Category Archives: .Net

Instrumentation presentation at Campus Days 2013

Campus Days 2013 logoI was fun to present today at Campus Days 2013 in Copenhagen, Denmark. The talk was about how to instrument software by using frameworks like TraceSource, EventSource, Event Tracing for Windows and how to perform post-mortem debugging via Visual Studio and PerfView.

Here is a great resource for enabling diagnostics in Azure.

Automatic Retry and Circuit Breaker made easy

Polly library logoIf you do not know Polly, you are missing out! I did not know about it until a couple of days ago and you properly never heard about it either, as this wonderful little library only has 63 downloads on NuGet at the time of writing.

Polly is an easy to use retry and circuit breaker pattern implementation for .Net – let me show you.
Start by specifying the policy – what should happen when an exception thrown:

  var policy = Policy
    .Handle<SqlException(e => e.Number == 1205) // Handling deadlock victim
    .Retry(3, (exception, retyCount, context) =>
      // Log...

The above policy specifies a SqlExeption with number 1205 or OtherException should be retried three times – if it still fails log and bobble the original exception up the call stack.

  var result = policy.Execute(() => FetchData(p1, p2));

It is also possible to specify the time between retries – e.g. exponential back off:

  var policy = Policy
    .WaitAndRetry(5, retryAttempt =>
      TimeSpan.FromSeconds(Math.Pow(2, retryAttempt)

Or the circuit breaker safeguarding against the same error occurs again and again if an external system is temporarily unavailable:

  var policy = Policy
    .CircuitBreaker(2, TimeSpan.FromMinutes(1));

Go get it – I’m already using it :)

Accessing HTTP Request from ASP.NET Web API

Do you need access to the bare HTTP request in ASP.NET Web API to access custom header etc.? Then add the HttpRequestMessage:

public class CalculatorController : ApiController
  public int Add(HttpRequestMessage requestMessage, int x, int y)
    var accessToken = requestMessage.Headers.Authorization.Parameter;
    // use the HTTP header

    return x + y;

The HttpRequestMessage is automatically bound to the controller action, so you can still execute the action like http://localhost/calculator/add?x=3&y=2

Simple and easy.

GOTO Aarhus 2012 – Tuesday

The morning keynote by Scott Hanselman was about the true power of JavaScript. He argued that JavaScript in the browser is a full operating system running as a virtual machine within the browser – so we should treat it so. Don’t use Java Applets, Flash, Flex or Silverlight as it just another (slow) abstraction upon an already powerfull engine – the browser. It was a great talk leading up to the pre-release of TypeScript.

I followed a couple of sessions the continuous delivery by Sam Newman, Michael T. Nygard (author of Release It) and Jez Humble (author of Continuous Delivery).
Continuous Integration is a prerequisite of Continuous Delivery, but many still don’t use apply Continuous Integration to their solution, with daily incremental check-ins, automated build and unit tests.

To simplify Continuous Delivery, everything must be automated. To ease the task of automation, things must be simplified. To simplify, start by decomposing the system into manageable pieces, so each can be deployed separately. How?
Decompose the system into disconnected services makes it easier to deploy a subset of the system. This limits the impact of a deployment. It even makes it possible to mitigate the risk further by making small incremental changes by only deploying one subsystem at the time.

These services have to be structured as application silos and share nothing, not even the database schema.

By automating and decomposing your system into disconnected application silo services you too can do Continuous Delivery.
After the conference the GOTO Aarhus guys had joint up with the local community and user groups to hos open sessions. I attended the ANUG (Aarhus .NET User Group) session with Anders Hejlsberg. He presented the brand new TypeScript – a superset of JavaScript that compiles into plain JavaScript and runs in any browser (similar concept as CoffeeScript). It has great tooling support in Visual Studio with intelliSense and static verification.

I’m looking forward to the last day of the conference tomorrow.

GOTO Aarhus 2012 – Monday

The day started with a keynote from @Falkvinge from the Pirate Party. I wasn’t expecting much from this keynote, but I was pleasantly surprised. First of all, I assumed that I knew quite a bit about the Pirate Party – I was wrong! Facts: the Pirate Party is present in 150 countries and has 2 European Union parliament members. These guys are serious and not just a protest party wanting to legalize sharing copyrighted material. They are fighting the problems with limiting access to knowledge and ideas. They are emphasizing that exclusive right like patents, copyright and subsidizing are counterproductive. That’s so true! @Falkvinge disrupted my brain – that’s great, because that is why I’m here!

