app work in progress

. 𝗔 𝗩𝗶𝗱𝗲𝗼(𝘀𝘁𝗿𝗲𝗮𝗺𝗶𝗻𝗴) 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗱𝗲𝗽𝗹𝗼𝘆𝗲𝗱 𝗼𝗻 𝗖𝗹𝗼𝘂𝗱 Build a mini YouTube that’s it. You will be dealing with Encoding and Decoding the videos, dumping and picking the files from S3/GCS/Blob, use CDN for faster loading. Containerize the application and deploy it on AKS/GKE/EKS. Collect the metadata and store it in a KV store and stream the collected data to a data warehouse. Write Terraform code for the Infrastructure.

Video Encoding/Decoding: Use a library or service like FFmpeg or AWS Elemental MediaConvert for encoding and decoding videos. You can integrate this into your backend service.

1. Cloud Storage: Utilize Amazon S3, Google Cloud Storage (GCS), or Azure Blob Storage for storing video files. You'll need to upload videos to these storage services and retrieve them when requested.

2. Content Delivery Network (CDN): Set up a CDN like Amazon CloudFront, Google Cloud CDN, or Azure CDN to cache and deliver video content to users with low latency.

3. Containerization: Dockerize your application to create a container image. You can use Dockerfile to define the container configuration.

4. Deployment: Deploy your containerized application on managed Kubernetes services like Azure Kubernetes Service (AKS), Google Kubernetes Engine (GKE), or Amazon Elastic Kubernetes Service (EKS).

5. Metadata Collection: Collect metadata such as video title, description, upload date, etc., and store it in a key-value store like Redis or DynamoDB.

6. Streaming Data to Data Warehouse: Stream the collected metadata to a data warehouse like Amazon Redshift, Google BigQuery, or Azure Synapse Analytics for analysis and reporting.

7. Terraform Infrastructure as Code: Write Terraform code to provision and manage the infrastructure components including cloud storage, CDN, Kubernetes cluster, key-value store, and data warehouse.

Here's a simplified Terraform configuration for creating AWS infrastructure components:

terraformCopy code# Define provider
provider "aws" {
  region = "us-west-2" # Specify your region
}

# Create S3 bucket
resource "aws_s3_bucket" "video_bucket" {
  bucket = "your-video-bucket-name"
  acl    = "private"
}

# Create CDN distribution
resource "aws_cloudfront_distribution" "cdn_distribution" {
  origin {
    domain_name = aws_s3_bucket.video_bucket.bucket_regional_domain_name
    origin_id   = aws_s3_bucket.video_bucket.id
  }

  enabled             = true
  is_ipv6_enabled     = true
  default_root_object = "index.html"
}

# Create Kubernetes cluster on EKS
resource "aws_eks_cluster" "my_cluster" {
  name     = "my-cluster"
  role_arn = aws_iam_role.eks_cluster_role.arn
  version  = "1.21"
}

# Create IAM role for EKS cluster
resource "aws_iam_role" "eks_cluster_role" {
  name = "eks-cluster-role"
  assume_role_policy = jsonencode({
    Version = "2012-10-17",
    Statement = [{
      Effect    = "Allow",
      Principal = {
        Service = "eks.amazonaws.com"
      },
      Action    = "sts:AssumeRole"
    }]
  })
}

# Create DynamoDB table for metadata storage
resource "aws_dynamodb_table" "metadata_table" {
  name           = "video_metadata"
  billing_mode   = "PAY_PER_REQUEST"
  hash_key       = "video_id"
  attribute {
    name = "video_id"
    type = "S"
  }
}

# Output resources
output "s3_bucket_name" {
  value = aws_s3_bucket.video_bucket.bucket
}

output "cdn_domain_name" {
  value = aws_cloudfront_distribution.cdn_distribution.domain_name
}

output "eks_cluster_name" {
  value = aws_eks_cluster.my_cluster.name
}

output "dynamodb_table_name" {
  value = aws_dynamodb_table.metadata_table.name
}
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This Terraform configuration sets up an S3 bucket for storing videos, creates a CloudFront distribution for CDN, provisions an EKS cluster, and creates a DynamoDB table for metadata storage.

You would need to adjust the configuration based on your specific requirements and cloud provider (AWS, Google Cloud, or Azure). Additionally, you'll need to implement backend logic in your application for encoding/decoding videos, managing metadata, and streaming data to the data warehouse.

what should be my first step guide me

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Your first step should be to outline and design the architecture of your mini YouTube-like app. Here's a step-by-step guide to help you get started:

1. Define Requirements: Clearly define the features and functionalities you want in your app. Consider aspects like user authentication, video uploading, playback, search, comments, likes, and subscriptions.

2. Design Architecture: Sketch out the architecture of your application. Identify the components you'll need such as frontend, backend, database, cloud services, CDN, Kubernetes cluster, etc.

3. Choose Technologies: Select the appropriate technologies for each component based on your requirements and expertise. For example:

   • Backend: Node.js, Python (Django or Flask), Java (Spring Boot), etc.

   • Database: PostgreSQL, MongoDB, DynamoDB, etc.

   • Cloud Services: AWS, Google Cloud Platform, Azure.

   • Containerization: Docker.

   • Kubernetes: AKS, GKE, EKS.

   • CDN: CloudFront, Google Cloud CDN, Azure CDN.

4. Set Up Development Environment: Install necessary tools and set up your development environment. This may include IDEs, Docker, Kubernetes CLI, Terraform, etc.

5. Create Project Structure: Set up the directory structure for your project and initialize version control (e.g., Git) to manage your codebase.

6. Implement Backend: Start by building the backend of your application. Implement functionalities such as user authentication, video uploading, and basic CRUD operations for managing videos and metadata.

7. Integrate Cloud Services: Set up accounts on your chosen cloud provider(s) and configure services like S3/GCS/Blob storage for video storage, CDN for content delivery, and Kubernetes cluster for deployment.

8. Implement Frontend: Develop the frontend of your application using frameworks like React.js, Angular, or Vue.js. Implement features for browsing videos, video playback, user authentication, etc.

9. Containerize Application: Dockerize your application by writing Dockerfiles for the frontend and backend components. This involves defining the dependencies and runtime environment for each component.

10. Deploy to Kubernetes: Use Terraform to define infrastructure as code (IaC) for provisioning Kubernetes resources such as deployments, services, and ingresses. Deploy your containerized application to the Kubernetes cluster.

11. Implement Metadata Collection: Develop functionality to collect metadata from user interactions (e.g., video views, likes, comments) and store it in a key-value store (e.g., Redis) or a database (e.g., DynamoDB).

12. Stream Data to Data Warehouse: Set up streaming of metadata to a data warehouse using services like Amazon Kinesis, Google Cloud Pub/Sub, or Azure Event Hubs. Implement data pipelines to ingest, transform, and analyze the streaming data.

13. Testing: Write unit tests, integration tests, and end-to-end tests to ensure the reliability and functionality of your application.

14. Monitoring and Scaling: Implement monitoring and logging using tools like Prometheus, Grafana, and ELK stack. Set up autoscaling policies to dynamically scale your application based on demand.

15. Security: Implement security best practices such as HTTPS for secure communication, encryption for data at rest and in transit, and access controls for managing user permissions.

16. Documentation: Document your architecture, deployment process, API endpoints, and any other relevant information to facilitate maintenance and future development.

By following these steps, you'll be able to systematically build and deploy your mini YouTube-like app while ensuring scalability, reliability, and maintainability.