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That is it, that is the SharePoint List in its entirety. To create the Flow, choose the first Flow Template in the list.

On selecting the template you will be redirected to the Flow website. On editing the Flow Template you will be presented with the following flow:.

Remove the last two actions so that you only see the When a new item is created action. Keep Flow open as we will be coming back to it later to complete the template.

Back in SharePoint, now click the PowerApps drop down. By clicking this dropdown, PowerApps will automagically build you a mobile application based on your list.

In 2 minutes you have a working mobile application that you can publish and then share. Once you have published the app, go to your mobile device, download the PowerApps app for your device, login with your O Account used to create the SharePoint List and you should see the PowerApp created above to open and run.

You could even pin the new app to your Home screen thereby bypassing the need to open PowerApps first PowerApps will open in the background.

So now you have your trigger and your mobile app. All we need to do now is add the actions when a SharePoint List item is added with an action of Start and when an action is added of type Stop.

For this I am going to use Azure Automation Runbooks :. For more information on how to create or import a Runbook please follow this document.

Once you have both Runbooks in your Account choose one of them and select Edit. For the purpose of this solution we want to stop start a single VM, so edit the Graphical Runbook and edit them so that once the script has connected to Azure, get a single VM only.

Your Graphical Runbook should then look something like this:. Publish your Runbooks and try each of them out. If they both run successfully we now want to add a Webhook for each Runbook so that we can run the Runbooks remotely via our Flow template.

For information on how to o create the Webhook for each Runbook please follow this document. Note, you only get the option once to copy the Webhook Url so make sure you click the Copy button.

As a strectch goal, you may want to try passing these values as part of the request — to do that you should add 2 extra columns to your SharePoint List so that once you have re-created the PowerApp you will have the option of entering the names which you can then use as part of your Flow.

Following the Trigger, create a Condition. This is obviously a very simple case, but hopefully it gives you food for thought on how you can use a mix of O and Azure Automation to manage your Azure Assets.

As part of the customer acquisition flow, the goal is for a new customer to sign up for Office which includes creating a new tenant and subscription through ContosoApps.

If the app tries to access other services behind Microsoft Graph, this pre-consent flow will not work. Note: If you plan to create a web app version of the bootstrap application, remember to register it as multi-tenant.

Bootstrap Application To help you understand the steps required to build the bootstrap application, we have included two applications you can download and modify.

Therefore, at the least you should perhaps consider the downloadable applications as simply templates for your own bootstrap application that you can use to understand how to build your own.

For this blog, we are going to concentrate on the code in the native. NET Console application. Where possible more on that later we are using the AAD Graph.

Whilst it is possible to make requests directly against the AAD Graph rest endpoint graph. Using this library simplifies the authentication process immensely, easily allowing us to separate the authentication code from the application logic.

All the code required to authenticate a user can be found in the class AuthenticationHelper. Whilst the bootstrap application does not make use of the data returned by the call there is a circumstance where a need to make a request is required…more on that later.

The following sections provide details on how to record consent for delegated permissions i. See this article for more details. Configuration: Once you have registered the bootstrap application there are a number of parameters that you need to modify in order for the authentication to happen successfully.

These parameters can all be found in the class Constants. The parameters you need to modify are: BootstrapClientId — generated when registering the application in the Azure Portal.

This value is represented by the Application Id for the application. RedirectUrl — specified when registering the application in the Azure Portal.

Authentication: As per previous comments, the logic to Authenticate a user is in the most the responsibility of the AuthenticationHelper. Once the user has authenticated we cache the access token as a static resource for the lifetime of the process.

This effectively means the user only needs to sign-in once maybe twice if we do need to use the Microsoft Graph resource and then we can make use of that token for all future requests.

Consent: The code for processing the consent flow can all be found in the class Request. Read Mail. AppOnlyPermissions …represented by a list of strings, these are the app-only permissions required by your AAD applications.

Note, these permissions are represented by their GUID value and not their string name. The console application then will be able to request consent for use of the bootstrap application; it will prompt the user to sign-in again with their credentials as a new access token needs to be generated to make the request.

The code to add the Service Principal will only add if the tenant does not already have the Service Principal in their directory.

Next, create a collection OAuthGrants. The contents of each OAuthGrant and the values you need was discussed earlier…the code to do so is as per below: From here on in you should no longer have to modify any more of the code.

Conclusion Okay we are done. You should find now that when a user of the tenant, targeted by the bootstrap application, sign-ins in to your AAD application the consent dialog should be suppressed.

Remember, you can download either a native or a web application bootstrap here. If you would like to know more about the specific API calls used for programmatic consent e.

Finally, thank you to Stewart Adam and Denis Kisselev for collaborating on this project. A couple of weeks ago I was given the opportunity of working with a partner to build a solution that would hopefully help them automate their expense receipts processing.

Whilst the scenario sounded simple there was a need for a reliable infrastructure to enable the processing, i. This is referenced in another blog post by one of my colleagues on the team that can be found here.

So why Azure Functions? Next I am going to walkthrough some of the key pieces of the solution and then finally provide instructions on where to learn how you would go about setting up continuous deployment to Azure using Visual Studio Team Services.

All the code I describe in this blog post can be found on GitHub. There are 2 folders: a simple image uploader console application and, the azure functions to process the image.

Please feel free to download the solutions and try out the code yourself. For instructions on how to deploy and run, please refer to the pre-requisite and setup instructions outlined in the readme documents in each folder.

