Create and deploy a C# Azure Function

Case
I want to create an Azure Function with C# code. How do I create and deploy one in Azure (and use it Azure Data Factory)?

Write C# in Visual Studio Code to create an Azure Function

Solution
In this blogpost we will create and deploy a very simple 'hello world' Azure Function with an HTTP trigger which you can extend to your own needs. After that we can use the Azure Data Factory pipeline with an Azure Function activity to execute it.

As an alternative you could also create an Azure Function with a Blob Storage trigger that executes when a new file arrives, but we rather want to use that same trigger type to start an Azure Data Factory pipeline that then starts this Function followed by other pipeline activities. This way we have one place that does the triggering/orchestration.

1) Create new Azure Function project
Please first follow the steps of our previous post on how to prepare Visual Studio Code for creating Azure Functions with C#. After that open Visual Studio code and perform the steps below to create your first hello world Function.

• In Visual Studio code click on the Azure icon in the left menu.
• In the newly opened pane click on the folder with the lightning icon on it to create a new project. (An additional function can later-on be added to the project with the Lightning-plus icon)
• Select the folder of the new project (or use the Browse... option)
• Next select C# as coding language
• Select HTTP trigger as the template for this example
• Enter the Function name. This is the name of the function within the project (that can contain multiple functions). Example: myCSharpFunction
• Provide a namespace: Bitools.Function
• For this test example use anonymous as Authorization level
• The project has been created, but their could be an additional action in step 2

Create new Azure Function project

2) Unresolved dependencies
This extra step seems to be a bug in the Azure Function extension for C# in Visual Studio code. After the project has been generated Visual Studio Code will show the following error in the lower right corner. This seems to refer to some missing references.

There are unresolved dependencies.
Please execute the restore command to continue.

If you don't get this error then Microsoft probably solved the bug. When you do get it, the only thing you have to do is clicking the Restore button. After that some extra files will be added in the obj folder of your project. (see previous post to compare extension versions)

Execute the restore command

Spot the differences

3) Code in myCSharpFunction.cs
The file 'myCSharpFunction.cs' contains your C# code. The name could be different when you gave your function a different name. Below you see the standard / generated code with some extra comment lines for if you are new to C#. For this example we do not extend the code.

// This section lists the namespaces that this function will be using frequently,
// and saves the programmer from specifying a fully qualified name every time that
// a method that is contained within is used
using System;
using System.IO;
using System.Threading.Tasks;
using Microsoft.AspNetCore.Mvc;
using Microsoft.Azure.WebJobs;
using Microsoft.Azure.WebJobs.Extensions.Http;
using Microsoft.AspNetCore.Http;
using Microsoft.Extensions.Logging;
using Newtonsoft.Json;

namespace Bitools.Function
{
    public static class myCSharpFunction
    {
        // Main function and entry point of this Azure Function
        [FunctionName("myCSharpFunction")]
        public static async Task<IActionResult> Run(
            [HttpTrigger(AuthorizationLevel.Anonymous, "get", "post", Route = null)] HttpRequest req,
            ILogger log)
        {
            // Log information
            log.LogInformation("C# HTTP trigger function processed a request.");

            // Retrieve parameter 'name' from querystring
            string name = req.Query["name"];

            // Also try to retrieve the same parameter from the request body
            string requestBody = await new StreamReader(req.Body).ReadToEndAsync();
            dynamic data = JsonConvert.DeserializeObject(requestBody);
            // If not found in querystring then use requestbody
            name = name ?? data?.name;

            // If name is still empty throw an error that a name parameter
            // is expected else response with a greeting
            string responseMessage = string.IsNullOrEmpty(name)
                ? "This HTTP triggered function executed successfully. Pass a name in the query string or in the request body for a personalized response."
                : $"Hello, {name}. This HTTP triggered function executed successfully.";

            return new OkObjectResult(responseMessage);
        }
    }
}

4) Debug locally
Now we are going to test the Azure Function locally on our Windows device. There are multiple ways to start debugging. Pressing F5 is probably the easiest. See animated gif for more options.

• In the Run menu on the top of the screen you will find the Start Debugging option. 
• The terminal pane on the bottom will show a lot of details. Wait a few seconds for it to finish and click (while also pressing CTRL) on the green URL.
• A new browser window will open and it shows the error output that it cannot find the name parameter.
• In the browser add a querystring after the URL: ?name=Joost (or your own name of course). Now it will respond with a greeting
• Close the browser and then hit the disconnect icon on top to stop debugging

Debugging your function locally

5) Create Azure Function in Azure Portal
Before you can deploy your newly created function you first need to create an Azure Function in the Azure portal.

