Using the TryGet pattern in C# to clean up your code

Modern C# allows you to declare output variables inline; this has a subtle benefit of making TryFoo methods more attractive and cleaning up your code. Consider this:

public class FooCollection : ICollection<Foo>
  // ICollection<Foo> members omitted for brevity
  public Foo GetFoo(string fooIdentity)
    return this.FirstOrDefault(foo => foo.Identity == fooIdentity);

// somewhere else in the code
var foo = foos.GetFoo("dave");
if (foo != null)

Our GetFoo method will return a default of Foo if one isn’t found that matches fooIdentity — code that uses this API needs to know that null indicates that no matching item was found. This isn’t unreasonably, but it does mean that we’re using two lines to find and assign our matching object. Instead, let’s try this approach:

public class FooCollection : ICollection<Foo>
  public bool TryGetFoo(string fooIdentity, out Foo fighter)
    figher = this.FirstOrDefault(foo => foo.Identity == fooIdentity);
    return fighter != null;

We’ve encoded the knowledge that null means “not found” directly into our method, and there’s no longer any ambiguity about whether we found our fighter or not. Our calling code can now be reduced by a line:

if (foos.TryGetFoo("dave", out foo))

It’s not a huge saving on its own, but if you have a class of several hundred lines that’s making heavy use of the GetFoo method, this can save you a significant number of lines, and that’s always a good thing.

Lose your self-respect with async

How many times have you written code like this in Java/TypeScript?

function saveData() {
  const self = this;
  $.post("/api/foo", function (response) {

The self variable is used to keep a reference to the real calling object so that, when the callback is executed, it can actually call back to the parent (if you used this, then its value would change as the callback executes).

Enter async! Suddenly, you can write:

function saveData() {
  await $.post("/api/foo");

That’s an awful lot of lines that you’ve just saved across your codebase!

Ditching typings for NPM @types

Managing TypeScript type files (*.d.ts) for third-party libraries has been a pain for a while; in the distant past of last year, I used the NPM package tsd, which has since been superseded by typings. Neither of these felt particularly nice to use, and I’ve been passively searching for alternatives.

The other day, I found out that NPM has typings support built-in! For example, to install JQuery types, one simply runs:

npm install --save-dev @types/jquery

Boom! If we look under node_modules, we see:

  • node_modules
    • @types
      • jquery
        • index.d.ts

It’s a wonderful thing. But wait! Now TypeScript, or rather Visual Studio, doesn’t know where to find the typings! Horror, whatever shall we do? Not to worry, turns out that TypeScript has us covered. In tsconfig.json, we simply add:

  compilerOptions: {
    typeRoots: [ "node_modules/@types" ]

(You may need to close/open the project a few times before VS gets the message!)

So it’s goodbye typings – one less tool to worry about on the chain.

SUNrise architecture – Part 1

I recently promised Twitter that I’d blog about the architecture of SUNrise.

Caveat: this won’t be an exhaustive document, partly for reasons of confidentiality, and partly because I’m writing this in the hour or so between putting my son to bed and the time where the tumbler of whisky next to me finally sends me to sleep.

A bit of background: SUNrise is an enterprise Graphics Lifecycle Management platform, written in-house at Sun Branding Solutions using (primarily) .NET and Microsoft Azure. It replaces our previous flagship product, ODIN, which dates from the early 2000s and runs on a combination of COM+, VB6 and Microsoft Project (yes, really). We began writing SUNrise in late 2013, although prototypes were kicking around since late 2012.

We were fortunate enough to start work on SUNrise just as Microsoft Azure was becoming an attractive platform. We began using Cloud Services, but have since moved to using App Services (formerly Websites).

SUNrise technology map

Our core data platform is SQL Azure, although we are increasingly starting to add de-normalized lookup data into Azure Table Storage, and we maintain a separate search index using Azure Search. We maintain (and have had to use!) a read-only replica of our core database in another region, and, apart from failover in the event of SQL Azure outages (yes, they have happened), we use this as the data source for our ETL processes to avoid clogging up the transactional system.

Diagram showing the logical architecture of SUNrise

By using Azure Blob Storage, we can provide highly scalable binary storage for our clients without having to buy the storage up-front – we pay for what we use and factor this into our pricing model. Using the storage APIs means that we can simply keep pushing files into storage, without worrying about folder or file limits or path length issues – under the covers, we simply assign each binary file a GUID, and use that as the URI pattern.

