Steve Spencer's Blog

Blogging on Azure Stuff

Cloud Load Testing Behind a Firewall with Visual Studio Team Services

Recently I’ve been looking at how we can load test one of our services so that we are able to understand the load our partners can put onto our systems before we start to have any issues. We used the Cloud-based Load Testing (CLT) service of Visual Studio Team Services (VSTS). I created a short video showing you how to easily setup a url based load test. The next stage of our load testing was to load test the service that our partners provide, Their service required IP whitelisting to connect which meant the CLT service would not be able to connect. Luckily for us the CLT service allows you to deploy agents into your own infrastructure  to carry out the load testing and they are controlled by the same CLT service that we used to load test our own service. This blog post will show you how to install the agent and configure the load test for this scenario.

The load test agent is installed using a PowerShell script which can be obtained from here. Open the PowerShell as administrator and don’t forget to unblock the script

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To enable you to run the script and to configure the agents to talk to the CLT service, you will need to create a PAT token in VSTS.

Login and click on your user icon, then select Security

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Select Personal Access Tokens, then Add

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Fill in the form and click Create Token at the bottom of the page

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This creates your token and this is the only time you will be able to access the token

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You need to make sure that you copy it now as it you will not be able to access it after you have left the page,

Gong back to PowerShell, run the following command

.\ManageVSTSCloudLoadAgent.ps1 -TeamServicesAccountName StevesVSTS -PATToken 37abawavsmsgj6hpakltwhdjt4jrqsmup2jx62hlcxbju2l2tbja -ConfigureAgent -AgentGroupName StevesInternalTest

This will take a few minutes to run. If you didn’t run PowerShell as an Administrator you might see errors. When it has run the VSTSLoadAgentService should be installed and running

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Now need to configure a load test. Following on from my video, you can create a url test

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I ran a test web app in Visual Studio using localhost as the address

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When the test has been created select the Settings tab, click “Use self-provisioned agents” and select your agent from the list and add the number of agents you want to use. You could install the agents on a number of machines in your environment using the same script, then you will be able to add more than 1 agent if required. As I only installed the one agent I can only select 1. You can see how many agents the CTL service can see

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If there are less than you think you will need to check to make sure the service was installed without error and that it is running 

Save the load test and run it.

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Whilst the test was running the performance meters in Visual Studio showed that the web page was being loaded.

When the test is complete you should see that it has not cost you any VUM (Virtual User Minutes) as the load tests are running on your own agents

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The Cloud Load Test service allows you to load test both publicly accessible and private websites and services. As long as the servers running the load test agents have outbound access to the internet for HTTPS then we are able to load test private sites and services and the load test does not cost anything apart from the cost of the infrastructure that the agents are running on locally.

Custom ASP.NET MVC app running in a Windows Container

With the introduction of Windows Containers on  Window Server 2016 and the ability to run containers in Service Fabric I thought it was time to investigate Windows Containers and I wanted to know how to build one that will run a web site using IIS.

As I’m new to containers, although I’ve done a very similar exercise with Docker on Linux, I decided to follow the Windows Quick Start Guide. I hit a few problems early on so I’ve put the steps I followed here:

After opening a PowerShell window as administrator I ran the following commands:

Install-Module -Name DockerMsftProvider -Repository PSGallery –Force – Ran OK
Install-Package -Name docker -ProviderName DockerMsftProvider – Had an error
WARNING: Cannot verify the file SHA256. Deleting the file.
WARNING: C:\Users\ADMINI~1.DEV\AppData\Local\Temp\DockerMsftProvider\Docker-1-12-2-cs2-ws-beta.zip does not exist
Install-Package : Cannot find path 'C:\Users\ADMINI~1.DEV\AppData\Local\Temp\DockerMsftProvider\Docker-1-12-2-cs2-ws-beta.zip' because it does not exist.

