Serverless Flask API with Azure Functions

In this tutorial, I will show you how to build a serverless Flask API using Azure Functions. We will cover everything you need to know to create a RESTful API using Python, Flask, and Azure Functions. I’ll also explain how to deploy and test your API.

Prerequisites:

• Basic knowledge of Python and Flask
• An Azure account with access to Azure Functions
• Visual Code Studio (optional)

Introduction to serverless architecture and Azure Functions

1.1 Brief overview of serverless architecture and its benefits

Serverless architecture is a way of building and running applications and services without managing the underlying infrastructure. Instead of provisioning and maintaining servers, serverless architectures allow developers to focus on writing code and building applications that can scale automatically and run efficiently in the cloud.

One of the key benefits of serverless architecture is that it enables developers to focus on writing code and building applications, without having to worry about infrastructure management. This can help reduce costs, increase agility, and improve time-to-market for new applications and services.

In addition, serverless architectures are designed to scale automatically based on demand, which can help improve performance and reduce costs. With serverless architectures, developers only pay for the resources they use, which can help reduce costs and optimize resource utilization.

Serverless architecture is a powerful approach to building and running applications in the cloud, and it can help developers build and deliver applications more quickly and efficiently than traditional infrastructure-based approaches.

1.2 Introduction to Azure Functions and its features

Azure Functions is a serverless compute service provided by Microsoft Azure that allows you to run code on-demand without provisioning or managing any infrastructure. With Azure Functions, you can build and deploy event-driven, serverless applications that scale based on demand.

Azure Functions supports a variety of programming languages, including C#, Java, JavaScript, PowerShell, and Python, which makes it easy to use for developers who are already familiar with these languages. In addition, Azure Functions provides a number of features and benefits, including:

1. Easy integration with other Azure services: Azure Functions can be integrated with other Azure services, such as Azure Storage, Azure Event Hubs, and Azure Service Bus, which makes it easy to build event-driven solutions.
2. Automatic scaling: Azure Functions can automatically scale up or down based on the number of events being processed, which makes it easy to handle high volumes of events and maintain application performance.
3. Pay-per-execution pricing model: Azure Functions charges based on the number of executions, and you only pay for the time your code runs. This makes it a cost-effective solution for running event-driven applications.
4. Developer-friendly tooling: Azure Functions provides a rich set of tools for developers, including Visual Studio, Visual Studio Code, and Azure Functions Core Tools, which makes it easy to develop, test, and deploy Azure Functions.

Azure Functions is a powerful platform for building and deploying event-driven, serverless applications in the cloud. Its ease of use, flexibility, and integration with other Azure services make it a popular choice for developers who want to build scalable and cost-effective applications in the cloud.

Creating a new Azure Function App

2.1 Creating a new Function App in the Azure portal

To create a new Function App in the Azure portal, follow these steps:

1. Log in to the Azure portal.
2. In the left-hand menu, click “Create a resource”.
3. Search for “Function App” in the search bar and select it from the results.
4. Click the “Create” button on the Function App overview page.
5. Fill out the Function App creation form, including the following information:
   • App name: a unique name for your Function App
   • Subscription: the Azure subscription to use
   • Resource group: the name of the resource group to use or create a new one
   • OS: the operating system to use (Windows or Linux)
   • Hosting plan: the type of hosting plan to use (Consumption or App Service Plan)
   • Location: the location of the Azure datacenter where the Function App will be hosted
   • Runtime stack: the language and version of the runtime stack to use (e.g. Python 3.9)
6. Click “Review + create” to review your settings and then click “Create” to create the Function App.
7. Wait for the deployment to complete, which may take a few minutes.

Once the Function App has been created, you can access it from the Azure portal and start creating new Functions within it.

2.2 Configuring the Function App settings

After you have created your Function App, you need to configure the Function App settings to match your requirements. Here are the steps to configure the Function App settings:

1. In the Azure portal, go to your Function App and click on “Functions” in the left-hand menu.
2. Click on “Application settings” in the top menu.
3. Here you can configure various settings for your Function App, including:

• General settings: Here you can set the default host name, configure logging, and set the default document for your app.
• App settings: Here you can add and configure application settings, which are environment variables that your functions can use. You can also add connection strings and configure other settings related to your app.
• Connection strings: Here you can add and configure connection strings that your functions can use.
• CORS: Here you can configure Cross-Origin Resource Sharing (CORS) for your app.
• Authentication / Authorization: Here you can configure authentication and authorization for your app.

4. Once you have configured the settings, click on “Save” to save your changes.

It’s important to note that some settings may require you to restart your Function App for the changes to take effect. You can do this by clicking on “Functions” in the left-hand menu, then clicking on “Restart” in the top menu.

