troubleshooting
+- **Zero sampling** - Complete data fidelity
+- **800+ integrations** out of the box
+
+### 2. **Resource Efficiency**
+
+- **Most energy-efficient monitoring tool** according to University of Amsterdam study
+- **40x better storage efficiency** compared to traditional solutions
+- **22x faster responses** than alternatives
+- **Uses only 15% of resources** compared to similar tools
+
+### 3. **Perfect Home Lab Architecture**
+
+- **Zero-configuration deployment** - Auto-discovers services
+- **Distributed by design** - No centralized data collection required
+- **Edge-based ML** - Anomaly detection runs locally on each node
+- **Parent-Child streaming** - Centralize dashboards while keeping data local
+
+### 4. **Advanced Features**
+
+- **Built-in ML anomaly detection** - One model per metric, trained locally
+- **Pre-configured alerts** - 400+ ready-to-use alert templates
+- **Multiple notification channels** - Slack, Discord, email, PagerDuty, etc.
+- **Export capabilities** - Prometheus, InfluxDB, Graphite integration
+
+## Architecture Options for Home Lab
+
+### Option 1: Standalone Deployment (Simple)
+
+```
+┌─────────────────┐  ┌─────────────────┐  ┌─────────────────┐
+│   Machine 1     │  │   Machine 2     │  │   Machine N     │
+│  (Netdata       │  │  (Netdata       │  │  (Netdata       │
+│   Agent)        │  │   Agent)        │  │   Agent)        │
+└─────────────────┘  └─────────────────┘  └─────────────────┘
+         │                     │                     │
+         └─────────────────────┼─────────────────────┘
+                               │
+                    ┌─────────────────┐
+                    │ Netdata Cloud   │
+                    │  (Optional)     │
+                    └─────────────────┘
+```
+
+**Benefits:**
+
+- Simple setup and maintenance
+- Each node retains its own data
+- No single point of failure
+- Perfect for learning and small deployments
+
+### Option 2: Parent-Child Architecture (Recommended)
+
+```
+                    ┌─────────────────┐
+                    │ Netdata Parent  │
+                    │ (Central Hub)   │
+                    │ - Dashboards    │
+                    │ - Long retention│
+                    │ - Alerts        │
+                    └─────────────────┘
+                             │
+              ┌──────────────┼──────────────┐
+              │              │              │
+    ┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
+    │ Netdata Child  │ │ Netdata Child  │ │ Netdata Child  │
+    │ (NixOS VMs)    │ │ (Containers)   │ │ (IoT devices)   │
+    │ - Thin mode    │ │ - Thin mode    │ │ - Thin mode     │
+    │ - Local buffer │ │ - Local buffer │ │ - Local buffer  │
+    └─────────────────┘ └─────────────────┘ └─────────────────┘
+```
+
+**Benefits:**
+
+- Centralized dashboards and alerting
+- Extended retention on Parent node
+- Reduced resource usage on Child nodes
+- Better for production-like home lab setups
+
+### Option 3: High Availability Cluster (Advanced)
+
+```
+    ┌─────────────────┐     ┌─────────────────┐
+    │ Netdata Parent 1│◄───►│ Netdata Parent 2│
+    │ (Primary)       │     │ (Backup)        │
+    └─────────────────┘     └─────────────────┘
+             │                       │
+    ┌────────┼───────────────────────┼────────┐
+    │        │                       │        │
+┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐
+│Child 1  │ │Child 2  │ │Child 3  │ │Child N  │
+└─────────┘ └─────────┘ └─────────┘ └─────────┘
+```
+
+**Benefits:**
+
+- No single point of failure
+- Automatic failover
