Push Notifications and Buttons with Microsoft Flow: Part 3

In part 1 we crated a Flow to enable/disable the sending of push notifications and in part 2 we created an Azure Function to generate random phrases of positivity.

In this third and final part of this series we’ll go and create the second Flow that sends the push notifications to the phone.

This Flow will be automatically triggered every 15 minutes by using a Recurrence action followed by an action to get the blob content containing whether or not we should send a notification as the following screenshot shows:

Running a Microsoft Flow every 15 minutes

Now that we have the blob content, we can examine it in an If condition. If the content of the blob is “enabled” we can continue the Flow:

If condition in Microsoft Flow

If the condition is satisfied (“IF YES”) two actions are  performed: the first an HTTP GET to the Azure function, the second a push notification action that as content uses what was returned in the body of the HTTP GET. Notice in the HTTP GET, the URI includes the function authorization key as a query string parameter.


After saving the new Flow, we can head back to the Flow app and hit the button to enable “positivity pushes”:

Microsoft Flow iOS app button

Then every 15 minutes (until we turn them off by hitting the button again) we’ll get a positivity notification on the phone:

iOS push notifications from Microsoft Flow

Push Notifications and Buttons with Microsoft Flow: Part 2

In part 1 we created a Flow to toggle the sending of push notifications on and off by storing the configuration in Azure blob storage.

Now that we have a way of enabling/disabling notifications we can start to build the second Flow.

Before jumping into the Flow designer, we need to consider how to generate random positivity phrases and how to integrate this into the second Flow. One option to do this is to create a simple Azure Function with an HTTP trigger. The Flow can then use an HTTP action to issue a GET to the server that will return the string content to be sent via push notifications.

In the Azure Portal function editor a new function can be created with a HTTP trigger configured to GET only as the following screenshot shows:

Creating an Azure Function with a HTTP trigger

Notice in the preceding screenshot the authorization level has bee set to “function”. This means the key needs to be provided when the function is called.

We can now write some code in the function code editor window as follows:

using System.Net;

public static HttpResponseMessage Run(HttpRequestMessage req, TraceWriter log)
    log.Info("C# HTTP trigger function processed a request.");

    string phrase = GeneratePhrase();

    return req.CreateResponse(HttpStatusCode.OK, phrase);

public static string  GeneratePhrase()
    var phrases = new string[]
        "Don't worry, be happy :)",
        "All is well",
        "Will it matter in 100 years?",
        "Change what you can, don't worry about what you can't"

    var rnd = new Random();
    return phrases[rnd.Next(phrases.Length)];

Azure Function code editor window

Clicking the Run button will test the function and we can see the random phrases being returned with a 200 status as shown in the following screenshot:

Azure function HTTP test output

In the final part of  this series we’ll go and create the second Flow that uses this function and the configuration value created in the previous article to actually send random positivity push notifications on a 15 minute schedule.

Push Notifications and Buttons with Microsoft Flow: Part 1

Microsoft Flow allows the creation of serverless cloud workflows. It is similar to services such as If This Then That and has more of a business focus. It allows custom Flows to integrate with Azure services such as blob storage, the calling of arbitrary HTTP services, in addition to a whole host of services such as Facebook, Dropbox, OneDrive, etc.

In addition to executing in the cloud, Flows can create push notification to the Flow app on iOS and Android.

Once installed, the Flow app can be used to design/edit Flows, view Flow activity/recent executions, and initiate the execution of flows via “buttons” as shown in the following screenshot.

Microsoft Flow iOS app

Tapping this software button will trigger the Flow in the cloud.

Example Scenario

To see buttons and push notification in action, imagine a scenario where sometimes you want cheering up with regular messages of positivity.

In this scenario, when enabled, you’ll get a push notification on your phone every 15 minutes with a random positive phase such as “Don't worry, be happy :)”.

To accomplish this two separate (but related) Flows can be created. The first Flow uses a button in the phone Flow app to toggle wether the “positivity pushes” will be sent. The second Flow is triggered automatically every 15 minutes and if enabled, sends a push notification.

Creating the Toggle Positivity Push Flow

This Flow will enable/disable the push notifications. To do this, a manual button trigger will be added to the Flow that will be pushed on the phone. To hold the enabled/disabled state, we can use the content of a blob in Azure blob storage. When triggered, the Flow will retrieve the content of the blob which can be the string “enabled” or “disabled”.

Microsoft Flow reading content from blob storage

Once the blob content has been retrieved, its content can be examined in a If condition. If the content of the blob is currently “enabled” it will be updated to “disabled” and vice versa. Finally we’ll send a push notification to confirm the state.

Microsoft Flow examining blob content

Pressing the button in the app a couple of times results in the expected push notifications:

Microsoft Flow sending push notifications to iOS

The blob content also gets toggled as expected:

Blob content being toggled from Microsoft Flow

In part 2 of this series we’ll start the process of creating another Flow to actually send the random positivity phrases to the phone.

Creating a Tweet Buffer with Azure Queues and Microsoft Flow

There are apps and services that allow the scheduling or buffering of the sending of Tweets. Using the features of Microsoft Flow, it’s possible to create a solution that allows Tweets to be quickly created as simple text files in a OneDrive folder and these will then be buffered to be sent every 15 minutes (or whatever schedule you fancy). The actual buffering mechanism used below is an Azure Queue.

There are two Flows as part of this solution: Flow 1 to pick up text files from OneDrive, extract the content and write a new message to an Azure Queue. Flow 2 runs on a schedule, picks a message off the queue, grabs the message content and sends it a s a Tweet.

Flow 1: Queuing Tweets

The first step is to create an Azure Storage account and create an Azure Queue. The easiest way to create a new queue is to use the Azure Storage Explorer. Once installed and connected, creating a queue is a simple right-click operation:

Using Azure Storage Explorer to create a new Azure Queue

We’ll call the queue “tweet-queue”.