Next up was great presentation of graph databases by Jim Webber – fast speaking provocative British architect from Neo4J. He (re)spiked my interest in ‘other’ databases and stressed that each type of database like relational, object, key-value stores, document,  graph etc. databases each fit their problem domain. So you shouldn’t just pick RavenDB because it is the new hot think in .Net sphere (or because Ayende aka Oren Eini says so). I will definitely take a look Net4J with the .Net client library Neo4jClient . Another great point from Jim Webber was; ACID does scale (though many claims otherwise), but he stressed it was distributed ACID with 2PC that doesn’t scale.

From then on I attended a couple of unfortunate sessions (not worth mentioning). Now it is time for the conference party where the beer is sponsored by Atlassian.

Using Lucene.Net with Microsoft Azure

Lucene indexes are usually stored on the file system and preferably on the local file system. In Azure there are additional types of storage with different capabilities, each with distinct benefits and drawbacks. The options for storing Lucene indexes in Azure are:

  • Azure CloudDrive
  • Azure Blob Storage

Azure CloudDrive

CloudDrive is the obvious solutions, as it is comparable to on premise file systems with mountable virtual hard drives (VHDs). CloudDrive is however not the optimal choice, as CloudDrive impose notable limitations. The most significant limitation is; only one web role, worker role or VM role can mount the CloudDrive at a time with read/write access. It is possible to mount multiple read-only snapshots of a CloudDrive, but you have to manage creation of new snapshots yourself depending on acceptable staleness of the Lucene indexes.

Azure Blob Storage

The alternative Lucene index storage solution is Blob Storage. Luckily a Lucene directory (Lucene index storage) implementation for Azure Blob Storage exists in the Azure library for Lucene.Net. It is called AzureDirectory and allows any role to modify the index, but only one role at a time. Furthermore each Lucene segment (See Lucene Index Segments) is stored in separate blobs, therefore utilizing many blobs at the same time. This allows the implementation to cache each segment locally and retrieve the blob from Blob Storage only when new segments are created. Consequently compound file format should not be used and optimization of the Lucene index is discouraged.

Code sample

Getting Lucene.Net up and running is simple, and using it with Azure library for Lucene.Net requires only the Lucene directory to be changes as highlighted below in Lucene index and search example. Most of it is Azure specific configuration pluming.

Lucene.Net.Util.Version version = Lucene.Net.Util.Version.LUCENE_29;

    (configName, configSetter) =>

var cloudAccount = CloudStorageAccount

var cacheDirectory = new RAMDirectory();

var indexName = "MyLuceneIndex";
var azureDirectory =
    new AzureDirectory(cloudAccount, indexName, cacheDirectory);

var analyzer = new StandardAnalyzer(version);

// Add content to the index
var indexWriter = new IndexWriter(azureDirectory, analyzer,

foreach (var document in CreateDocuments())


// Search for the content
var parser = new QueryParser(version, "text", analyzer);
Query q = parser.Parse("azure");

var searcher = new IndexSearcher(azureDirectory, true);

TopDocs hits = searcher.Search(q, null, 5, Sort.RELEVANCE);

foreach (ScoreDoc match in hits.scoreDocs)
    Document doc = searcher.Doc(match.doc);

    var id = doc.Get("id");
    var text = doc.Get("text");

Download the reference example which uses Azure SDK 1.3 and Lucene.Net 2.9 in a console application connecting either to Development Fabric or your Blob Storage account.

Lucene Index Segments (simplified)

Segments are the essential building block in Lucene. A Lucene index consists of one or more segments, each a standalone index. Segments are immutable and created when an IndexWriter flushes. Deletes or updates to an existing segment are therefore not removed stored in the original segment, but marked as deleted, and the new documents are stored in a new segment.

Optimizing an index reduces the number of segments, by creating a new segment with all the content and deleting the old ones.

Azure library for Lucene.Net facts

  • It is licensed under Ms-PL, so you do pretty much whatever you want to do with the code.
  • Based on Block Blobs (optimized for streaming) which is in tune with Lucene’s incremental indexing architecture (immutable segments) and the caching features of the AzureDirectory voids the need for random read/write of the Blob Storage.
  • Caches index segments locally in any Lucene directory (e.g. RAMDirectory) and by default in the volatile Local Storage.
  • Calling Optimize recreates the entire blob, because all Lucene segment combined into one segment. Consider not optimizing.
  • Do not use Lucene compound files, as index changes will recreate the entire blob. Also this stores the entire index in one blob (+metadata blobs).
  • Do use a VM role size (Small, Medium, Large or ExtraLarge) where the Local Resource size is larger than the Lucene index, as the Lucene segments are cached by default in Local Resource storage.

Azure CloudDrive facts

  • Only Fixed Size VHDs are supported.
  • Volatile Local Resources can be used to cache VHD content
  • Based on Page Blobs (optimized for random read/write).
  • Stores the entire VHS in one Page Blob and is therefore restricted to the Page Blob maximum limit of 1 TByte.
  • A role can mount up to 16 drives.
  • A CloudDrive can only be mounted to a single VM instance at a time for read/write access.
  • Snapshot CloudDrives are read-only and can be mounted as read-only drives by multiple different roles at the same time.

