🌟 Serverless Image Processing with Azure Logic Apps & Shell Scripting

🔹 Project Overview

This project automates image processing using Azure Logic Apps and Linux shell scripting. The workflow includes:

✅ Uploading images to Azure Blob Storage.

✅ A Logic App triggers a shell script when a new image is uploaded.

✅ A Linux-based script processes the images (resize, watermark, etc.).

✅ The processed images are stored in another Blob container.

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📚 Table of Contents

• Step 1: Set Up Azure Blob Storage
• Step 2: Deploy a Linux VM (or Use ACI)
• Step 3: Write the Image Processing Shell Script
• Step 4: Set Up Azure Logic Apps
• Step 5: Set Up an API to Run the Script
• Step 6: Test the System
• 📊 Summary
• 🎯 Learning Outcomes
• 📚 Official Documentation
• 📞 Contact

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Step 1: Set Up Azure Blob Storage

• Storage Setup Script: Infrastructure/storage_setup.sh
  • This script creates an Azure Storage Account with two containers:
    • raw-images → Stores the original images.
    • processed-images → Stores the processed images.

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Step 2: Deploy a Linux VM (or Use ACI)

• VM Setup Script: Infrastructure/vm_setup.sh
  • This script creates an Azure Linux VM or sets up Azure Container Instances (ACI) for running the image processing script.

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Step 3: Write the Image Processing Shell Script

• Image Processing Script: Scripts/process_images.sh
  • This script fetches images from Blob Storage, processes them, and uploads the processed images back to Blob Storage.

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Step 4: Set Up Azure Logic Apps

1. Create a Logic App:

   • Go to the Azure portal and create a new Logic App.

2. Add Trigger: When a Blob is Added or Modified:

   • Choose the trigger "When a blob is added or modified (V2)".
   • Configure it to point to your raw-images container in your Azure Blob Storage.
   • This trigger will activate the Logic App whenever a new image is uploaded or an existing image is updated.

3. Add Action: HTTP Request:

   • After the blob trigger, add a new action for the HTTP request.
   • Choose the action "HTTP".
   • Set the method to POST and provide the URL for your Flask API endpoint (e.g., http://<your-vm-ip>:8080/run-script).
   • In the body, you can include any relevant data if necessary (e.g., the name of the blob or any other parameters).

4. Add Trigger: When an HTTP Request is Received:

   • If you want to manually trigger the processing, add a second trigger by choosing "When an HTTP request is received".
   • This will allow you to invoke the Logic App via an HTTP request whenever you need to process the images.

5. Configure the Logic App:

   • Once you have set up both triggers, you can define the workflow further by connecting additional actions as needed, such as logging or sending notifications.

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Step 5: Set Up an API to Run the Script

• API Script: APIs/app.py
  • This Flask API allows the Logic App to trigger the image processing script.

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Step 6: Test the System

1. Upload an Image to raw-images:

   az storage blob upload --container-name raw-images --account-name store4serverless --file sample.jpg

2. Trigger the Logic App:

   • This is automatically triggered by the blob upload.

3. Test the Flask API Manually (if needed):

   curl -X POST http://<your-vm-ip>:8080/run-script

4. Execute the Image Processing Script Manually (for testing):

   cd Scripts
   ./process_images.sh

5. Check the processed-images Container to see if the processed image appears.

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📊 Summary

Step	Task	Files
1️⃣	Set up Azure Blob Storage	storage_setup.sh
2️⃣	Deploy Linux VM / ACI	vm_setup.sh
3️⃣	Write Shell Script	process_images.sh
4️⃣	Set Up Logic App	Azure Portal
5️⃣	Create API to Trigger Script	app.py
6️⃣	Test the Workflow	Azure CLI

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🎯 Learning Outcomes

✅ Hands-on Azure Logic Apps for automation.

✅ Advanced Bash scripting for image processing.

✅ Real-world Azure Blob Storage Management.

✅ Deployment of serverless solutions using ACI or VM.

✅ Secure VM automation with Flask APIs & HTTP triggers.

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📚 Official Documentation

• Azure Logic Apps Documentation 📄
• Azure Blob Storage Documentation 📄
• Flask Documentation 📄
• Bash Scripting Guide 📄

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📞 Contact

For any help or inquiries regarding this project, feel free to reach out to me at [email protected]!

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