SUNrise is a distributed application, and consists of several websites, hosting various parts of the logical application from the core customer-facing website, to the login screen or the integration API. Each of these are hosted as an App Service, backed by a hosting plan with a minimum of two instances. The diagram below shows how we use a mixture of hosting plans of various sizes, from a single large plan running a single site, to a smaller plan hosting a mixture of lesser-used or less-intensive applications. The joy of using Azure is that changing this layout is a matter of configuration rather than ordering new physical hardware.

App service hosting plan layout

As well as customer-facing web applications, we run background processes on WebJobs, using a mixture of continuous and scheduled processes. By abstracting the plumbing of receiving queue messages, we have been able to write durable and reliable queue processors and task schedulers with very little code (the actual processes that they kick off are a different matter!).

Other technologies used include Redis Cache, SSIS, ApplicationInsights and Cloud Services.

The application is written in .NET 4.6, but we are actively porting our code to .NET Core 1.0 (a process that we’ll complete with the release of Visual Studio 2017). We aim to use mostly POCOs and don’t rely on any one framework; to that end, we’re gradually moving towards Dapper for data access, and away from Entity Framework.

We use a wide range of .NET technologies, from EF to WF, WCF, WebAPI, MVC and Razor.

The “secret sauce” of SUNrise is the workflow engine, a custom-built domain-specific language for modelling and running our customers’ business processes. For scalability, we run most of the intensive processing for this in a background WebJob using Storage Queues to pass messages between the application and processing tiers. By using a competing consumers model and idempotent/stateless messages, we can easily scale this system up by increasing the number of instances within the Hosting Plan, and in fact we do this automatically, so that higher volumes of messages in the queue will spin up more servers to handle them.

Development Environment

Our developers all run Visual Studio 2015 Enterprise Edition, and work on their own laptops against local databases. We use a combination of SSDT and FluentMigrator to model our data layer, the upshot of which is that developers can build a local copy of the database with a single command, so that each developer is working on their own segregated data island. Where certain services aren’t available locally (such as Azure Search), we emulate them using the next-best equivalent (in the case of Azure Search, we run ElasticSearch locally to provide a similar environment, and perform more detailed integration testing against a testing Azure subscription).

We all run SQL Server 2016 Developer Edition on our machines, as well as the Azure Storage Emulator, and various services such as Redis and Papercut (to emulate local SMTP).

We host our source code, CI builds, release and test automation on Visual Studio Team Services, but that’s a subject for another blog post!

Using PowerShell to update DotNet Core version numbers

The problem: I have a DotNet Core package that I would like to build and publish to an internal NuGet feed using Visual Studio Team Services. If I was using a .nuspec or .csproj file, I could set the version number of the package during the build, but DotNet Core doesn’t let me do this.

The solution: Write a very small PowerShell script that will update project.json with a new version number, then plug that into the build.

The script

$project = Get-Content $path | ConvertFrom-Json
$project.version = $version
ConvertTo-Json -InputObject $project -Depth 32 | Out-File $path

So, what’s going on here? Not a lot: we’re reading project.json into an object, then modifying the version property (if you do this from command-line, you even get intellisense for project.json!), and then finally re-serializing the object to over-write the original file.

Annoyingly, this will screw up the formatting of project.json, but you don’t actually care about this because this file will only live for the duration of the build, and will never get back into source control.

Plugging it into VSTS

I’ve added a build variable to store the desired version number:

Package.Version = 1.0.$(Build.BuildId)-*

Then I’ve added a new PowerShell build step into the build as the first step. I’ve saved my file as Set-DotNetVersion.ps1, so we set up the following arguments:


That’s it! If you then call dotnet pack on your library, it’ll create a NuGet package with the version number that you specified above. My full build pipeline is:

  • PowerShell Script
  • Dotnet restore
  • Dotnet pack
  • Publish build artifacts

Custom Authentication in ASP.NET MVC Core

ASP.NET Core has really good out-of-the-box support for authorization and authentication via ASP.NET Identity. However, sometimes that’s not enough, and you need to roll your own logic.

In my case, I was writing an API for sending emails, which many different clients would connect to. Each client would be given an “API Key” that would identify and authorize their requests. I could have implemented this using HTTP Basic authentication, or using OAuth tokens, but instead I thought it’d be good to get my hands dirty in the base classes.

So, the scenario is that a client sends a request with a known header value, as in:

$Headers = @{
    Authorization = "abcdefg1234567"

$Data = @{
    To = "";
    From = "";
    Subject = "Hello!";
    Body = "How you doing?"

Invoke-WebRequest -Uri "" -Headers $Headers -Data $Data

The actual value of the key and the logic behind it isn’t relevant to this article (I’m using RSA private keys under the hood), but the point is that we have a method in our code to verify the authentication key.

