Prerequisites

Install Azure CLI # Windows curl -sL https://aka.ms/InstallAzureCLIDeb | sudo bash

# macOS brew install azure-cli

# Or download from: https://docs.microsoft.com/en-us/cli/azure/install-azure-cli

Install Azure Functions Core Tools

# Windows (via npm)
npm install -g azure-functions-core-tools@4 --unsafe-perm true

# macOS
brew tap azure/functions
brew install azure-functions-core-tools@4

# Linux
curl https://packages.microsoft.com/keys/microsoft.asc | gpg --dearmor > microsoft.gpg
sudo mv microsoft.gpg /etc/apt/trusted.gpg.d/microsoft.gpg
sudo sh -c 'echo "deb [arch=amd64] https://packages.microsoft.com/repos/microsoft-ubuntu-$(lsb_release -cs)-prod $(lsb_release -cs) main" > /etc/apt/sources.list.d/dotnetdev.list'
sudo apt-get update
sudo apt-get install azure-functions-core-tools-4

Step 1: Login to Azure

az login


Step 2: Set Your Subscription (if you have multiple)
bash# List subscriptions
az account list --output table

# Set active subscription

az account set --subscription "Your-Subscription-Name-Or-ID"

Step 3: Create Resource Group (if needed) bash

az group create --name myResourceGroup --location eastus

Step 4: Create Storage Account (for Function App) bash

az storage account create \
  --name myfunctionstorageacct \
  --location eastus \
  --resource-group myResourceGroup \
  --sku Standard_LRS

Step 5: Create Function App bash

az functionapp create \
  --resource-group myResourceGroup \
  --consumption-plan-location eastus \
  --runtime python \
  --runtime-version 3.9 \
  --functions-version 4 \
  --name myFaceBlurFunctionApp \
  --storage-account myfunctionstorageacct \
  --os-type linux

Step 6: Prepare Your Project Structure Create the following folder structure: face-blur-function/ ├── requirements.txt ├── host.json ├── local.settings.json ├── FaceBlurTimer/ │ ├── init.py │ └── function.json └── shared/

  └── face_blur_processor.py
  
  

Step 7: Create Project Files requirements.txt

txtazure-functions
azure-storage-blob
requests
python-dotenv
Pillow
schedule

host.json

{
  "version": "2.0",
  "logging": {
    "applicationInsights": {
      "samplingSettings": {
        "isEnabled": true,
        "excludedTypes": "Request"
      }
    }
  },
  "extensionBundle": {
    "id": "Microsoft.Azure.Functions.ExtensionBundle",
    "version": "[2.*, 3.0.0)"
  },
  "functionTimeout": "00:10:00"
}

local.settings.json

{
  "IsEncrypted": false,
  "Values": {
    "AzureWebJobsStorage": "your_function_storage_connection_string",
    "FUNCTIONS_WORKER_RUNTIME": "python",
    "AZURE_STORAGE_CONNECTION_STRING": "your_blob_storage_connection_string",
    "AZURE_CONTAINER_NAME": "your_source_container_name",
    "WEBAPP_URL": "https://your-webapp.com/blur",
    "WEBAPP_TIMEOUT": "60"
  }
}
<code>

FaceBlurTimer/function.json
<code>
{
  "scriptFile": "__init__.py",
  "bindings": [
    {
      "name": "mytimer",
      "type": "timerTrigger",
      "direction": "in",
      "schedule": "0 0 * * * *"
    }
  ]
}

Step 8: Set Application Settings

# Set your environment variables
az functionapp config appsettings set \
  --name myFaceBlurFunctionApp \
  --resource-group myResourceGroup \
  --settings \
  "AZURE_STORAGE_CONNECTION_STRING=your_blob_storage_connection_string" \
  "AZURE_CONTAINER_NAME=your_source_container_name" \
  "WEBAPP_URL=https://your-webapp.com/blur" \
  "WEBAPP_TIMEOUT=60"
  

Step 9: Initialize Function Project Locally

# Create project directory
mkdir face-blur-function
cd face-blur-function
# Initialize function project
func init --python

Step 10: Create Timer Function

func new --name FaceBlurTimer --template "Timer trigger"

<code>

Step 11: Deploy to Azure

<code>
# Deploy the function
func azure functionapp publish myFaceBlurFunctionApp

Alternative: Deploy using Azure CLI (Zip Deploy) If you prefer to deploy using zip:

Create deployment package
zip -r deployment.zip .

# Deploy using az cli

az functionapp deployment source config-zip \
  --resource-group myResourceGroup \
  --name myFaceBlurFunctionApp \
  --src deployment.zip