 

Not sure what was causing this to fail but I followed the instructions to manually install (from https://github.com/OneGet/MicrosoftDockerProvider/issues/15)

Start-BitsTransfer -Source https://dockermsft.blob.core.windows.net/dockercontainer/docker-1-12-2-cs2-ws-beta.zip -Destination /docker.zip
Get-FileHash -Path /docker.zip -Algorithm SHA256
mkdir C:\Users\Administrator\AppData\Local\Temp\DockerMsftProvider\
cp .\docker.zip C:\Users\Administrator\AppData\Local\Temp\DockerMsftProvider\
cd C:\Users\Administrator\AppData\Local\Temp\DockerMsftProvider\
cp .\docker.zip Docker-1-12-2-cs2-ws-beta.zip
Install-Package -Name docker -ProviderName DockerMsftProvider -Verbose Restart-Computer –Force

After Rebooting I tried to download and run a sample container

docker run microsoft/dotnet-samples:dotnetapp-nanoserver

but I got the following error

docker : C:\Program Files\Docker\docker.exe: error during connect: Post http://%2F%2F.%2Fpipe%2Fdocker_engine/v1.25/containers/create: open //./pipe/docker_engine: The

system cannot find the file specified..

At line:1 char:1

+ docker run microsoft/dotnet-samples:dotnetapp-nanoserver

+ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

+ CategoryInfo : NotSpecified: (C:\Program File...ile specified..:String) [], RemoteException

+ FullyQualifiedErrorId : NativeCommandError

It turns out that the docker service wasn’t running after the reboot, so open services.msc and find the docker service to start it.

Running the same command again will download the image from docker hub, create a container from it and then run it. As this is a visual container it runs once and then stops.

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Every time I do docker run microsoft/dotnet-samples:dotnetapp-nanoserver it creates a new container. What I want to do is to run one that is stopped and view the output on the screen.

For this I needed to start the container I had already created. If you run

docker –ls –a

This will list all the containers that are both running and stopped and you can see from the image below that I had run docker run a number of time. Each time it tried to download the image (which was already downloaded) and then create a new container from it.

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docker container start -a 12d382ae0bd6 (-a attached STDOUT so you can see the output)

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Now I know how to create and start containers I wanted to build one of my own. This is easier than I first though as there a lots of base templates stored on docker hub and git hub.

https://docs.microsoft.com/en-us/virtualization/windowscontainers/samples#Application-Frameworks

https://hub.docker.com/r/microsoft/

I picked one on docker hub that has IIS and ASP.Net installed already, so all I needed to do after was to add my own website and configure IIS correctly. Using docker pull,

docker pull microsoft/aspnet (see https://hub.docker.com/r/microsoft/aspnet/)

This retrieves the template from Docker Hub and I want to use that template to install my ASP.Net MVC site and configure IIS to serve the pages on port 8000. Following the instructions here (https://docs.microsoft.com/en-us/dotnet/articles/framework/docker/aspnetmvc). I published my MVC site and copied the publish folder to my docker machine. Then I needed to create a Dockerfile recipe to instruct docker what to install in my image. So I created a folder that contained the Dockerfile and also the published website as below

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The contents of the Dockerfile are:

# The FROM instruction specifies the base image. You are
# extending the microsoft/aspnet image.
FROM microsoft/aspnet
# Next, this Dockerfile creates a directory for your application
RUN mkdir C:\sdsweb
# configure the new site in IIS.
RUN powershell -NoProfile -Command \
Import-module IISAdministration; \
New-IISSite -Name "sdsweb" -PhysicalPath C:\sdsweb -BindingInformation "*:8000:"
# This instruction tells the container to listen on port 8000.
EXPOSE 8000
# The final instruction copies the site you published earlier into the container.
ADD sdswebsource/ /sdsweb

Now I need to run this to create the image

In PowerShell, I changed directory to the folder containing my Dockerfile, then ran

docker build -t sdsweb .

This has created an image and we need to now get this running as a container

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using docker run again

docker run -d -p 8000:8000 --name sdsweb sdsweb

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My container is now running and I should be able to view the web pages in my browser on port 8000, but I need to know the IP address first

docker inspect -f "{{ .NetworkSettings.Networks.nat.IPAddress }}" sdsweb

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Now I can browser to http://172.17.97.235:8000

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I changed the default web page to show the machine name serving the pages under Getting Started. Listing the containers will show the container ID and this matches the machine name displayed on the web page

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That’s it running in a container. There are a couple more things I’d like to do before I’ve finished. The first is to make sure that when my Windows Server restarts, then my sdsweb container also starts. At the moment it will not start as I didn’t add a restart parameter when I called docker run. Adding –restart always will cause the container to restart when windows restarts.