We’ll also create OneDrive folders: OneDrive\FlowDemo\TweetQ\In

Now we can create a new Flow that grabs files from this path and adds them to tweet-queue as the following screenshot shows (notice we're also deleting the file after adding to the queue):

Microsoft Flow reading a file from OneDrive and adding to Azure Queue

Now if we create a .txt file (for example with the content “Testing - this Tweet came from Microsoft Flow via OneDrive and an Azure Queue” in the OneDrive\FlowDemo\TweetQ\In directory, wait for the Flow to run and check out the queue in Storage Explorer we can see a new message as the following screenshot shows:

Azure Storage Explorer showing Azure Queue message content

Now we have a way of queuing Tweets we can create a second flow to send them on a timer.

Flow 2: Sending Tweets

The second Flow will be triggered every 15 minutes, grab a message from the queue, use the message body as the Tweet content, then delete the message from the queue.

The following screenshot shows the first 2 phases:

Getting Azure Queue messages on a timer

Even though we’ve specified 1 message, when we add the next action in the Flow, we’ll automatically get an “Apply to each” added as the following screenshot shows:

Posting Tweet from Azure Queue

Notice in the preceding screenshot that we also need to add an action to delete the message from the queue.

Now once we save this Flow, every 15 minutes a message will be retrieved and posted as a Tweet:

Triggering a Microsoft Flow from an HTTP Post

Microsoft Flow allows the building of workflows in the cloud. One way to trigger a Flow is to set up a HTTP endpoint that can be posted to.

For example, a Flow can be created that takes some JSON data and writes it out to OneDrive or Dropbox.

The first step is to create a new Flow and add a Request trigger. When the Flow is saved, a URL will be generated that can be posted to.

As part of this Request trigger, a JSON schema can be specified that allows individual JSON properties to be surfaced and referenced by name in later actions.

For example the following JSON schema could be specified:

  "$schema": "http://json-schema.org/draft-04/schema#",
  "title": "Customer",
  "description": "A generic customer",
  "type": "object",
  "properties": {
    "id": {
      "description": "The unique identifier for a customer",
      "type": "integer"
    "name": {
      "description": "The full name of the customer excluding title",
      "type": "string"
  "required": [

Now in later steps, the “id” and the “name” properties from the incoming JSON can be used as dynamic content.

Next action(s) can be added that make use of the the data in these properties when an HTTP post occurs. For example we could create a file in OneDrive where the filename is {id}.txt that contains the customer name. This is a simple example but serves to demonstrate the flexibility.

The following screenshot shows the full flow and the JSON schema properties in use:

Microsoft Flow using request trigger and OneDrive

We can now post to the generated URL. For example the following screenshot shows a test post using Postman and the resulting file that was created in OneDrive:

HTTP post to trigger a Microsoft Flow

Serverless Computing and Workflows with Azure Functions and Microsoft Flow

Microsoft Flow is a tool for creating workflows to automate tasks. It’s similar in concept to If This Then That but feels like it exists more towards the end of the spectrum of the business user rather than the end consumer – though both have a number of channels/services in common. Flow has a number of advanced features such as conditions, loops, timers, and delays.

Flow has a number of services including common ones such as Dropbox, OneDrive, Twitter, and Facebook. There are also generic services for calling HTTP services, including those created as Azure Functions. Essentially, services are the building blocks of a Flow.

Screenshot of Microsoft Flow Services

Once the free sign up is complete you can create Flows from existing templates or create your own from scratch.

Screenshot of Microsoft Flow pre-built templates

To create a new custom Flow, the web-based workflow designer can be used.

Integrating a Flow with Azure Functions

In the following example, a Flow will be created that picks up files with a specific naming convention from a OneDrive folder, sends the text content to an Azure Function that simply converts to uppercase and returns the result to the Flow. The Flow then writes out the uppercase version to another OneDrive folder.

Reading Files From OneDrive

The first step in the Flow is to monitor a specific OneDrive folder for new files.

A Flow triggered by new OneDrive files

As an example of conditions, an “if statement” can be added to only process files that contain the word “data”:

Microsoft Flow condition

Now if the filename is correct we can go ahead and call an Azure Function (or other HTTP endpoint).

Calling an Azure Function from Microsoft Flow

Now that we are reading specific files, we want to call an Azure Function to convert the text content of the file to upper case.

The following code and screenshot shows the function that will be called – this code is stripped down and doesn’t contain any error checking/handling code for simplicity:

Azure Function app screenshot

using System.Net;

public static async Task<HttpResponseMessage> Run(HttpRequestMessage req, TraceWriter log)
    log.Info($"C# HTTP trigger function processed a request. RequestUri={req.RequestUri}");

    dynamic data = await req.Content.ReadAsAsync<object>();
    string text = data.text;

    return  req.CreateResponse(HttpStatusCode.OK, text.ToUpperInvariant());

We can test the API in Postman:

Calling Azure Function from Postman

Now that we have a working function we can add a new action of type “HTTP” to the Flow and pass the contents of the OneDrive file as JSON data in the request. The final step is to take the response of calling the Azure Function and writing out to a new file in OneDrive as the following screenshot shows:

Calling Azure Function passing OneDrive file content as JSON data

Now we can create a file “OneDrive\FlowDemo\In\test1data.txt”, the Flow will be trigged, and the output file “OneDrive\FlowDemo\Out\test1data.txt” created.

Output file

Microsoft Flow also has a really nice visual representation of runs (individual executions) of Flows:

Microsoft Flow run visualization

Microsoft Flow by itself enables a whole host of workflow scenarios, and combined with all the power of Azure Functions (and other Azure features) could enable some really interesting uses.