Adding Flask to Azure Functions

3.1 Setting up a virtual environment

There are different ways to set up a virtual environment in Python, but one common method is to use the venv module that comes with Python 3.

Here are the steps to set up a virtual environment for your Flask application:

1. Open a terminal or command prompt and navigate to the root directory of your project.

2. Create a new virtual environment by running the following command:

python -m venv venv

This will create a new directory named venv that will contain the virtual environment.

3. Activate the virtual environment by running the appropriate command for your operating system:

On Windows:

venv\Scripts\activate

On Linux or macOS:

source venv/bin/activate

After running this command, you should see the name of the virtual environment in your command prompt, like this:

(venv) $

4. Install Flask and any other dependencies your application needs. You can do this by running the following command:

pip install flask

5. Create a file named app.py (or any other name you prefer) and write your Flask application code.

Your virtual environment is now set up and you can start developing your Flask application. Remember to activate the virtual environment every time you work on the project by running the appropriate command.

3.2 Creating a new Flask app

1. In your project folder, you’ve created a new file called app.py.

2. Open the app.py file in your preferred text editor.

3. Import the necessary modules for your Flask application by adding the following lines of code:

from flask import Flask, request, jsonify
import logging
import azure.functions as func

4. Create a new Flask app object by adding the following line of code:

app = Flask(__name__)

The __name__ parameter is a Python special variable that specifies the name of the current module.

5. Define the route for the API endpoint by adding the following code:

@app.route('/api/greet', methods=['POST'])
def greet():
    data = request.get_json()
    name = data['name']
    message = f"Hello, {name}!"
    return jsonify(message=message)

This code creates a Flask route decorator that maps the URL /api/greet to the greet() function. The methods parameter specifies that the function should only be called when a POST request is received.

6. Define the main function that will be called when the Azure Function is triggered by adding the following code:

def main(req: func.HttpRequest) -> func.HttpResponse:
    try:
        name = req.params.get('name')
        if not name:
            try:
                req_body = req.get_json()
            except ValueError:
                pass
            else:
                name = req_body.get('name')
        if name:
            return func.HttpResponse(f"Hello, {name}!")
        else:
            return func.HttpResponse(
                "Please pass a name on the query string or in the request body",
                status_code=400
            )
    except Exception as e:
        print(str(e))

This code defines a function called main that takes an HttpRequest object as input and returns an HttpResponse object as output. It checks for the presence of a name parameter in the query string or the request body, and returns a greeting message if the parameter is present. Otherwise, it returns an error message.

7. Save the app.py file.

Your Flask application is now ready for deployment to Azure Functions.

3.3 Testing the API locally

Here, we will test the Flask API that we have created locally on our machine. Testing the API locally is an important step before deploying it to Azure Functions.

To test the API, follow these steps:

1. Make sure that you are in the virtual environment that you created in Section 3.1.

2. In the terminal, navigate to the directory where you have saved your Flask app.

3. Start the Flask app by running the following command:

flask run

1. After starting the Flask app, open a web browser and go to the following URL: http://localhost:5000/api/greet.

2. You should see the message “Please pass a name on the query string or in the request body”. This is because we have not passed a name to the API yet.

3. To pass a name to the API, add a query parameter to the URL. For example, to pass the name “John”, use the following URL: http://localhost:5000/api/greet?name=John.

4.. You should see the message “Hello, John!”.

5. You can also test the API using a REST client such as Postman or cURL.

6. Once you are satisfied with the testing, stop the Flask app by pressing CTRL+C in the terminal.

By testing the Flask API locally, we have verified that it is working as expected. In the next section, we will deploy the Flask API to Azure Functions so that it can be accessed over the internet.

Deploying the Flask API to Azure Functions

4.1 Creating a new Function in the Function App

Now, you will create a new Azure Function to host your Flask application.

1. Go to the Azure portal and navigate to your Function App.
2. Click on the “+ New Function” button to create a new Function.
3. In the “Create a function” pane, select “HTTP trigger” and click the “Create” button.
4. In the “New Function” pane, give your Function a name, such as “flaskapi”.
5. Under the “Authorization level” section, select “Anonymous” to allow public access to your API.
6. Leave the “Language” setting as “Python”.
7. Under the “Template” section, select “HTTP trigger”.
8. Click the “Create” button to create your new Function.

Your new Azure Function is now created and you can proceed to the next step to upload your Flask application files.

Note: In some cases, certain configurations may not allow functions to be created and deployed in the Azure portal. In that case, you can create and deploy your function using Visual Studio Code instead. To do this, follow the steps outlined in this tutorial, but instead of creating the function in the Azure portal, create and deploy the function using Visual Studio Code and the Azure Functions extension.

4.2 Uploading the Flask API files

After creating the new function, the next step is to upload the Flask API files to the Azure Functions app. There are several ways to do this, but one convenient method is to use Visual Studio Code.