• Go to the Azure Portal and click on Create a resource
• Search for function and select Function App
• Click on the Create button
• On the Basics tab you find the most important settings
• Select your Subscription and Resource Group
• Enter an unique Function App name
• Select .NET Core as Runtime stack
• Select 3.1 as Version 
• Select the Region (probably the same as your Resource Group)
• Optionally go to the Hosting tab for extra settings
• Choose a new or existing Storage account
• Change the Plan type (default: Serverless)
• Optionally go to the Monitoring tab for extra settings
• Disable or enable Application insights and change its name
• Click the Review + create button
• Review the settings and click on the Create button

Create new Azure Function (app) on Azure portal

Note 1: you cannot create an Azure Function with a Windows worker (.NET Core) if there is already a Linux worker (Python) in that same resource group and with the same region.

Note 2: you could also perform these steps within Visual Studio Code during deployment.

6) Deploy Azure Function to Azure Portal
Now that we have an (empty) Azure Functions app in the Azure portal we can deploy our newly created Azure Function to this resource.

• In Visual Studio code click on the Azure icon in the left menu.
• In the newly opened pane click on the blue arrow (deploy) icon
• In the drop down select your Azure Functions App from the previous step

Deploy Azure Functions from Visual Studio Code

7) Testing in portal
Now that we have deployed our project to Azure Functions we can test it in the Azure Portal. For this example we will use the post method.

• Go to the Azure Portal and then open your Azure Functions App
• In the left menu click on Functions
• In the list of functions click on your function (only one in this example)
• In the left menu click on Code + Test
• Click on the test button (top center)
• Change the HTTP method to post
• Select one of the keys
• Enter a JSON message in the body: {"name":"Joost"} (name=case-sensitive)
• Click on the Run button and see the result

Testing in the Azure Portal

8) Executing from Azure Data Factory
Now if you want to execute this new Azure Function in Azure Data Factory with the Azure Function Activity you can follow the steps in this previous post. However without code changes it will return an error stating that the response is invalid: 3603 - Response Content is not a valid JObject

3603 - Response Content is not a valid JObject

At the moment it is returning a so called JArray, but it is expecting a JObject (J = JSON). Any other return types than JObject will throw the error above. To overcome this we need a minor code change at the end by changing the return construction at line 37.

// This section lists the namespaces that this function will be using frequently,
// and saves the programmer from specifying a fully qualified name every time that
// a method that is contained within is used
using System;
using System.IO;
using System.Threading.Tasks;
using Microsoft.AspNetCore.Mvc;
using Microsoft.Azure.WebJobs;
using Microsoft.Azure.WebJobs.Extensions.Http;
using Microsoft.AspNetCore.Http;
using Microsoft.Extensions.Logging;
using Newtonsoft.Json;

namespace Bitools.Function
{
    public static class myCSharpFunction
    {
        // Main function and entry point of this Azure Function
        [FunctionName("myCSharpFunction")]
        public static async Task<IActionResult> Run(
            [HttpTrigger(AuthorizationLevel.Anonymous, "get", "post", Route = null)] HttpRequest req,
            ILogger log)
        {
            // Log information
            log.LogInformation("C# HTTP trigger function processed a request.");

            // Retrieve parameter 'name' from querystring
            string name = req.Query["name"];

            // Also try to retrieve the same parameter from the request body
            string requestBody = await new StreamReader(req.Body).ReadToEndAsync();
            dynamic data = JsonConvert.DeserializeObject(requestBody);
            name = name ?? data?.name;

            // If name is still empty throw an error that a name parameter
            // is expected else response with a greeting
            return name != null
                ? (ActionResult)new OkObjectResult(new {message = "Hello " + name})
                : new BadRequestObjectResult("Pass a name in the query string or in the request body for a personalized response.");

            /* 
            string responseMessage = string.IsNullOrEmpty(name)
                ? "This HTTP triggered function executed successfully. Pass a name in the query string or in the request body for a personalized response."
                : $"Hello, {name}. This HTTP triggered function executed successfully.";

            return new OkObjectResult(responseMessage);
            */
        }
    }
}

Below a couple of screenshots on how to configure and test this in Azure Data Factory. You might want to store the Function key in Azure Key Vault to avoid keys in your ETL/ELT code.