Additional Azure references

CNUG Lucene.Net presentation

I have just held another presentation about Lucene.Net, this time in Copenhagen .Net user group. I hope everyone enjoyed the presentation and walked away with newfound knowledge how to implement full text search into their applications.

I love the presentations, like this one, where everyone participates in the discussion. It makes the experience so much enjoyable and everyone benefits of the collective knowledge sharing.

The presentation and code samples can be downloaded below:

I recommend the book “Lucene in Action” by Eric Hatcher. The samples in this book are all in Java, but they apply equally to Lucene.Net, as it is a 1:1 port of the Java implementation.

Microsoft Julekalender låge #7 vinder

Yet another blog post in Danish, sorry.

Vinderen af gårsdagens Microsoft Julekalender låge #7 fundet. Vinderen er Gianluca Bosco, som har indsendt følgende WCF klient til servicen:

class Program
    static void Main(string[] args)
        Console.WriteLine("Ready? Press [ENTER]...");

        var factory = new ChannelFactory<Shared.IMyService>(
            new WSHttpBinding(),
            new EndpointAddress("http://localhost:8080/MyService"));

        factory.Endpoint.Binding.SendTimeout = new TimeSpan(0,2,0);

        var names = new[] { "Anders", "Bende", "Bo", "Egon",
            "Jakob", "Jesper", "Jonas", "Martin", "Ove",
            "Rasmus", "Thomas E", "Thomas" };

        var x = from name in names.AsParallel()
                select Do(factory, name);


        Console.WriteLine("Done processing...");

    static string Do(ChannelFactory<Shared.IMyService> factory,
         string name)
        var proxy = factory.CreateChannel();

        var result = proxy.LooongRunningMethod(name);

        return result;

Gianluca har rigtig nok fundet den værste performance synder af dem alle, at man ikke skal instantier en ChannelFactory for hvert kald. Alene denne forbedring kan halvere tiden brugt ved et WCF kald.

Desuden fandt Gianluca den indbyggede fælde i min implementation. Server implementationen kalder Thread.Sleep (mellem 1 og 100 sekunder) for at simulere langvarigt arbejde. Default SendTimout på wsHttpBinding (og alle andre bindings) er 1 minut, hvilket betyder, at klienten vil få en TimeoutException pga. serverens lange arbejde.

Tillykke til Gianluca med hans nye helikopter.

Der er en mindre optimering, som kan forbedre performance yderligere og det er at kalde Open og Close på en Channel explicit. Det skyldes, at der i en implicit Open er thread synchronisation, således at kun én thread åbner en Channel og de resterende threads venter på at Channel er klar.

Hvis du har forslag til yderligere forbedringer, så skriv en kommentar.

Microsoft Julekalender låge #7

Sorry – this post is in Danish.

Dagens opgave handler om Windows Communication Foundation. WCF er kompleks pga. mængden af funktionalitet og kan derfor virke indviklet. Kompleksiteten afspejles også i størrelsen på WCF assembly System.ServiceModel.dll, som er klart den største assembly i hele .Net Framework Class Library (FCL) … selv større end mscorlib.dll.


Implementer en klient til nedstående service, som benytter WSHttpBinding med default settings.

[ServiceContract(Namespace = "")]
public interface IMyService
    [OperationContract(ProtectionLevel =
    string LooongRunningMethod(string name);

public class MyService : IMyService
    public string LooongRunningMethod(string name)
        Console.WriteLine("{0} entered.", name);

        // Simulate work by random sleeping
        var rnd = new Random(
            name.Select(Convert.ToInt32).Sum() +
        var sleepSeconds = rnd.Next(0, 100);
        System.Threading.Thread.Sleep(sleepSeconds * 1000);

        var message = string.Format(
            "{0} slept for {1} seconds in session {2}.",

        return message;

Klienten må meget gerne være smukt struktureret og skal:

  • Implementeres i .Net 3.x eller .Net 4.0
  • Simulere et dusin forskellige klienter
  • Være så effektiv som mulig (tænk memory, CPU cycles, GC)

Beskriv kort jeres valg af optimeringer.

For at gøre opgaven nemmere at løse, så har jeg allerede løst den for jer… dog ikke optimalt. Download min implementation.

Send løsning til anders at inden midnat; vinderen vil bliver offentligt i morgen og vil blive den lykkelige ejer af en fjernstyrret helikopter med tilbehør, så den er klar til af flyve. En cool office gadget. Helikopteren er nem at flyve og kan holde til en del. Det ved jeg af erfaring :-)

Se helikopteren flyve nedefor.