Running the Service with Docker

This guide will walk you through the steps to build and run the service using Docker.

Step 1: Build the Docker Image

To build the Docker image for the service, run the following command:

docker build -t yourapp .

This command will build the Docker image with the tag yourapp.

Step 2: Run the Docker Container

Once the image is built, you can run the container with the following command:

docker run -p 8080:8080 -e PORT=8080 -e DATABASE_URL="mongodb connection string" yourapp

Explanation of the flags:

• -p 8080:8080: Maps port 8080 on your local machine to port 8080 in the container.
• -e PORT=8080: Sets the PORT environment variable inside the container to 8080.
• -e DATABASE_URL="mongodb connection string": Sets the DATABASE_URL environment variable with your MongoDB connection string.

Multi-Stage Build for Production

This setup uses a multi-stage build to optimize the Docker image for production. The multi-stage build helps keep the final image size smaller by excluding unnecessary build dependencies.

Deployment Strategies

1. Containerizing the Entire Application on EC2

   • Pros: Simple setup, consistent environment, easy to scale.
   • Cons: Resources are always allocated (long running process), even for lightweight background tasks, leading to higher costs. Any failure impacts the entire application.

2. Using Kubernetes with a Cron Resource

   • Pros: Scalable, robust, and ideal for managing complex workloads.
   • Cons: Overhead of setting up and managing Kubernetes for a lightweight job. Higher costs and complexity for small-scale tasks.

3. My Approach: Splitting into Two Services

   • HTTP Service: Handles API requests, containerized and deployed on EC2 (If serving verr high traffic) otherwise lambda.
   • Background Job: AWS Lambda fetches data from CoinGecko and updates the database. EventBridge invokes the Lambda every 2 hours.

   Pros:

   • Cost-efficient: Lambda runs only when needed.
   • Resilient: HTTP service and background job are independent, ensuring no downtime if one fails.
   • Simplified setup for lightweight background tasks. Cons: Limited control over serverless environments and potential latency in Lambda cold starts.

This approach balances cost, reliability, and scalability, making it ideal for current needs.

Currently due to resource and time constraints i have dockerised the http server part and deployed it as a container on Render.

Docker Image: https://hub.docker.com/r/prajjwaljson200/koinx

Koinx API Endpoints

1. Health Check

• URL: https://koinx-c52s.onrender.com
• Method: GET
• Description: This endpoint checks the health of the server and ensures it is running properly.

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2. Coin Stats

• URL: https://koinx-c52s.onrender.com/coins/stats?coin=<coin_name>

• Method: GET

• Query Parameters:

  • coin (required): The name of the cryptocurrency (e.g., bitcoin, ethereum).

• Response Example:

  {
    "price": 94384,
    "marketCap": 1869291548664.941,
    "24hChange": 0.6255164736666748
  }
  

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3. Coin Deviation

• URL: `https://koinx-c52s.onrender.com/coins/deviation?coin=<coin_name>``

• Method: GET

• Query Parameters: coin (required): The name of the cryptocurrency (e.g., bitcoin, ethereum). Response Example:

{
  "deviation": 74.72073005531999
}

Description: This endpoint calculates the price deviation of the specified coin.