Set up the Azure Function Activity in Azure Data Factory

After configuring the Azure Function activity you can hit the debug button and see the result. This output could then be used as input for successive pipeline activities

Successfully executing and getting the response

Conclusion
First a big thank you to colleague Walter ter Maten for always helping me out with the C# stuff. In this blog post you learned how to create, test and deploy your first (very basic) Azure Function App with C# code. Then we also showed you how to execute this from Azure Data Factory. In a couple of follow up posts we will show you how to build some useful functions for DWH projects and show you some technical stuff like adding Azure Key Vault to the game. Also check out the Python version of this blogpost.

Create and deploy a Python Azure Function

Case
I want to create an Azure Function with Python code. How do I create and deploy one in Azure?

Write Python in Visual Studio Code to create an Azure Function

Solution
In this blogpost we will create and deploy a very simple 'hello world' Azure Function with an HTTP trigger which you can extend to your own needs. After that we can use the Azure Data Factory pipeline with an Azure Function activity to execute it.

As an alternative you could also create an Azure Function with a Blob Storage trigger that executes when a new file arrives, but we rather want to use that same trigger type to start an Azure Data Factory pipeline that then starts this Function followed by other pipeline activities. This way we have one place that does the triggering/orchestration.

1) Create new Azure Function project
Please first follow the steps of our previous post on how to prepare Visual Studio Code for creating Azure Functions with Python. After that open Visual Studio code and perform the steps below to create your first hello world Function.

• In Visual Studio code click on the Azure icon in the left menu.
• In the newly opened pane click on the folder with the lightning icon on it to create a new project. (An additional function can later-on be added to the project with the Lightning-plus icon)
• Select the folder of the new project (or use the Browse... option)
• Next select Python as coding language
• Select the Python interpreter. In our example it is py 3.8.3 (if it's not in the list you need to browse to python.exe on your device)
• Select HTTP trigger as the template for this example
• Enter the Function name. This is the name of the function within the project (that can contain multiple functions)
• For this test example use anonymous as Authorization level
• The project has been created, but continue with the next step below with some additional actions before you can start coding

Create new Azure Function project

2) Select interpreter and install Linter pylint
To finish the creation of the project we need to select the location of the interpreter and install a linter.

• Click on the popup in the bottom left corner to select the interpreter. 
• On the top in the middle you can now select the interpreter. Select the one in the .venv folder which is a subfolder of your project.
• Next step is to install Linter pylint by clicking on the install button on the new popup in the bottom left corner.
• Now wait a few seconds for the installation to finish

Select interpreter and install Linter pylint

3) Code in __init__.py
The file '__init__.py' contains your Python code. Below you see the standard / generated code with some extra comment lines for if you are new to Python. For this example we do not extend the code.

# Import module for logging purposes
import logging

# Import module for Azure Functions and give it an alias
import azure.functions as func

# Main function and entry point of this Azure Function
def main(req: func.HttpRequest) -> func.HttpResponse:
    # Log information
    logging.info('Python HTTP trigger function processed a request.')

    # Retrieve parameter 'name' from querystring
    name = req.params.get('name')
    # If not found try to retrieve it from the request body
    if not name:
        try:
            # Check if there is a request body
            req_body = req.get_json()
        except ValueError:
            # On failure do nothing
            pass
        else:
            # On success try to retrieve name from request body
            name = req_body.get('name')

    # If a name was found then response with 'Hello [name]'
    if name:
        return func.HttpResponse(f"Hello {name}!")
    else:
        # If a name was not found response with an error message
        return func.HttpResponse(
             "Please pass a name on the query string or in the request body",
             status_code=400
        )

4) Debug locally
Now we are going to test the Azure Function locally on our Windows device. There are multiple ways to start debugging. Pressing F5 is probably the easiest. See animated gif for more options.

• In the Run menu on the top of the screen you will find the Start Debugging option. 
• The terminal pane on the bottom will show a lot of details. Wait a few seconds for it to finish and click (while also pressing CTRL) on the green URL.
• A new browser window will open and it shows the error output that it cannot find the name parameter.
• In the browser add a querystring after the URL: ?name=Joost (or your own name of course). Now it will respond with a greeting
• Close the browser and then hit the disconnect icon on top to stop debugging

Debugging your function locally

5) Create Azure Function in Azure Portal
Before you can deploy your newly created function you first need to create an Azure Function in the Azure portal.

