A JavaScript runtime parses and executes JavaScript code outside the browser. In browser environments, the runtime includes APIs for DOM interaction, event handling, and UI operations. These runtimes do not support backend tasks. Node.js uses the V8 engine and a non-blocking I/O model to run JavaScript on servers without relying on a browser. Node.js: Server-Side JavaScript Runtime Node.js runs JavaScript outside the browser using the V8 engine. It connects with system-level APIs to perform networking, file I/O, and process management. It is used to build backend services, automation tasks, and command-line tools. Example: // Import core Node.js modules const http = require('http'); const fs = require('fs').promises; const path = require('path'); // Create an HTTP server const server = http.createServer(async (req, res) => { try { // Process management: Get CPU usage const startUsage = process.cpuUsage(); // Handle different routes if (req.url === '/') { // File I/O: Read HTML file const data = await fs.readFile( path.join(__dirname, 'public', 'index.html'), 'utf8' ); res.writeHead(200, { 'Content-Type': 'text/html' }); res.end(data); } else if (req.url === '/api/data') { // Networking: API endpoint res.writeHead(200, { 'Content-Type': 'application/json' }); res.end(JSON.stringify({ message: 'Hello from Node.js!', pid: process.pid, uptime: process.uptime(), cpuUsage: process.cpuUsage(startUsage) })); } else { res.writeHead(404); res.end('Not Found'); } } catch (err) { console.error('Server error:', err); res.writeHead(500); res.end('Internal Server Error'); } }); // Start the server const PORT = process.env.PORT || 3000; server.listen(PORT, () => { console.log(`Server running on port ${PORT}`); console.log(`Process ID: ${process.pid}`); console.log(`Platform: ${process.platform}`); }); // Demonstrate event loop with async operation setImmediate(() => { console.log('Event loop demo: setImmediate callback executed'); }); // File system watcher (demonstrating fs module) if (process.env.NODE_ENV === 'development') { fs.watch(path.join(__dirname, 'public')) .on('change', (eventType, filename) => { console.log(`File changed: ${filename} (${eventType})`); }); } Explanation: fs.promises enables non-blocking file operations using Promises (readFile, watch, etc.) path helps build file paths in a cross-platform-safe way. The callback receives req (request) and res (response) objects for handling HTTP traffic. Marked async to support await for asynchronous file I/O and system calls. For this to work completely, you'd want a public/index.html file: Node.js Demo

Node.js Runtime Demo

Explanation: Attaches a click event listener to the button using its id. Arrow function is declared async to handle asynchronous fetch operations. Sends a GET request to the /api/data endpoint. Returns a Response object containing the HTTP response from the server. Node.js Execution Model Node.js uses a non-blocking execution model built around asynchronous operations. V8 compiles JavaScript to machine code, and libuv manages system-level I/O. The event loop coordinates execution without blocking the main thread. Example const fs = require('fs'); fs.readFile('./data.txt', 'utf8', (err, data) => { if (err) throw err; console.log('File contents:', data); }); console.log('Reading file...'); Explanation : fs.readFile is non-blocking. The script continues execution and logs 'Reading file...'. When the file read completes, its callback is pushed to the queue and executed later. How Node.js Fits into Video Workflows Node.js integrates into video workflows by managing backend tasks such as encoding orchestration, metadata processing, and API routing. Its asynchronous I/O model supports concurrent video uploads, format conversions, and stream control without blocking execution. Manifest Generation and Video Metadata APIs Node.js is used to build APIs that serve video manifests (like HLS .m3u8 or DASH .mpd) dynamically based on user entitlements or session tokens. These APIs also handle metadata retrieval, license generation requests (for DRM), and secure playback initialization. app.get('/manifest/:videoId', async (req, res) => { const videoId = req.params.videoId; const manifest = await fetchManifest(videoId); res.setHeader('Content-Type', 'application/vnd.apple.mpegurl'); res.send(manifest); }); Explanation: app.get('/manifest/:videoId', ...) defines an HTTP GET route in an Express application. The path includes a route parameter :videoId, allowing clients to request different manifest files by ID. req.params.videoId extracts the videoId string from the URL. For example, a request to /manifest/abc123 sets videoId to 'abc123'. This API route could serve adaptive bitrate manifests after performing access control or token verification. Chunked Upload Handling for Video Ingest Node.js handles multipart uploads for large media files. It streams uploaded video chunks directly to cloud storage without buffering the entire file in memory. const stream = require('stream'); app.post('/upload', (req, res) => { const uploadStream = createS3Stream(); req.pipe(uploadStream).on('finish', () => res.end('Upload complete')); }); Explanation: const stream = require('stream') imports Node.js's core stream module. app.post('/upload', ...) defines an HTTP POST endpoint at /upload. createS3Stream() initializes a writable stream that connects to an object storage service like AWS S3, MinIO, or Backblaze B2. Real-Time Analytics for Video Sessions Node.js runs real-time analytics pipelines by listening to playback session events, forwarding logs to services like Kafka, and storing session heatmaps in a NoSQL store. Due to its non-blocking nature, it handles high throughput logging with low latency. Example: Capture and Forward Playback Events to Kafka // server.ts import express from 'express'; import { Kafka } from 'kafkajs'; const app = express(); app.use(express.json()); const kafka = new Kafka({ clientId: 'video-analytics', brokers: ['localhost:9092'] }); const producer = kafka.producer(); await producer.connect(); app.post('/analytics/event', async (req, res) => { const { sessionId, videoId, event, timestamp } = req.body; await producer.send({ topic: 'video-events', messages: [ { key: sessionId, value: JSON.stringify({ videoId, event, timestamp }), }, ], }); res.status(200).end(); }); Explanation: clientId: 'video-analytics' assigns a unique identifier to this Kafka client instance for tracking and logging within the Kafka cluster. brokers: ['localhost:9092'] specifies the Kafka broker address. Kafka producers connect here to publish messages.

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