Build a Serverless app in 30 minutes with Azure Functions and Logic Apps


In this lab we will build a social dashboard as a Serverless app. It will contain an Azure Logic App to trigger on all tweets coming from Twitter, process them through Cognitive Services Text Analytics (Machine Learning), call an Azure Function to categorize them, and publish them to a Power BI dashboard.

Getting Started

  1. Log into the machine for the lab TECH-CAD-ILL200
  2. You may want to increase the resolution to 1280x1024 for easier navigation
  3. Use the Azure Pass code to provision an Azure Environment.
  4. Go to (the Azure Portal)[]

You should now be at the Azure Dashboard. Here we can create a Logic App that will trigger from the tweets in real-time.

  1. Click on the New button in the top left of the screen
  2. Choose Enterprise Integration and select a Logic App
  3. Give it the name Twitter-Analysis, create a new Resource Group called Serverless, and put it in West US (you can really put anything you want in any of these fields). Choose Pin to dashaboard for easy access in the remainder of the lab, and Create the logic app.

Once it’s created, it should automatically open (if not, just open it when it’s done). If you aren’t in the designer after opening, click the Edit button at the top menu to open the Logic App designer.

Logic Apps is the Serverless orchestration and workflow component. It will trigger and flow data to the different aspects of the Serverless app. We will build a logic app to trigger on Twitter, push the data to Cognitive Services, process with a Function, and publish to a Power BI dashboard.

  1. Scroll down to select the Blank Logic App template.
  2. Select the Twitter connector and choose the trigger When a tweet is posted
  3. Authenticate with a Twitter account - you can use this one as well:
  4. Enter the search term #Azure, and set the trigger to check Twitter every 15 seconds
  5. Click Save and push the Run button.

You’ll notice it will keep listening to Twitter until someone tweets about #Azure, and then fire. Once you verify your trigger is working, click the Designer button to go back and edit

Adding in Cognitive Services

Now we will add in a step to process all tweets with Azure Cognitive Services.

  1. Back in the Designer, click the New Step and Add an action
  2. Choose the Text Analytics connector and the Detect Sentiment action – this will use Machine Learning to detect the sentiment of the tweet, and give a score between 0 and 1. 0 being very negative, 1 being very positive.
  3. Provide a key to Cognitive Services. You can use the below:
  4. Select the Tweet Text from the trigger to process
  5. Click Save and push the Run button to verify the trigger works, and the tweet is evaluated by Cognitive Services.

Adding an Azure Function

Now that we have tweets with some sentiment, let’s add in an Azure Function to add a category for the Tweet. Let’s create the following rules:

For this kind of custom logic, we will create an Azure Function and add this code.

  1. Save your logic app, and click the New button on the top-left of the Azure Portal.
  2. Select the Compute category and choose to create a Function App
  3. Give it a UNIQUE name (like ServerlessLab19592), use the Use existing resource group from the Logic App (Serverless), keep the Consumption Plan, put it in West US, keep the Create New for storage, Pin the Dashboard, and Create
  4. Once the Function App is created (HINT: You can skip down to the Power BI step to start setting up your dashboard while you wait), open it up.
  5. Click the + next to Functions to create a new one, and leave the settings as a C# Webhook Function. Click Create this function

An Azure Function will not be created. You can click Run just to see that it works. The code here will fire on an HTTP Request - and we will eventually call from our Logic App.

  1. Replace the code in the Azure Function with the following:
using System.Net;
public static async Task<HttpResponseMessage> Run(HttpRequestMessage req, TraceWriter log)
    log.Info("C# HTTP trigger function processed a request.");
    // Get the score
    double score = await req.Content.ReadAsAsync<double>();
    // Set the category
    string category = "RED";
    if(score >= .6) {
        category = "GREEN";
    } else if (score >= .3) {
        category = "YELLOW";
    // Return the category
    return req.CreateResponse(HttpStatusCode.OK, category);
  1. (optional) You can test the function by setting the Request Body to some score like .7

Now that the Azure Function is created, we can go back into the Logic App to call it from there.

  1. Close the Azure Function and open the Logic App from the dashboard
    (If it’s not on the dashboard, you can use the search at the top, or choose the Logic App on the browse menu on the left)
  2. Click the Edit button to return to editing your app
  3. Add a New step, Add an Action, and choose Azure Functions
  4. Choose the Azure Function you just created
  5. Pass in the Score from the cognitive service into the Function

You now have a Serverless app that can categorize tweets from Twitter in real-time. As a last step, let’s publish this to a Power BI dashboard.

Publish to a Power BI dashboard

Using the pre-built dashboard

Using a pre-built dashboard will allow you to finish the lab quicker, but if you want details on using a dashboard you create from scratch in Power BI you can see details here

  1. Add a new step and search for Power BI - choose Add rows to a dataset
  2. Login with the following pre-created dashboard:
  3. Select My Workspace, the Twitter dataset, and the RealTimeData table.
  4. Fill in the following items (remember the Category is coming from our Azure Function):

NOTE: You will need to use the Search box on the outputs to fine the Created At - or click Show More as it is an advanced output

  1. Click save, and run.

That’s it! You can now to go and login with account with password S3rverless to see the tweets appear in real-time.

Next Steps

You have a few options if you have finished this far. You can learn how to create a dashboard from scratch here, or you can open your logic app to add logic like “If the score is less than .3, send an email to me.” To do that you would add a “Condition”, and then add an action in the “If yes” branch.

Creating a dashboard in Power BI

  1. Go to [] to login to Power BI.
  2. You may be able to use the Azure account here, or you may need to use the provided O365 account.
  3. Skip through the sign-up steps to get to the Power BI dashboard.
  4. Once at the Get Data screen - select the My Workspace button, and click the Skip for now option. You need to click the “My Workspace” area for ‘skip for now’ to appear
  5. Select Datasets, + Create, and Streaming Dataset to create a dataset to stream data to.
  6. Click Next for “API”
  7. Provide the following information:
Value Type
Tweet Text Text
Created At DateTime
Score Number
Location Text
Category Text

Creating the report

Once the dataset is created, you need to create a report to visualize the data.

  1. Select your workspace Datasets, and click the Create report icon for the Twitter dataset.
  2. Select the Line chart visualization, and chart it with Created At as the axis, and Score as the values. Change score to the average. This will draw a real-time line chart of average sentiment score over time.
  3. Pin your visualizations to a dashboard by clicking the Pin button.
  4. Choose to save your report (could name it Twitter), and create a new dashboard.
  5. You can continue to add more visualizations using similar steps - like a Map with location being Location, and size being Score
  6. You can now go back to the “pre-built dashboard” section, but instead of using the shared dashboard credentials, login with your O365 credentials. This will then publish your data to this dashboard.


Hopefully you were successful and understand the power and speed in which you can ship cloud-scale applications with serverless. If you have any questions or need any help feel free to contact me at