To upload the files using Visual Studio Code, follow these steps:

1. Open Visual Studio Code and install the Azure Functions extension if you haven’t already.
2. Open the Azure Functions app in Visual Studio Code.
3. In the Explorer pane, navigate to the function that you created earlier.
4. Right-click on the function and select “Deploy to Function App”.
5. In the dialog box that appears, select the appropriate subscription and function app, and then click “Deploy”.
6. Wait for the deployment to complete.

Once the deployment is complete, your Flask API should be accessible through the endpoint that you defined in the previous step.

4.3 Configuring the Function settings

We can now configure the Azure Function app settings. The app settings include configuration values that the function app can use during execution. These settings can store keys, database connection strings, and other configuration values your app needs.

To configure the app settings, you can use the Azure portal or Visual Studio Code. In the Azure portal, navigate to your function app and click the “Configuration” tab. From here, you can add, update, or delete app settings as needed. In Visual Studio Code, you can update the app settings in the local.settings.json file.

In the local.settings.json file, add the necessary app settings as key-value pairs under the “Values” property. For example, if your Flask app needs a database connection string, you can add the following key-value pair:

{
  "IsEncrypted": false,
  "Values": {
    "DATABASE_CONNECTION_STRING": "your_database_connection_string_here"
  }
}

Note that if you’re working with sensitive information, such as database credentials, you should mark the IsEncrypted property as true and store the secrets in Azure Key Vault instead.

Once you’ve added the necessary app settings, save the file and deploy the changes to Azure Functions. You can do this by running the func azure functionapp publish <function-app-name> command in your terminal or by using the “Deploy to Function App” option in Visual Studio Code.

Testing the serverless Flask API

5.1 Using the Azure portal to test the API

1. To test the Flask API, you can use the Azure portal.

2. Go to your Function App in the Azure portal.

3. Click on “Functions” in the left-hand menu.

4. Click on the name of the function you created in section 4.1.

5. Click on “Code + Test” in the top menu.

In the “Test” pane, enter a JSON payload with the “name” property. For example:

{
  "name": "John"
}

6. Click the “Run” button to send the request and view the response.

You should see the response from the Flask API, which will be a JSON object containing a greeting message with the name you provided.

5.2 Using a REST client to test the API

Here are the steps to test the Flask API using a REST client:

1. Open a REST client, such as Postman or Insomnia.
2. Set the HTTP method to POST.
3. Set the request URL to the URL of your deployed Azure Function endpoint, followed by “/api/greet”.
4. Set the request headers to “Content-Type: application/json”.
5. Set the request body to a JSON object with a “name” property, like this: {“name”: “John”}.
6. Send the request and check the response. It should be a JSON object with a “message” property that says “Hello, John!” (or whatever name you used in the request body).

You can also test the API using the Azure portal or other HTTP clients, such as cURL or the Python requests library. The process is similar, but the specific steps may vary depending on the tool you’re using.

Conclusion and next steps

6.1 Recap of what was covered in the tutorial

In this tutorial, we explored how to create a serverless Flask API using Azure Functions. We started by creating a new Function App in the Azure portal, setting up a virtual environment, and creating a Flask app. We then created an API route and methods for our Flask app, and tested the API locally using both the Azure portal and a REST client. Finally, we deployed our Flask API to Azure Functions by creating a new Function, uploading the Flask API files, and configuring the Function settings. I hope this tutorial helped introduce you to serverless architecture and Azure Functions, and that you’re now equipped with the knowledge to start building your own serverless APIs.

6.2 Suggestions for next steps to continue learning about serverless architecture and Azure Functions

Here are some suggestions for next steps to continue learning about serverless architecture and Azure Functions:

1. Try out different types of triggers: Azure Functions supports a variety of triggers, including HTTP, blob storage, and event grid. Experiment with different triggers to see how they work and how you can use them in your applications.
2. Learn about serverless patterns: Serverless architecture allows you to build applications using small, independent functions that can be scaled up or down as needed. Learn about different serverless patterns and how they can be used to build efficient and scalable applications.
3. Integrate with other Azure services: Azure Functions can be used with a wide variety of other Azure services, including Azure Storage, Azure Event Hubs, and Azure Cosmos DB. Explore these integrations and learn how they can be used to build more complex and powerful applications.
4. Optimize performance: Serverless architecture is designed for efficient and scalable applications, but there are still many ways to optimize the performance of your Azure Functions. Learn about techniques like warm starts, connection pooling, and efficient use of memory to make your functions as fast and efficient as possible.
5. Learn about monitoring and debugging: Monitoring and debugging serverless applications can be challenging, but there are many tools and techniques available to make the process easier. Learn about tools like Azure Monitor and Application Insights, and explore best practices for debugging and troubleshooting your applications.