+- Load distribution
+- Production-grade reliability
+
+## Integration with Your NixOS Infrastructure
+
+### NixOS Configuration
+
+```nix
+# In your NixOS configuration.nix
+{
+  services.netdata = {
+    enable = true;
+    config = {
+      global = {
+        "default port" = "19999";
+        "memory mode" = "ram";  # For children
+        # "memory mode" = "save"; # For parents
+      };
+      
+      # For Parent nodes
+      streaming = {
+        enabled = "yes";
+        "allow from" = "*";
+        "default memory mode" = "ram";
+      };
+      
+      # For Child nodes  
+      stream = {
+        enabled = "yes";
+        destination = "parent.yourdomain.local";
+        "api key" = "your-api-key";
+      };
+    };
+  };
+  
+  # Open firewall for Netdata
+  networking.firewall.allowedTCPPorts = [ 19999 ];
+}
+```
+
+### Deployment Strategy for Your Lab
+
+1. **Reverse Proxy** (grey-area): Netdata Parent + Nginx reverse proxy
+2. **Sleeper Service** (NFS): Netdata Child with storage monitoring
+3. **Congenital Optimist**: Netdata Child with system monitoring
+4. **VM workloads**: Netdata Children in thin mode
+
+## MCP Server Integration (Beta Feature)
+
+Netdata recently introduced an **MCP (Model Context Protocol) server in beta**. This is particularly relevant for your AI-integrated workflow:
+
+### What It Offers
+
+- **AI-powered metric analysis** through standardized MCP interface
+- **Integration with Claude, ChatGPT, and other LLMs** for intelligent monitoring
+- **Natural language queries** about your infrastructure metrics
+- **Automated root cause analysis** using AI reasoning
+- **Contextual alerting** with AI-generated insights
+
+### Potential Use Cases
+
+```bash
+# Example MCP interactions (conceptual)
+"What's causing high CPU on sleeper-service?"
+"Show me network anomalies from the last hour"
+"Compare current metrics to last week's baseline"
+"Generate a performance report for grey-area"
+```
+
+### Integration with Your Existing MCP Setup
+
+Since you're already using MCP servers (TaskMaster, Context7), adding Netdata's MCP server would create a powerful monitoring-AI pipeline:
+
+```
+Your Infrastructure → Netdata → MCP Server → AI Analysis → Insights
+```
+
+## Comparison with Alternatives
+
+### vs. Prometheus + Grafana
+
+| Feature | Netdata | Prometheus + Grafana |
+|---------|---------|---------------------|
+| Setup Complexity | Zero-config | Complex setup |
+| Real-time Data | 1-second | 15-second minimum |
+| Resource Usage | Very low | Higher |
+| Built-in ML | Yes | No |
+| Dashboards | Auto-generated | Manual creation |
+| Storage Efficiency | 40x better | Standard |
+
+### vs. Zabbix
+
+| Feature | Netdata | Zabbix |
+|---------|---------|---------|
+| Agent Overhead | Minimal | Higher |
+| Configuration | Auto-discovery | Manual setup |
+| Scalability | Horizontal | Vertical |
+| Modern UI | Yes | Traditional |
+| Cloud Integration | Native | Limited |
+
+### vs. DataDog/Commercial SaaS
+
+| Feature | Netdata | Commercial SaaS |
+|---------|---------|-----------------|
+| Cost | Open Source | Expensive |
+| Data Sovereignty | Local | Vendor-hosted |
+| Customization | Full control | Limited |
+| Lock-in Risk | None | High |
+
+## Implementation Roadmap
+
+### Phase 1: Basic Deployment (Week 1)
+
+1. Deploy Netdata Parent on **grey-area**
+2. Install Netdata Children on main nodes
+3. Configure basic streaming
+4. Set up reverse proxy for external access
+
+### Phase 2: Integration (Week 2-3)
+
+1. Configure alerts and notifications
+2. Set up Prometheus export for existing tools
+3. Integrate with your existing monitoring stack