For details on where to download please refer here. The function itself is triggered by a message being added to the Azure Storage Queue, receiptQueueItem.

As well as receiptQueueItem there are several other important parameters of this function, namely:. Step 0 in the case statement is responsible for the primary activity of this function and is the the one that provides the SmartOCRService with the necessary information so that it can process the image:.

The message has 4 properties:. An added advantage of using a queue rather than a direct request to the SmartOCRService is that the role of the ExpenseProcessor is now temporarily complete until the OCRCallback function triggers the state change or continuation of the workflow.

Step 1 of the process provides a placeholder to communicate when the processing of the image is complete success or failure.

In this simplified case, the code simply updates the receiptsTable to highlight the final status of the process. To identify which image has been processed, the ItemId is a property of the message payload.

As you will see as part of the OCRSmartService, there are several non-catastrophic scenarios which we may want to handle by retrying the process.

This step simply restarts the process by following the steps executed as part of Step 0. This new workflow state will either be Complete, Error or Retry.

Its important to note that it was a desired condition by the partner to have this separation of concerns between the ExpenseProcessor and the SmartOCRService — it is imagined that overtime more processors will be put in place e.

InvoiceProcessor, OrderProcessor, etc. As per the previous ExpenseProcessor function, the function is triggered when a message is added to the Azure Storage Queue QueueTrigger described by the parameter ocrQueue.

Key thing to note within this function: As the function is dependent on the OCR Service being available it needs to handle the exception when the service is unavailable.

If the service is unavailable the requestor may want to inform the user that they need to try later, or in our case automate that process by having the requestor retry the whole process automagically.

By default, if the function fails there will be a maximum of 5 retry attempts. If the last retry attempt fails then the original queue message is added to a poison-message queue.

By adding the message to a poison-message queue means the message will not be acted upon again but provides a user some notification that the message has failed.

In our case we wanted to override this behaviour by preventing this message being added to the poison-message queue.

Note, to monitor the number of retries the function has tried then add the parameter dequeueCount , which is type int to the signature of the Run … method.

It was a requirement of the Partner that they needed this continuous infrastructure in place. The original plan was to investigate how this could be done by trying out ourselves the setup within Visual Studio Team Services, but after some researching on the internet we found a great blog which set out the steps perfectly.

The final requirement the partner had was being able to monitor their Azure Functions. After several iterations it was decided that to get the best insights into how the application was performing was to integrate Microsoft Application Insights.

If you are interested in using Application Insights inside your Azure Functions then I would suggest you read the following blog post found here.

If you find Application Insights is overkill for your projects then I would suggest having a look at the following documentation.

A common bot use case that is often discussed is how to have a bot contact a user based on some triggered event or lengthy job or an external event such as a state change in the system.

These type of bots are often referred to as proactive bots. In this post I am going to show you how to create a proactive bot using the Microsoft Bot Framework and Microsoft Azure.

I have decided to write the solution using C but all of the concepts are just as valid for Node. You can find all the code you need in my GitHub here.

The code to build the bot can be found here. To use this code you must:. Azure functions allow you to develop and deploy small pieces of code in the language of your choice and in the cloud without setting up infrastructure.

If you are new to Azure Functions then I would definitely recommend having a look at this tutorial. As well as being a great getting started it will also introduce you to working with Azure Queues which form the basis of our solution.

As per the general architecture diagram above, will need to create 2 Azure Functions: one to capture the subscription posted from the Bot and another to capture the back office event being completed.

So looking at each one in turn:. This function is triggered when a new Queue Message is added to an Azure Queue. Give, your function the name SubscriptionTrigger and then specify the Queue name as subscription-items and select from the dropdown the Storage Account you created previously.

Once the function has been created, you need to allow the function to update an Azure Table. Change both the Table parameter name and Table name to subscriptionTable, and select from the dropdown the Storage Account you created previously.

Back in the body of the function run. Note, the parameter names for the types SubscriptionMessage and CloudTable need to match what you entered as part of the Integrate step.

Choose Save and I suspect you will get an error complaining about the type ConversationReference. This is a class specified in the Microsoft. Builder framework which is available as a Nuget package.

We need to therefore include a reference to this framework and to do so we need to add a new file. The diagram below shows the new file project.

Once you have added the file, try saving the function again and hopefully the code should compile successfully. At this stage, you should be able to test your code to see if the Subscription side of the solution is working successfully.

To check, go to the bot channel e. You should get a response from the bot that the subscription to that order has been noted.

Like the previous function, this function is triggered when a new Queue Message is added to an Azure Queue. Friday, April 10, For the Birds.

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The Bride. The bride. Mask from traditional Kabuki Theater. Posted by Unknown at Friday, April 10, 0 comments.

Labels: amateur photography , digital photography , japan , japanese , kabuki , kabuki theater , mask , oriental , plays , sake , traditional.

Thursday, April 9, Petals. A rose by any other name Posted by Unknown at Thursday, April 09, 3 comments. Labels: amateur photography , beauty , digital photography , flowers , iris , moggy , moggy k , my back yard , nc , north carolina , panasonic dmc fz18k , petals , plants , roses , spring.

Falls lake is a man-made lake that covers 12, acres and is surrounded by 26, acres of woodland. Posted by Unknown at Wednesday, April 08, 0 comments.

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Tuesday, April 7, Red Bellied Woodpecker. This beautiful bird is a regular at our suet feeders. Posted by Unknown at Tuesday, April 07, 2 comments.

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Saturday, September 20, William B.

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