Steve Spencer's Blog

Blogging on Azure Stuff

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.


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.


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


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 and SignalR with Gadgeteer

I’ve been playing with Gadgeteer ( for a while now and I am a big fan of the simple way we can build embedded hardware applications with high functionality. We have a proof of concept device that includes a Colour touch screen, RFID reader and an Ethernet connections. This device is capable of connecting to a web api REST service which we have hosted in Windows Azure and we can use this service to retrieve data from our service depending upon the RFID code that is read. This works well but there are times when we would like to notify the device when something has changed. SignalR seems to be the right technology for this as it removes the need to write polling code in your application.

Gadgeteer uses the .Net Micro framework which is a cut down .Net framework and doesn’t support the ASP.NET SignalR libraries. As we can use web api using the micro framework using the WebRequest classes,  I wondered what was involved to get SignalR working on my Gadgeteer device.

The first problem was to work out the protocol used by SignalR and after a short while trawling the web for details of the protocol I gave up and got my old friend fiddler out to see what was really happening.

After creating a SignalR service I connected my working example to the signalR hub running on my local IIS..

The first thing that pleased me was that the protocol looked fairly simple. It starts with a negotiate which is used to return a token which is needed for the actual connection.

GET /signalr/negotiate?_=1369908593886

Which returns some JSON:


I used this JSON to pull out the connection id and connection token. This was the first tricky part with the .Net Micro framework. There is not the same support for JSON serialisation you get with the full framework plus the string functions are limited as well. For this I used basic string functions using Substring and IndexOf as follows:

int index = negJson.IndexOf("\""+token+"\":\"");
if (index != -1)
    // Extracts the exact JSON value for then name represented by token
    int startindex = index + token.Length + 4;
    int endindex = negJson.IndexOf("\"", startindex);
    if (endindex != -1)
        int length = endindex - startindex;
        stringToExtract = negJson.Substring(startindex, length);

With the correct token received Fiddler led me to the actual connection of signalR:

GET /signalr/connect?transport=webSockets&connectionToken=yourtoken&connectionData=%5B%7B%22name%22%3A%22chathub%22%7D%5D&tid=2 HTTP/1.1

Looking at this I could determine that I needed to pass in the token I retrieved from negotiate, the transport type and the name of the hub I want to connect to. After a bit of investigating I used the transport of longPolling.

Now as I think I understood the protocol, I tried to implement it in SignalR. The first issue that arose was what to send with the negotiate call. I figured that this was some sort of id of the client that is trying to connect so I decided to use the current tick count. This seemed to work and I guess that as long as my devices don’t connect at exactly the same time then Signal R would work. I’ve had no problems so far with this.

Upon connecting to the hub I needed to create a separate thread to handle signalR so that the main device wouldn't stop running whilst the connection to the SignalR hub was waiting for a response. Once a response is received the response returns with a block of JSON data appropriate to the SignalR message being received. This needs to be decoded and passed onto the application. You then need to reconnect back to the SignalR hub. The period between receiving data and then reconnecting back to the hub needs to be small. Whilst the message is being processed it cannot receive any more message and may miss some data. I retrieve the response stream and then pass the processing of the stream to a separate thread so that I can reconnect to the hub as fast as possible.

This is not a full implementation of SignalR on the .Net Micro-framework but it is the implementation of a simple client and can be used fairly successfully on the Gadgeteer device. I still need to do a little more work to try to speed up the connections as it is possible to miss some data.

The SignalR hub is hosted on a Windows Azure website along side the web api service which allows both web, Windows 8 and Gadgeteer applications to work side by side.

Gadgeteer has opened up another avenue for development and helps us to provide more variety of devices in a solution

Gadgeteer, Ethernet and Windows Azure

I was having problems getting my Gadgeteer ethernet card initialised and running. I wanted to set it up to use DHCP but I never got an IP address assigned. I am using a GHI Electronics J11D ethernet card and browsing for examples seemed to pull up a lot of code but none of it seemed to work or the code didn’t seem to match what the libraries were providing. I eventually found the solution.

// Wire up the event handler to notify when the ip address has been assigned 
// and the port is ready to use
ethernet_J11D.Interface.NetworkAddressChanged += new
Interface_NetworkAddressChanged); // Open the ethernet port ethernet_J11D.Interface.Open(); // Assign the network stack to the ethernet card if (!ethernet_J11D.Interface.IsActivated) { NetworkInterfaceExtension.AssignNetworkingStackTo(ethernet_J11D.Interface); } // Turn on DHCP and Dynamic DNS ethernet_J11D.Interface.NetworkInterface.EnableDhcp(); ethernet_J11D.Interface.NetworkInterface.EnableDynamicDns();

It was the line (NetworkInterfaceExtension.AssignNetworkingStackTo(ethernet_J11D.Interface); ) that was the issue, once that was in everything worked fine.

I can now connect to my Windows Azure Websites hosted web api/signalR service.

The code for this is fairly standard and once I got the connection it worked well. The code below shows you how to call the web api service from Gadgeteer. This method works for both GET (read) and PUT (update) requests.

private string CallWebservice(string fn, bool put, string data)

string responseFromServer ;
    // Create a request for the URL. 
    WebRequest request = WebRequest.Create(url + fn);

    // set a timeout of a nice big value - 10 minutes
    request.Timeout = 600000;
    if (put)
        request.Method = "PUT";
        System.Text.UTF8Encoding encoding = new System.Text.UTF8Encoding();
        byte[] arr = encoding.GetBytes(data);
        request.ContentType = "application/json";
        request.ContentLength = arr.Length;
        Stream requestStream = request.GetRequestStream();
        requestStream.Write(arr, 0, arr.Length);


    // Get the response.
    WebResponse response = request.GetResponse();

    // Get the stream containing content returned by the server.
    Stream dataStream = response.GetResponseStream();

    // Open the stream using a StreamReader for easy access.
    StreamReader reader = new StreamReader(dataStream);

    // Read the content.
    responseFromServer = reader.ReadToEnd();

    // Tidy up
catch (Exception ex)

return responseFromServer ;



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 (, the copy the ADO.NET connection string.


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


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


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.


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


This will display the publish dialog.


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


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 ( 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