• Go to the Azure Portal and click on Create a resource
• Search for function and select Function App
• Click on the Create button
• On the Basics tab you find the most important settings
• Select your Subscription and Resource Group
• Enter an unique Function App name
• Select Python as Runtime stack
• Select the Python Version (3.8 in our example)
• Select the Region (probably the same as your Resource Group)
• Optionally go to the Hosting tab for extra settings
• Choose a new or existing Storage account
• Change the Plan type (default: Serverless)
• Optionally go to the Monitoring tab for extra settings
• Disable or enable Application insights and change its name
• Click the Review + create button
• Review the settings and click on the Create button

Create new Azure Function (app) on Azure portal

Note 1: you cannot create an Azure Function with a linux worker (python) if there is already a Windows worker (C#) in that same resource group and with the same region. You will then get an error: LinuxWorkersNotAllowedInResourceGroup - Linux workers are not available in resource group bitools. Use this link to learn more https://go.microsoft.com/fwlink/?linkid=831180. Also see the Azure Function documentation. Summary: don't mix C# and Python functions within the same resource group.

Note 2: you could also perform these steps within Visual Studio Code during deployment.

6) Deploy Azure Function to Azure Portal
Now that we have an (empty) Azure Functions app in the Azure portal we can deploy our newly created Azure Function to this resource.

• In Visual Studio code click on the Azure icon in the left menu.
• In the newly opened pane click on the blue arrow (deploy) icon
• In the drop down select your Azure Functions App from the previous step

Deploy Azure Functions from Visual Studio Code

7) Testing in portal
Now that we have deployed our project to Azure Functions we can test it in the Azure Portal. For this example we will use the post method.

• Go to the Azure Portal and then open you Azure Functions App
• In the left menu click on Functions
• In the list of functions click on your function (only one in this example)
• In the left menu click on Code + Test
• Click on the test button (top center)
• Change the HTTP method to post
• Select one of the keys
• Enter a JSON message in the body: {"name":"Joost"} (name=case-sensitive)
• Click on the Run button and see the result

Testing in the Azure Portal

7) Executing from Azure Data Factory
Now if you want to execute this new Azure Function in Azure Data Factory with the Azure Function Activity you can follow the steps in this previous post. However without code changes it will return an error stating that the response is invalid: 3603 - Response Content is not a valid JObject

3603 - Response Content is not a valid JObject

At the moment it is returning a so called JArray, but it is expecting a JObject (J = JSON). Any other return types than JObject will throw the error above. To overcome this we need two code changes. First we need to import the JSON module by adding: import json at the top of the code with the other imports. Then we need to adjust the return of the Hello world message. See changes after lines 4 and 30.

# Import module for logging purposes
import logging

# import json module to return a json message
import json

# Import module for Azure Functions and give it an alias
import azure.functions as func

# Main function and entry point of this Azure Function
def main(req: func.HttpRequest) -> func.HttpResponse:
    # Log information
    logging.info('Python HTTP trigger function processed a request.')

    # Retrieve parameter 'name' from querystring
    name = req.params.get('name')
    # If not found try to retrieve it from the request body
    if not name:
        try:
            # Check if there is a request body
            req_body = req.get_json()
        except ValueError:
            # On failure do nothing
            pass
        else:
            # On success try to retrieve name from request body
            name = req_body.get('name')

    # If a name was found then response with 'Hello [name]'
    if name:
        #return func.HttpResponse(f"Hello {name}!")
        message = {'message': f"Hello {name}!"}
        return json.dumps(message)
    else:
        # If a name was not found response with an error message
        return func.HttpResponse(
             "Please pass a name on the query string or in the request body",
             status_code=400
        )

Below a couple of screenshots on how to configure and test this in Azure Data Factory. You might want to store the Function key in Azure Key Vault to avoid keys in your ETL/ELT code.

Set up the Azure Function Activity in Azure Data Factory

After configuring the Azure Function activity you can hit the debug button and see the result. This output could then be used as input for successive pipeline activities

Successfully executing and getting the response

Conclusion
First a big thank you to colleague Jasper Diefenbach for helping me out with the Python stuff. In this blog post you learned how to create, test and deploy your first (very basic) Azure Function App with Python code. Then we also showed you how to execute this from Azure Data Factory. In a couple of follow up posts we will show you how to build some useful functions for DWH projects and show you some technical stuff like adding Azure Key Vault to the game. Also check out the C# version of this blogpost.

Setup Visual Studio code for Azure Functions

Case
I want to create Azure Functions on my Windows device, but which tools and extensions do I need to install?

