Multi-Resolution-Transcoder-Pipeline | Mux

A scalable video transcoding pipeline designed to convert videos into multiple resolutions, leveraging Azure's powerful cloud services. This project is inspired by Mux and demonstrates how to build a video processing pipeline that can be easily scaled to handle large volumes of videos.

Table of Contents

• Overview
• Tech Stack
• Azure Services Used
• Pipeline Workflow
• Setup and Installation
• Usage
• Contributing
• License

Overview

This project automates the process of transcoding videos into multiple resolutions using Azure services. The pipeline downloads a video from Azure Blob Storage, transcodes it into different resolutions (360p, 480p, 720p), and uploads the transcoded videos back to Azure Blob Storage with a suffix indicating the resolution. This allows for easy selection of videos based on desired resolution.

Why settle for one resolution when you can have them all? Transcode like a ninja!✨

Tech Stack

• Node.js: The runtime environment used to execute JavaScript code on the server side.
• TypeScript: Superset of JavaScript used for type safety and improved developer experience.
• Fluent-ffmpeg: A Node.js library for working with FFmpeg, used here for video transcoding.
• Azure SDK for JavaScript: Used for interacting with various Azure services.

Azure Services Used

1. Azure Blob Storage

• Purpose: Used for storing the original video files and the transcoded videos.
• Role: The pipeline retrieves the input video from a specified container, processes it, and stores the output videos back in another container.

2. Azure Storage Queue

• Purpose: Used for queuing video processing requests.
• Role: The pipeline listens to the queue, retrieves messages, and processes videos accordingly. This allows for asynchronous processing and easy scaling.

3. Azure Container Instances

• Purpose: Provides a platform for running the containerized video transcoding service.
• Role: The pipeline spins up containers on demand to handle video transcoding, ensuring that resources are used efficiently.

4. Azure Container Registry

• Purpose: Stores container images.
• Role: The pipeline pulls the Docker image from the registry to spin up container instances for video processing.

Pipeline Workflow

1. Message Queue: The pipeline starts by receiving a message from an Azure Storage Queue, which contains the name of the video blob to be processed.

2. Video Download: The pipeline downloads the video from Azure Blob Storage.

3. Video Transcoding: The video is transcoded into multiple resolutions using fluent-ffmpeg.

4. Video Upload: The transcoded videos are uploaded back to Azure Blob Storage with filenames that include the resolution suffix (e.g., video-360p.mp4).

5. Repeat: The pipeline continues to listen to the queue for new messages, allowing for continuous processing.

Setup and Installation

Prerequisites

• Node.js and npm/yarn installed.
• Azure account with the following services set up:
  • Blob Storage containers (input and output)
  • Storage Queue
  • Container Registry with a Docker image for the transcoding service
  • Container Instance setup

Installation

1. Clone the repository:

   git clone https://github.com/VinayakVispute/Multi-Resolution-Transcoder-Pipeline-Mux.git
   cd Multi-Resolution-Transcoder-Pipeline-Mux

2. Install dependencies:

   npm install

3. Set up environment variables: Create a .env file in the root directory and populate it with the following values:

   AZURE_STORAGE_CONNECTION_STRING=your_connection_string
   AZURE_RESOURCE_GROUP=your_resource_group
   AZURE_CONTAINER_REGISTRY_SERVER=your_registry_server
   CONTAINER_GROUP_NAME=your_container_group_name
   CONTAINER_NAME=your_container_name
   BUCKET_NAME=input_blob_container_name
   OUTPUT_VIDEO_BUCKET=output_blob_container_name
   SUBSCRIPTION_ID=your_subscription_id
   ACR_USERNAME=your_acr_username
   ACR_PASSWORD=your_acr_password
   QUEUE_NAME=your_queue_name
   RESOURCE_GROUP_LOCATION=location_for_resource_group
   

4. Run the pipeline:

   npm start

Usage

• Input: The pipeline processes video files stored in an Azure Blob Storage container. The video file's name is extracted from a message received from an Azure Storage Queue.
• Output: The transcoded videos are stored in another Azure Blob Storage container with filenames suffixed with the resolution (e.g., video-360p.mp4, video-480p.mp4, video-720p.mp4).

Contributing

Contributions are welcome! Please fork this repository, create a feature branch, and submit a pull request for any enhancements or fixes.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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