+4. Configure retention policies
+
+### Phase 3: Advanced Features (Week 4+)
+
+1. Enable MCP server (beta)
+2. Set up high availability if needed
+3. Custom dashboard creation
+4. Advanced alert tuning
+
+## Potential Challenges
+
+### 1. **Learning Curve**
+
+- New terminology (Parent/Child vs traditional)
+- Different approach to metrics storage
+- **Mitigation**: Excellent documentation and active community
+
+### 2. **Beta MCP Server**
+
+- Still in beta development
+- Limited documentation
+- **Mitigation**: Conservative adoption, wait for stability
+
+### 3. **Integration Complexity**
+
+- May need adaptation of existing monitoring workflows
+- **Mitigation**: Gradual migration, parallel running during transition
+
+## Resource Requirements
+
+### Minimal Setup (Per Node)
+
+- **CPU**: 1-2% of a single core
+- **RAM**: 20-100MB depending on metrics count
+- **Disk**: 100MB for agent + retention data
+- **Network**: Minimal bandwidth for streaming
+
+### Parent Node (Centralized)
+
+- **CPU**: 2-4 cores for 10-20 children
+- **RAM**: 2-4GB for extended retention
+- **Disk**: 10-50GB depending on retention period
+- **Network**: Higher bandwidth for ingesting streams
+
+## Recommendations
+
+### For Your Home Lab: **Strong Yes**
+
+1. **Start with Parent-Child architecture** on grey-area as Parent
+2. **Deploy gradually** - begin with critical nodes
+3. **Integrate with existing Prometheus** via export
+4. **Monitor MCP server development** for AI integration
+5. **Consider as primary monitoring solution** due to superior efficiency
+
+### Specific Benefits for Your Use Case
+
+- **Perfect fit for NixOS** - declarative configuration
+- **Complements your AI workflow** - MCP integration potential  
+- **Scales with lab growth** - from single nodes to complex topologies
+- **Energy efficient** - important for home lab power consumption
+- **Real-time visibility** - excellent for development and testing
+
+## Next Steps
+
+1. **Proof of Concept**: Deploy on grey-area as standalone
+2. **Evaluate**: Run for 1-2 weeks alongside current monitoring
+3. **Expand**: Add children nodes if satisfied
+4. **Integrate**: Connect with existing toolchain
+5. **MCP Beta**: Request early access to MCP server
+
+## Conclusion
+
+Netdata represents a modern, efficient approach to infrastructure monitoring that aligns well with your home lab's goals. Its combination of real-time capabilities, minimal resource usage, and emerging AI integration through MCP makes it an excellent choice for sophisticated home lab environments. The Parent-Child architecture provides enterprise-grade capabilities while maintaining the simplicity needed for home lab management.
+
+The addition of MCP server support positions Netdata at the forefront of AI-integrated monitoring, making it particularly appealing given your existing investment in MCP-based tooling.
+
+## References
+
+- [Netdata GitHub Repository](https://github.com/netdata/netdata)
+- [Netdata Documentation](https://learn.netdata.cloud/)
+- [University of Amsterdam Energy Efficiency Study](https://www.ivanomalavolta.com/files/papers/ICSOC_2023.pdf)
+- [Netdata vs Prometheus Comparison](https://www.netdata.cloud/blog/netdata-vs-prometheus-2025/)
+- [Netdata MCP Server Documentation](https://github.com/netdata/netdata/blob/master/docs/mcp.md) (Beta)
+
+## Netdata API for Custom Web Dashboards
+
+Netdata provides a comprehensive REST API that makes it perfect for integrating with custom web dashboards. The API is exposed locally on each Netdata agent and can be used to fetch real-time metrics in various formats.