Write Python or C# in Visual Studio code to create Azure Functions

Solution
In this blogpost we will show you which tools you need to install to create an Azure Function with either .NET or with Python code. The screenshots are of the current versions at the time of writing, but you might just want to take the latest stable version when downloading. In the upcoming Azure Functions posts we will create some basic Hello World functions to show the basics of creating and deploying your first Function. After that we will show some more useful functions for the Data Warehousing developers. For example to convert Excel or XML files to an easier readable format for Azure Data Factory or Synapse Polybase: CSV.

1) Download and install Visual Studio Code
For this blog post we will be using Visual Studio Code instead of the regular Visual Studio. Where this 'regular' Visual Studio is a so called Integrated Development Environment (IDE), the newer Visual Studio Code is more a lightweight source code editor. Ideal for some coding with PowerShell, C# or Python. Use the link below to download Visual Studio Code and then install it.
https://code.visualstudio.com/download

Installing Visual Studio Code

2) Install extensions for Python
If you want to use Python for your Azure Functions you need to install Python for Windows and the Python extension for Visual Studio code. First download and install Python for windows 64bit. The default is a 32 bit version, but you can also find the 64 bit version slightly down the page (search for Windows x86-64 executable installer).
https://www.python.org/downloads/windows/

Install Python for Windows 64bit

Then install the Python extension for Visual Studio code. When clicking on the install button on the website it will ask to open it with Visual Studio Code. Within Visual Studio Code you have to click on the install button again. After installation it will ask to point to the previously installed Python interpreter.
https://marketplace.visualstudio.com/items?itemName=ms-python.python

Install Python extension for Visual Studio code

Note: You can also use the Extensions icon in the left menu of Visual Studio code to search for this specific extension.

There is one last installation required: Linter Pylint, but Visual Studio Code will ask for it when creating your first Azure Function with Python code: Linter pylint is not installed.

Install Linter pylint for Visual Studio Code

Installing Linter pylint within Visual Studio Code

3) Install extentions for C#
If you want to create Azure Functions with C# then you first need to install .Net Core SDK. Make sure to install the version to Build apps (Run Apps is not sufficient). The minimum version is .NET Framework 4.7.2 or .NET Core 2.2, but try the most recent version depending on your needs and the Runtime version of Azure Functions. If you forget this then you will recieve an error while trying to create a C# Function.

Receive an error when have not installed .NET Core SDK

Furthermore you should install the C# extension from Microsoft. This extension is not mandatory, but will be recommended when creating your first C# Azure Function.

Install C# extension for Visual Studio code

Note: You can also use the Extensions icon in the left menu of Visual Studio code to search for this specific extension.

4) Install extensions for Azure Functions
Next extension is Azure Functions for Visual Studio code. When clicking on the install button on the website it will ask to open it in Visual Studio Code. Within Visual Studio Code you have to click on the install button again.
https://marketplace.visualstudio.com/items?itemName=ms-azuretools.vscode-azurefunctions

Azure Functions for Visual Studio Code

Note: You can also use the Extensions icon in the left menu of Visual Studio code to search for this specific extension.

5) Install Azure Functions Core Tools
To make you able to debug the Azure Function code locally we need Azure Functions Core Tools, but to install that we first need to install Node Package Manager (NPM) which is included in nodejs (more detailed info here).
https://nodejs.org/en/download/

Install NodeJS with NPM

Last step of this installation is to open a Command Promt (or PowerShell promt) in Administrator mode to install Azure Functions Core Tools. With the command npm -v you can check your npm version. Now use the following command for the installation (more detailed info here):

npm i -g azure-functions-core-tools@3 --unsafe-perm true

Install Azure Functions Core Tools via command prompt

Conclusion
In this introduction post you read which tools and extensions to install to create Azure Functions. Quite a lot installations, but manageable when following the steps above. We focused on the most popular languages (in the DWH scene) C# and Python, but there are way more languages to choose from like Java(script) or PowerShell. Each with its own extensions.

As mentioned before the next post about Azure Functions will be about deploying your first simple function with Python or C#. After that we will focus on the more functional Azure Functions solutions, but with a focus on the DWH scene. Also bringing Azure Key Vault to the game is a must for Azure Functions.

Introducing Azure Function Activity to Data Factory

Case
Last month Microsoft released the new Azure Function Activity for Azure Data Factory (ADF). This should make it easier to integrate Azure Function code in Data Factory. How does it work?

Azure Function activity in Azure Data Factory

Solution
Using Azure Functions (like other API's) was already possible via the Web Activity, but now ADF has its own activity which should make the integration be even better.