docker run -d -p 8000:8000 --name sdsweb --restart always sdsweb

The final thing I want to do is to be able to share this image so I’d like to push it up to docker hub

docker login - enter username and password

docker push recneps/sdsweb

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Then to use it on another machine

docker pull recneps/sdsweb

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In my next post I am going to look at how I can create a container that can be hosted in Service Fabric

Processing a flat file with Azure Logic Apps

[Update: 5th Aug 2018 – This post is still relevant especially the integration account, schemas and maps and I  have written a new blog that builds on this one and integrates into SQL  -  Using Azure Logic Apps to Import CSV to SQL Server]

A lot of companies require the transfer of files in order to transact business and there is always a need to translate these files from one format to another. Logic Apps provides a straight forward way to build serverless components that provide the integration points into your systems. This post is going to look at Logic apps enterprise integration to convert a multi-record CSV file into and XML format. Most of the understanding for this came from the following post:

https://seroter.wordpress.com/2016/09/09/trying-out-standard-and-enterprise-templates-in-azure-logic-apps/

Logic Apps can be created in Visual Studio or directly in the Azure Portal using the browser. Navigate to the azure portal https://portal.azure.com click the plus button at the top of the right hand column, then Web + Mobile then Logic App

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Complete the form and click Create

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This will take a short while to complete. Once complete you can select the logic app from you resource list to start to use it.

If you look at my recent list

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You can see the logic app I’ve just created but you will also see my previous logic app and you will also notice that there is also an integration account and an Azure function. These are both required in order to create the necessary schemas and maps required to translate the CSV file to XML.

The integration account stores the schemas and maps and the Azure function provides some code that is used to translate the CSV to XML.

An integration account is created the same way as a logic app. The easiest way is to click on the plus symbol and then search for integration

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Click on Integration Account then Create

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Complete the form

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Then Create. Once created you can start to add your schemas and maps

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You will now need to jump into Visual Studio to create your maps and schemas. You will need to install the Logic Apps Integration Tools for Visual Studio

You will need to create a schema for the CSV file and a schema for the XML file. These two blog posts walk you through creating a flat file schema for a CSV file and also a positional file

I created the following two schemas

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Once you have create the two schemas you will need to create a map which allows you to map the fields from one schema to the fields in the other schema.

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In order to upload the map you will need to build the project in Visual Studio to build the xslt file.

The schemas and map file project can be found in my repository on GitHub

To upload the files to the integration account, go back to the Azure portal where you previously selected the integration account, click Schemas then Add

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Complete the form, select the schema file from your Visual Studio project and click OK. Repeat this for both schema files. You do the same thing for the map file. You will need to navigate to your bin/Debug (or Release) folder to find the xslt file that was built. Your integration account should now show your schemas and maps as uploaded

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There’s one more thing to do before you can create your logic app. In order to process the transformation some code is required in an Azure Function. This is standard code and can be created by clicking the highlighted link on this page. Note: If you haven’t used Azure Functions before then you will also need to click the other link first.

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This creates you a function with the necessary code required to perform the transformation

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You are now ready to start your logic app. Click on the Logic App you created earlier. This will display a page where you can select a template with which to create your app.

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Close this down as you need to link your integration account to your logic app.

Click on Settings, then Integration Account and pick the integration Account where you previously uploaded the Schemas and Map files. Save this and return to the logic app template screen.

Select VETER Pipeline

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Then “Use This Template”. This is the basis for your transformation logic. All you need to do now is to complete each box.

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In Flat File Decoding & XML Validation, pick the CSV schema

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In the transform XML

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Select the function container, the function and the map file

All we need to do now is to return the transformed xml in the response message. Click “Add an Action” on Transform XML and search for Response.

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Pick the Transformed XML content as the body of the response. Click save and the URL for the logic app will be populated in the Request flow

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We now have a Request that takes the CSV in the body and it returns the XML transform in the body of the response. You can test this using a tool like PostMan or Fiddler to send in the request to the request URL above.

There is also a test CSV file in my repository on GitHub which can be used to test this.