+
+### API Overview
+
+**Base URL**: `http://localhost:19999/api/v1/`
+
+**Primary Endpoints**:
+- `/api/v1/data` - Query time-series data
+- `/api/v1/charts` - Get available charts
+- `/api/v1/allmetrics` - Get all metrics in shell-friendly format
+- `/api/v1/badge.svg` - Generate SVG badges
+
+### Key API Features for Dashboard Integration
+
+1. **Multiple Output Formats**
+   - JSON (default)
+   - CSV
+   - TSV
+   - JSONP
+   - Plain text
+   - Shell variables
+
+2. **Real-Time Data Access**
+   - Per-second granularity
+   - Live streaming capabilities
+   - Historical data queries
+
+3. **Flexible Query Parameters**
+   - Time range selection
+   - Data grouping and aggregation
+   - Dimension filtering
+   - Custom sampling intervals
+
+### API Query Examples
+
+#### Basic Data Query
+```bash
+# Get CPU system data for the last 60 seconds
+curl "http://localhost:19999/api/v1/data?chart=system.cpu&after=-60&dimensions=system"
+
+# Response format:
+{
+  "api": 1,
+  "id": "system.cpu",
+  "name": "system.cpu",
+  "update_every": 1,
+  "first_entry": 1640995200,
+  "last_entry": 1640995260,
+  "before": 1640995260,
+  "after": 1640995200,
+  "dimension_names": ["guest_nice", "guest", "steal", "softirq", "irq", "system", "user", "nice", "iowait"],
+  "dimension_ids": ["guest_nice", "guest", "steal", "softirq", "irq", "system", "user", "nice", "iowait"],
+  "latest_values": [0, 0, 0, 0.502513, 0, 2.512563, 5.025126, 0, 0.502513],
+  "view_update_every": 1,
+  "dimensions": 9,
+  "points": 61,
+  "format": "json",
+  "result": {
+    "data": [
+      [1640995201, 0, 0, 0, 0.0025, 0, 0.0125, 0.025, 0, 0.0025],
+      [1640995202, 0, 0, 0, 0.005, 0, 0.0275, 0.0525, 0, 0.005]
+      // ... more data points
+    ]
+  }
+}
+```
+
+#### Available Charts Discovery
+```bash
+# Get all available charts
+curl "http://localhost:19999/api/v1/charts"
+
+# Returns JSON with all chart definitions including:
+# - Chart IDs and names
+# - Available dimensions
+# - Update frequencies
+# - Chart types and units
+```
+
+#### Memory Usage Example
+```bash
+# Get memory usage data with specific grouping
+curl "http://localhost:19999/api/v1/data?chart=system.ram&after=-300&points=60&group=average"
+```
+
+#### Network Interface Metrics
+```bash
+# Get network traffic for specific interface
+curl "http://localhost:19999/api/v1/data?chart=net.eth0&after=-60&dimensions=received,sent"
+```
+
+#### All Metrics in Shell Format
+```bash
+# Perfect for scripting and automation
+curl "http://localhost:19999/api/v1/allmetrics"
+
+# Example output:
+NETDATA_SYSTEM_CPU_USER=2.5
+NETDATA_SYSTEM_CPU_SYSTEM=1.2
+NETDATA_SYSTEM_RAM_USED=4096
+# ... all metrics as shell variables
+```
+
+### Advanced Query Parameters
+
+| Parameter | Description | Example |
+|-----------|-------------|---------|
+| `chart` | Chart ID to query | `system.cpu` |
+| `after` | Start time (unix timestamp or relative) | `-60` (60 seconds ago) |
+| `before` | End time (unix timestamp or relative) | `-30` (30 seconds ago) |
+| `points` | Number of data points to return | `100` |
+| `group` | Grouping method | `average`, `max`, `min`, `sum` |
+| `gtime` | Group time in seconds | `60` (1-minute averages) |
+| `dimensions` | Specific dimensions to include | `user,system,iowait` |
+| `format` | Output format | `json`, `csv`, `jsonp` |
+| `options` | Query options | `unaligned`, `percentage` |
+
+### Web Dashboard Integration Strategies
+
+#### 1. Direct AJAX Calls
+```javascript
+// Fetch CPU data for dashboard widget
+fetch('http://localhost:19999/api/v1/data?chart=system.cpu&after=-60&points=60')
+  .then(response => response.json())
+  .then(data => {
+    // Process data for chart library (Chart.js, D3, etc.)