Azure Functions via the Web Activity

For a project at a client we where already using the Web Activity for a Azure Function with an HTTP trigger and to use this code with the new activity, we did need to slightly change the code. Note that I'm not a die hard .NET developer, but I got some help from my colleague Walter ter Maten.

1) HttpResponseMessage to IActionResult
The standard function did return an HttpResponseMessage, but for Azure Function Activity in the ADF pipeline it needs to return a json object. Below you find a very simple and partial code purely to show the differences in the function call and the return code. Also notice the extra reference/using.

Partial old code with the HttpResponseMessage (Web Activity only):

//C# Code
using System.Linq;
using System.Net;
using System.Net.Http;
using System.Threading.Tasks;
using Microsoft.Azure.WebJobs;
using Microsoft.Azure.WebJobs.Extensions.Http;
using Microsoft.Azure.WebJobs.Host;

namespace Calculate
{   
    public static class Calculate
    {
        [FunctionName("SumNumbers")]
        public static async Task<HttpResponseMessage> SumNumbersFunction([HttpTrigger(AuthorizationLevel.Function, "get", "post", Route = null)]HttpRequestMessage req, TraceWriter log)
        {
            int number1 = 0;
            int number2 = 0;

            // Log start
            log.Info("C# HTTP trigger function processed a request.");

            // Get request body
            dynamic data = await req.Content.ReadAsAsync<object>();
            number1 = data?.number1 ?? 0;
            number2 = data?.number2 ?? 0;

            // Log parameters
            log.Info("Number1:" + number1.ToString());
            log.Info("Number2:" + number2.ToString());

            return req.CreateResponse(HttpStatusCode.OK, "The result is " + (number1 + number2).ToString());
        }
    }
}

Partial new code with the IActionResult (Azure Function Activity and Web Activity):

//C# Code
using System.Linq;
using System.Net;
using System.Net.Http;
using System.Threading.Tasks;
using Microsoft.Azure.WebJobs;
using Microsoft.Azure.WebJobs.Extensions.Http;
using Microsoft.Azure.WebJobs.Host;
using Microsoft.AspNetCore.Mvc;  // Added

namespace Calculate
{   
    public static class Calculate
    {
        [FunctionName("SumNumbers")]
        public static async Task<IActionResult> SumNumbersFunction([HttpTrigger(AuthorizationLevel.Function, "get", "post", Route = null)]HttpRequestMessage req, TraceWriter log)
        {
            int number1 = 0;
            int number2 = 0;

            // Log start
            log.Info("C# HTTP trigger function processed a request.");

            // Get request body
            dynamic data = await req.Content.ReadAsAsync<object>();
            number1 = data?.number1 ?? 0;
            number2 = data?.number2 ?? 0;

            // Log parameters
            log.Info("Number1:" + number1.ToString());
            log.Info("Number2:" + number2.ToString());

            return new OkObjectResult(new { Result = "OK" });
        }
    }
}

We also needed to install the Microsoft.AspNetCore.Mvc NuGet Package. In the tools menu from Visual Studio you will find the NuGet Package Manager. Then search for this package and click the install button. After that you can add the new Using (Microsoft.AspNetCore.Mvc) in the code.

Bijschrift toevoegen

2) Get Function Key and App URL
In the next step we need to specify the Function URL and the Function Key. You can find them in the Azure Portal and then locate the specific function.

Function App URL

For the Function Key you need to go to Manage in you function and then copy the Function Key.

Function Key

3) Azure Function Activity
Now you can replace the Web Activity by an Azure Function Activity. Drag the new activity to the pipeline canvas and give it a suitable name. Next create a new Azure Function Linked Server. This is where you need the two strings from the previous step. After that enter the name of the function you want to execute, choose the Method and fill in the Body (copy it from the Web Activity).
Now delete the Web Activity and debug the pipeline to check the Function. Also check the Monitor (log) of your Azure Function to see whether it was successfully executed.

Replace Web Activity by Azure Function Activity

Summary
In this post you saw how to use the new Azure Function activity in the Azure Data Factory pipeline. It is fairly easy, but we did have to make a small change to the code. If you don't change the code you will get this error:
{
    "errorCode": "3600",
    "message": "Error calling the endpoint.",
    "failureType": "UserError",
    "target": "Sum this"
}
For now I did not see any improvements other than that you now can use the Function Key in Azure Functions which also allows you to revoke access for a specific key.