My next post covers how I diagnosed a fault with this Logic App

System.Web.Mvc not found after deploying to Azure Web Apps using Release Manager

I’m currently evaluating Release Manager in Visual Studio Team Services and I am using it to deploy website to Azure Web Apps. I recently tried to deploy an Asp.Net MVC 4 application and ran into some issues.

I’ve created a build that packages and zips up my web application which runs successfully.I’ve linked a Release pipeline to this build and I can deploy to my test Azure site without any errors, but when I try and run the web application I get the following error:

Could not load file or assembly 'System.Web.Mvc, Version=4.0.0.0, Culture=neutral, PublicKeyToken=31bf3856ad364e35' or one of its dependencies. The system cannot find the file specified.

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I’m using Visual Studio 2013 with MVC as a nuget package.Looking at the properties of System.Web.Mvc I can see that it is set to Copy Local = True

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I tried a few different things to try to get the assembly to be copied like redoing the nuget install and eventually I toggled the Copy Local to False, saved the project file and then set it back to true. When I looked at the diff of the project file I found an additional property

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This seems to fix the build. When I checked this in and rebuild, System.Web.Mvc now appears in the zip file. The build was then release to Azure and the web app worked correctly.

Windows 10 IoT core project issues when upgrading to VS2015RTM

Just updated my VS2015 to RTM and tried to load in my blinky Iot Project for Raspberry Pi 2. It didn’t load and I was informed that the project required updating

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Right clicking on the project offers the option to download updates

Selecting this takes you to:

https://msdn.microsoft.com/en-us/library/windows/apps/xaml/mt188198.aspx

It looks like all I can do is to create a new blank project and copy the existing project files over.

Created a new project and copied the contents of MainPage.xaml.cs and MainPage.Xaml over the contents of the files created in the new project. I found it was quicker to do this than to copy the files over manually. Also, change the namespace (if you created a project with a different name) in both MainPage.xaml.cs and MainPage.xaml. Add in all other files you are using by right clicking on the project and clicking Add Existing Items…

Need to add the following reference:

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In the project properties: I selected remote debugger and entered the ip address of my raspberry pi.

When I tried to debug the deployment failed because the version of the remote debugger on the raspberry pi2 was out of date. In order to upgrade it I needed to also upgrade my Windows 10 to the latest version.( https://ms-iot.github.io/content/en-US/win10/SetupPCRPI.htm ) then reflash my raspberry pi 2 sd card ( https://ms-iot.github.io/content/en-US/win10/SetupRPI.htm)

I first updated my Win 10 VM but when I ran the WindowsIoTImageHelper it would not recognise the SD card of the host machine and I couldn’t seem to force it to use the SD card on the host. I then updated my surface Pro to the latest Windows 10 and repeated the process to reflash my Pi.

With all the upgrades completed my project now deploys and runs fine on my updated Raspberry PI2.

Issues setting up Raspberry Pi, Windows 10 IoT core and Visual Studio on a Windows 10 VM

After setting up my Surface Pro with Windows 10 and IoT core I decided that in order to demo it all I needed a Windows 10 VM with it all on. I had a couple of issues that I didn’t get on my Surface Pro.

The first issue I had was that the Windows IoT core watcher application would not run properly and kept shutting down. This is a known bug and has a work around:

Launch the "Developer Command Prompt for VS2015" as Administrator
change the working directory over to "C:\Program Files (x86)\Microsoft IoT"
sn -Vr WindowsIoTCoreWatcher.exe
corflags WindowsIoTCoreWatcher.exe /32BIT+ /FORCE

 

The second issue was Visual Studio couldn’t connect to TFS online. When I tried to manage connections I got the following error:

SplitterDistance must be between Panel1MinSize and Width - Panel2MinSize.

This seems to happen on both VS 2015 Enterprise RC and Community RC editions. I found a work around as follows:

Open up Team Foundation Server online at <youraccount>.visualstudio.com. Click code, then navigate to the project you want to open, click on the solution file which then opens the solution in the web editor. Click the visual studio icon and VS opens with the team project now in team explorer. Close VS and open it again and your team project should still be  connected to team explorer

 

Now with Visual Studio working I needed to set Windows into developer mode. This can be done as follows:

Start->settings->Update & Security -> For Developers. However, when I tried this the setting page kept closing. You can also use the Group Policy editor (Gpedit.msc) as follows:

https://msdn.microsoft.com/en-us/library/windows/apps/dn706236.aspx

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Getting Started with Raspberry Pi 2 and Windows 10 IoT Core

I've got my Raspberry Pi 2 this week and promptly downloaded the Windows 10 IoT core for it.

