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VIDEO_SYSTEM_IMPLEMENTATION.md

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Video System Implementation Summary

Overview

A robust video processing and streaming architecture has been implemented to support high-quality educational content delivery. This system handles the entire lifecycle of video content from upload to adaptive streaming.

Key Components

1. Data Models (src/video/entities/)

  • Video: Core entity tracking metadata, status, and ownership.
  • VideoVariant: Stores different quality versions (1080p, 720p) and formats (HLS, MP4).
  • VideoAnalytics: Tracks engagement metrics like views, watch time, and retention.

2. Services (src/video/services/)

  • VideoService: Orchestrates CRUD operations and manages the video lifecycle.
  • TranscodingService:
    • Simulates ffmpeg processing pipeline.
    • Handles status transitions (PENDING -> PROCESSING -> READY).
    • Generates mock assets (thumbnails, previews).
  • StreamingService:
    • Generates HLS manifest URLs.
    • Implements URL signing logic for secure playback.

3. API Layer (src/video/controllers/)

  • VideoController: RESTful endpoints for managing video resources.
  • StreamingController: Specialized endpoints for delivering video streams.

Features Implemented

✅ Video Upload: Multipart form-data support for video files. ✅ Asynchronous Processing: Non-blocking transcoding workflow. ✅ Adaptive Streaming: Architecture ready for HLS/DASH delivery. ✅ Analytics Ready: Schema designed for deep engagement tracking. ✅ Security: Visibility controls (Public/Private/Unlisted) and signed URL logic.

API Reference

Upload Video

POST /api/videos
Content-Type: multipart/form-data

file: [video_file]
title: "Introduction to Blockchain"
visibility: "PRIVATE"

Get Stream

GET /api/stream/{videoId}/manifest.m3u8

Future Enhancements

  1. FFmpeg Integration: Replace the mock TranscodingService with actual fluent-ffmpeg implementation or AWS MediaConvert integration.
  2. Storage Provider: Implement S3/Cloudinary storage strategy for physical files.
  3. Webhooks: Add webhook support for external transcoding services.
  4. Live Streaming: Add support for RTMP ingestion and HLS live output.

Database Schema

CREATE TABLE videos (
  id UUID PRIMARY KEY,
  title VARCHAR NOT NULL,
  status VARCHAR DEFAULT 'PENDING',
  visibility VARCHAR DEFAULT 'PRIVATE',
  ...
);

CREATE TABLE video_variants (
  id UUID PRIMARY KEY,
  video_id UUID REFERENCES videos(id),
  resolution VARCHAR,
  url VARCHAR,
  ...
);

Testing

The system is designed with dependency injection to allow easy mocking of the transcoding and storage layers during testing.

Status: ✅ Core Architecture Complete Next Steps: Configure storage provider and install ffmpeg binaries in production environment.