Part 2: Automating Deployment with GitHub Actions and Docker

In Part 1 of our journey, we successfully set up a robust data pipeline between Paystack and Zoho CRM using Python scripts. Now, let's automate the deployment process using GitHub Actions and Docker to enhance our development workflow.

Setting Up GitHub Actions Workflow (workflow.yml)

GitHub Actions allow us to automate tasks such as testing and deployment directly from our repository. Here’s how to set up a workflow to deploy our Python application to Amazon ECR (Elastic Container Registry).

Step-by-Step Guide:

1. Create workflow.yml in Your Repository:

Create a .github/workflows/workflow.yml file in your project repository with the following content:

   name: Deploy to Amazon ECR

   on:
     push:
       branches:
         - main

   env:
     AWS_REGION: ${{ secrets.AWS_REGION }}
     IMAGE_TAG: ${{ github.sha }}
     ECR_REPOSITORY: paystacktozoho # Update with your ECR repository name

   jobs:
     deploy:
       name: Deploy to Amazon ECR
       runs-on: ubuntu-latest

       steps:
         - name: Checkout
           uses: actions/checkout@v3

         - name: Configure AWS credentials
           uses: aws-actions/configure-aws-credentials@v1
           with:
             aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
             aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
             aws-region: ${{ env.AWS_REGION }}

         - name: Login to Amazon ECR
           id: login-ecr
           uses: aws-actions/amazon-ecr-login@v1

         - name: Build, tag, and push image to Amazon ECR
           env:
             ECR_REGISTRY: ${{ steps.login-ecr.outputs.registry }}
             IMAGE_TAG: ${{ github.sha }}
             ECR_REPOSITORY: ${{ env.ECR_REPOSITORY }}
           run: |
             docker build -t $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG .
             docker push $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG

Explanation:

• This workflow triggers on any push to the main branch.
• It sets up environment variables for AWS Region, Image Tag (based on commit SHA), and ECR Repository name.
• The workflow uses AWS credentials stored in GitHub Secrets to authenticate with AWS.
• It logs into Amazon ECR, builds the Docker image using the Dockerfile, and pushes it to the specified ECR repository.

1. Commit and Push Changes:

Commit the workflow.yml file to your repository and push it to GitHub.

1. Monitor Workflow Execution:

Go to the "Actions" tab in your GitHub repository to monitor the workflow execution. You should see the workflow running and deploying your application to Amazon ECR whenever you push changes to the main branch.

Dockerfile Configuration (Dockerfile)

The Dockerfile specifies the environment and dependencies required to run your Python application in a Docker container.

Step-by-Step Guide:

1. Create Dockerfile in Your Project Directory:

Create a Dockerfile in the root of your project directory with the following content:

   FROM python:3.8-slim-buster

   WORKDIR /python-docker

   COPY requirements.txt requirements.txt
   RUN pip3 install -r requirements.txt

   COPY .env .env

   COPY paystack_zoho_pipeline.py paystack_zoho_pipeline.py

   EXPOSE 5000

   ENV FLASK_APP=paystack_zoho_pipeline.py

   CMD [ "python3", "-m" , "flask", "run", "--host=0.0.0.0"]

Explanation:

• This Dockerfile sets up a Python 3.8 environment with necessary dependencies installed.
• Copies requirements.txt and installs Python dependencies.
• Copies .env file for environment configuration.
• Copies paystack_zoho_pipeline.py which contains your Flask application.
• Exposes port 5000 for Flask to run.
• Defines the command to start the Flask application when the container starts.

1. Build and Test Locally:

Build the Docker image locally to ensure everything is set up correctly:

   docker build -t paystack_zoho_app .

Run the Docker container locally to test your application:

   docker run -p 5000:5000 paystack_zoho_app

Access your application at http://localhost:5000 to verify that it functions as expected.

Testing ngrok Webhook Setup for Paystack

During development, testing webhooks locally with ngrok ensures that your Paystack webhook integration works before deployment.

Step-by-Step Guide:

1. Download and Install ngrok:

Download ngrok from ngrok.com and install it on your local machine.

1. Start ngrok:

Start ngrok to expose your local server to the internet:

   ngrok http 5000

This will provide you with a temporary public URL (https://abcd1234.ngrok.io) that tunnels requests to your local Flask server running on port 5000.

1. Configure Paystack Webhook Endpoint:

• Log in to your Paystack dashboard.
• Navigate to Settings > Webhooks & API.
• Add the ngrok URL (https://abcd1234.ngrok.io) as the webhook endpoint URL.
• Ensure that webhook events sent from Paystack reach your local Flask server via ngrok.

Conclusion

You have now automated the deployment of your Paystack-Zoho CRM pipeline using GitHub Actions and Docker. This setup allows you to efficiently manage and deploy your application, ensuring seamless integration and scalability. By testing your ngrok setup with Paystack, you verify that webhook events are correctly received before moving to production. Stay tuned for more cloud automation insights as we continue our 100 Days of Cloud journey! Happy coding and cloud exploring!

Keep Clouding! ☁️