Scott Hanselman's blog post covers most of what you need to get started

http://www.hanselman.com/blog/SettingUpWindows10ForIoTOnYourRaspberryPi2.aspx

I've summarised the bits that I either didn't read properly or had to go searching for :-)

Download the Windows 10 IoT core and follow the instructions here: http://ms-iot.github.io/content/win10/SetupRPI.htm

In the zip file that is downloaded there is also an MSI file. Install this on your dev machine and you will get an IoT Watcher application that shows all devices on your network. It shows you all the details you need to remote debug your IoT Core device. If you right click on the device you can copy the ip address. This was really useful for this because the only display I could connect my Pi to was my TV (Mainly due to having the wrong cables or no hdmi port on my monitors). Although it was quite impressive to see such a small device on a big screen, it wasn't very practical, plus I keep getting kicked off as the family want to use it to actually watch TV! I'm going to get myself a cheap small monitor just for my Pi. The IoT Watcher application allowed me to check that the Pi was running and also to get its IP address

In order to configure your device including changing the password and setting the machine name the following commands are useful

http://ms-iot.github.io/content/win10/samples/PowerShell.htm

To get started developing for your device download the samples from here: https://github.com/ms-iot/samples

I started with the Blinky sample and this can be the basis for your applications, I picked this one as it shows how to use the GPIO to control something. When this is loaded in Visual Studio 2015 the MainPage.Xaml.cs file is where all the work is done. InitGPIO() sets up the pins for connecting the LED to and there is a timer that ticks to turn the LED on and off

Debugging the application can be done directly on the device and this needs configuring. In order for this to deploy you need to ensure that authentication is turned off in VS as won’t deploy otherwise. When setting the device in VS, I could not get the device to appear in the search tool so I manually configured it with its IP address. This can be done (or to change the device) in the debug section of project properties. Once deployed you can set break points in the code which is running on the device and debug it remotely.

Now I've got that working I've dusted off my soldering iron and the rest of my electronics kit and I am off to play. More later.

5 Tips for using Azure Web Jobs

1. Use public on the main program class.In order for web jobs to initialise correctly the main class that contains the web jobs needs to be made public. Once this has been added the individual jobs can then be read and should be visible in the output when running locally.

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2. In order to store and view the invocation details for each web job you need to configure AzureWebJobsDashboard in the configure tab of the website you have deployed the web job to. Even if you have configured this in your app.config file.

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If this is not configured in the website then you will receive the following error when you try and view the web jobs dashboard

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3. Debug using Visual Studio. Once of the nice features of the web jobs SDK is the ability to run and debug the web job locally in Visual Studio. Following the Getting Started guide, you create a console application which you can debug in Visual Studio before deploying it to Azure

4. User TextWriter for debugging. The Azure Web Jobs SDK (see the logging section) provides a mechanism to log out information that can be viewed through the Azure Web jobs dashboard. By adding a TextWriter as an input parameter to your web job method, you can use WriteLine to then output information you wish to log.

5. Make your Blob Triggers more efficient by triggering them using BlobOutput. The mechanism that the BlobInput trigger uses has a 10-20 minute lag before the trigger can fire, but each time BlobOutput is used it triggers a rescan for Blob input.

“There is an optimization where any blob written via a [BlobOutput] (as opposed to being written by some external source) will optimistically check for any matching [BlobInputs],” See How does [BlobInput] work?. Storage Queues and Service Bus topics and Queues are generally processed within seconds so if you can use a queue to trigger a BlobOutput then use this to trigger any subsequent BlobInputs

Windows Azure Websites, Web API and SignalR

One of our projects involves a web service that implements both SignalR and Web API and we were looking at the quickest and most cost effective way to get it deployed so that one of our customers could run a Windows 8 application as a demo away from the office. The application works well internally as we have the service deployed on one of our servers on IIS. The options we were considering were:

  1. Package the application up in an install package, ship this to our customer and then provide them with instructions and support to allow them to deploy and configure their application
  2. Deploy it on one of our servers and then publish the service through our firewall
  3. Deploy as a Cloud service in Windows Azure
  4. Deploy as a website in Windows Azure

We considered the fact that the first option would probably take us a fair amount of time to make a deployment package, test it and provide enough documentation and support to allow our customer to deploy it on their servers. The other 3 options involved us doing a smaller amount of work, but at least we could get everything working well before shipping the demo out. Option 2 would mean using our internal resources for something that would not be used that often but we would not necessarily know whether and when it was being used so the resources would need to be kept running limiting our capacity internally. Windows Azure was a good fit for this application and the choice was really between setting up a cloud service or use a web site, I guess we could have set up a virtual machine hosted in Windows Azure, but this was a bit excessive just for a simple web service. The two remaining options were to set up a cloud service by creating a web role in deploying to Windows Azure or to use Websites. The cloud service would involve more work for us as we would need to change the project to add in the cloud service project and web role and then do a full PaaS deploy to Windows Azure. This would then utilise a whole virtual machine (although we would have used an Extra Small instance), but the web sites seem a sensible option especially as we already have a number of them available for free. How easy was this going to be and will both Web API and SignalR work with Windows Azure Websites, especially as we were using preview software. I was surprised about how easy this was to deploy and I’ll walk through the process we went through.

Step 1: Make sure that the service runs locally,

Step 2: Our service uses Code First Entity Framework using a local SQL server. Create a database using Windows Azure SQL Server via the Windows Azure Management portal (https://manage.windowsazure.com), the copy the ADO.NET connection string.

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Paste this into your web config file of the web api service. You will need to make sure that the Windows Azure SQL Server firewall has your public IP address configured and you will need to make sure that your firewall will allow connections through port 1433. Now run your application and make sure that you can connect to the Windows Azure SQL database. As we are using Code First Entity Framework, the database tables were created for me so I didn’t need to do any database deployment. The only issue I had with this approach was that I had to create the database first in Windows Azure.

Step 3: With our service running locally but with the database in Windows Azure we are now ready to deploy to the cloud. In the Windows Azure Management portal, click the “New” button

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The “Quick Create”, enter the url you want to use and click “Create Web Site”

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Step 4: We now need to deploy our service. In the Azure management portal, navigate to the web site you just created and click “Download Publishing Profile”. Save this to your computer.

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In Visual Studio 2012, open your web api project, right click on the project in Solution Explorer and click publish.

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This will display the publish dialog.

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Click the import button and navigate to the folder where the publish profile was saved. This should then allow you to complete the wizard

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Click Next and check to make sure the correct connection string is displayed, click Next then Publish. This should then start to upload your web api project to the Windows Azure Website. The deploy should be relatively quick and no where near the time it takes to deploy a cloud service. When completed, your deployed website should start in the browser and you can carry out whatever tests you need.

Step 5: With your website deployed you should just need to change the url of your service in the Window 8 application.

This whole process took less than 10 minutes to setup and deploy. One of the nice features of using websites is that changes are quick to deploy.

We had a number of issues to get this all working fully:

  1. As I mentioned earlier we had to ensure that the database was created before the EF code would create the correct tables
  2. When we first ran the Windows 8 application we were getting an error each time we tried to use SignalR. We received an “Incompatible protocol version”. This was because I installed the latest SignalR libraries on the server side code but the client was using an older version. You need to make sure that both the client and server are using the same version of SignalR
  3. We also had an issue when deployed to Windows Azure where it looked like the SignalR hubs were not being created correctly. It looked like the hub creation was hanging and not returning. This is a known issue that has been fixed but not yet deployed to Azure. There is a work around which is to configure SignalR to use long polling (https://github.com/SignalR/SignalR/issues/510). We did that with the following code:
   1: hubConnection = new HubConnection(App.SignalRUrl);            
   2: proxy = App.hubConnection.CreateHubProxy("statushub");
   3: App.hubConnection.Start(new LongPollingTransport()).Wait();

Windows Azure Web Sites is not just for web sites, using it also for services can make a lot of sense as the scaling model will allow a lot of flexibility and can provide a cost effective way to host your services, especially if they are not heavily loaded at the start. They are also easy and fast to deploy which is always a bonus Smile