+    updateCPUChart(data.result.data);
+  });
+```
+
+#### 2. Server-Side Proxy
+```javascript
+// Proxy through your web server to avoid CORS issues
+fetch('/api/netdata/system.cpu?after=-60')
+  .then(response => response.json())
+  .then(data => updateWidget(data));
+```
+
+#### 3. Real-Time Updates
+```javascript
+// Poll for updates every second
+setInterval(() => {
+  fetch('http://localhost:19999/api/v1/data?chart=system.cpu&after=-1&points=1')
+    .then(response => response.json())
+    .then(data => updateRealTimeMetrics(data));
+}, 1000);
+```
+
+### Custom Dashboard Implementation Example
+
+```html
+<!DOCTYPE html>
+<html>
+<head>
+    <title>Home Lab Dashboard</title>
+    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
+</head>
+<body>
+    <div class="dashboard">
+        <div class="widget">
+            <canvas id="cpuChart"></canvas>
+        </div>
+        <div class="widget">
+            <canvas id="memoryChart"></canvas>
+        </div>
+        <div class="widget">
+            <canvas id="networkChart"></canvas>
+        </div>
+    </div>
+
+    <script>
+        class NetdataDashboard {
+            constructor() {
+                this.baseUrl = 'http://localhost:19999/api/v1';
+                this.charts = {};
+                this.initCharts();
+                this.startPolling();
+            }
+
+            async fetchData(chart, timeRange = '-60') {
+                const response = await fetch(`${this.baseUrl}/data?chart=${chart}&after=${timeRange}&points=60`);
+                return response.json();
+            }
+
+            initCharts() {
+                // Initialize Chart.js charts
+                this.charts.cpu = new Chart(document.getElementById('cpuChart'), {
+                    type: 'line',
+                    data: { datasets: [] },
+                    options: { responsive: true }
+                });
+                // ... other charts
+            }
+
+            async updateCPU() {
+                const data = await this.fetchData('system.cpu');
+                // Update chart with new data
+                this.charts.cpu.data.datasets = this.processNetdataForChart(data);
+                this.charts.cpu.update();
+            }
+
+            startPolling() {
+                setInterval(() => {
+                    this.updateCPU();
+                    this.updateMemory();
+                    this.updateNetwork();
+                }, 1000);
+            }
+        }
+
+        const dashboard = new NetdataDashboard();
+    </script>
+</body>
+</html>
+```
+
+### Integration Considerations
+
+#### 1. **CORS Handling**
+- Netdata allows cross-origin requests by default
+- For production, consider proxying through your web server
+- Use server-side API calls for sensitive environments
+
+#### 2. **Performance Optimization**
+- Cache frequently accessed chart definitions
+- Use appropriate `points` parameter to limit data transfer
+- Implement efficient polling strategies
+- Consider WebSocket connections for real-time updates
+
+#### 3. **Data Processing**
+- Netdata returns timestamps and values as arrays
+- Convert to your chart library's expected format
+- Handle missing data points gracefully
+- Implement data aggregation for longer time ranges
+
+#### 4. **Error Handling**
+```javascript
+async function safeNetdataFetch(endpoint) {
+    try {
+        const response = await fetch(endpoint);
+        if (!response.ok) throw new Error(`HTTP ${response.status}`);
+        return await response.json();
+    } catch (error) {
+        console.error('Netdata API error:', error);
+        return null;
+    }
+}
+```
+
+### Multi-Node Dashboard
+
+For Parent-Child deployments, you can create a unified dashboard:
+
+```javascript
+class MultiNodeDashboard {
+    constructor(nodes) {
+        this.nodes = nodes; // [{ name: 'server1', url: 'http://server1:19999' }, ...]
+    }
+
+    async fetchFromAllNodes(chart) {
+        const promises = this.nodes.map(async node => {
+            const data = await fetch(`${node.url}/api/v1/data?chart=${chart}&after=-60`);
+            return { node: node.name, data: await data.json() };
+        });
+        return Promise.all(promises);
+    }
+}
+```
+
+### API Documentation Resources
+
+- **Swagger Documentation**: https://learn.netdata.cloud/api
+- **OpenAPI Spec**: https://raw.githubusercontent.com/netdata/netdata/master/src/web/api/netdata-swagger.yaml
+- **Query Documentation**: https://learn.netdata.cloud/docs/developer-and-contributor-corner/rest-api/queries/
+
+### Conclusion
+
+Netdata's REST API provides excellent capabilities for custom web dashboard integration:
+
+✅ **Real-time data access** with sub-second latency
+✅ **Multiple output formats** including JSON and CSV
+✅ **Flexible query parameters** for precise data selection
+✅ **No authentication required** for local access
+✅ **CORS-friendly** for web applications
+✅ **Well-documented** with OpenAPI specification
+
+The API is production-ready and provides all the data access patterns needed for sophisticated custom dashboards, making it an excellent choice for integrating Netdata metrics into your existing home lab web interfaces.