To do this, we need to implement custom authorization middleware. This will be composed of three parts:

  • The middleware class
  • The middleware options
  • The authentication handler

The middleware inherits from Microsoft.AspNetCore.Authentication.AuthenticationMiddleware<TOptions>, where TOptions inherits from Microsoft.AspNetCore.Builder.AuthenticationOptions. It’s responsible for building new instances of our authentication handler, and for injecting any required dependencies into the handler. For the purposes of this example, let’s suppose that I have an interface to validate my API keys, like so:

public interface IApiKeyValidator
    Task<bool> ValidateAsync(string apiKey);

Let’s assume that I’ve implemented this somehow (maybe using Azure KeyVault), so my challenge now is to hook my custom logic up to MVC, so that its built-in authentication can kick in. The end result is that I can decorate my controllers with:

[Authorize(ActiveAuthenticationSchemes = "apikey")]

You can think of the middleware as the glue that binds the MVC framework with our business logic. We could start by writing:

public class ApiKeyAuthenticationOptions : AuthenticationOptions
    public const string DefaultHeaderName = "Authorization";
    public string HeaderName { get; set; } = DefaultHeaderName;

public class ApiKeyAuthenticationMiddleware : AuthenticationMiddleware<ApiKeyAuthenticationOptions>
    private IApiKeyValidator _validator;
    public ApiKeyAuthenticationMiddleware(
       IApiKeyValidator validator,  // custom dependency
       RequestDelegate next,
       IOptions<ApiKeyAuthenticationOptions> options,
       ILoggerFactory loggerFactory,
       UrlEncoder encoder)
       : base(next, options, loggerFactory, encoder)
        _validator = validator;

    protected override AuthenticationHandler<ApiKeyAuthenticationOptions> CreateHandler()
        return new ApiKeyAuthenticationHandler(_validator);

This is all just glue code. The real meat lies in ApiKeyAuthenticationHandler, which can be stubbed out as follows:

public class ApiKeyAuthenticationHandler : AuthenticationHandler<ApiKeyAuthenticationOptions>
    private IApiKeyValidator _validator;
    public ApiKeyAuthenticationHandler(IApiKeyValidator validator)
        _validator = validator;

    protected override Task<AuthenticateResult> HandleAuthenticateAsync()
        throw new NotImplementedException();

As you can probably tell, our logic lives in the HandleAuthenticateAsync method. In here, we can basically do whatever we want – we can inject any dependency that the application knows about through the middleware, and the handler has access to the full request context. We could check the URL, querystring, form values, anything. For simplicity, here’s a really cut-down implementation:

StringValues headerValue;
if (!Context.Headers.TryGetValue(Options.HeaderName, out headerValue))
    return AuthenticateResult.Fail("Missing or malformed 'Authorization' header.");

var apiKey = headerValue.First();
if (!_validator.ValidateAsync(apiKey))
    return AuthenticateResult.Fail("Invalid API key.");

// success! Now we just need to create the auth ticket
var identity = new ClaimsIdentity("apikey"); // the name of our auth scheme
// you could add any custom claims here
var ticket = new AuthenticationTicket(new ClaimsPrincipal(identity), null, "apikey");
return AuthenticateResult.Success(ticket);

I’ve kept this example simple, but at this point you have to power to construct any sort of claims identity that you like, with as much or as little information as you need.

Finally, we just need to tell MVC about this middleware in Startup.cs:

public void ConfigureServices(IServiceCollection services)
    // the implementation of this is left to the reader's imagination
    services.AddTransient<IApiKeyValidator, MyApiKeyValidatorImpl>();
    // etc...

public void Configure(IApplicationBuilder app, IHostingEnvironment env, ILoggerFactory loggerFactory)
    // etc...

And that’s it! Custom business logic, dependency injection and MVC all working together beautifully.

Typescript interfaces for C# developers

Or, how not to make the mistakes I made with Typescript.

As a long-time .NET developer, I took the plunge into TypeScript a couple of years ago after much uhm-ing and ah-ing. I learned that you could write interfaces in TypeScript, and I immediately starting doing them wrong.

In .NET, an interface is something that you expect to be implemented in a class. For example:

public interface IFoo {
    string Bar { get; }
    string Baz(string bar);

public class FunkyFoo {
    public string Bar { get; set; }
    public void Baz(string bar) => $"Hello {bar}";

You might code against the interface, but you would only really create interfaces if you expected several different concrete classes to implement that contract.

When I started writing TypeScript, I wrote interfaces in much the same fashion:

interface IFoo {
    string Bar;
    Baz(bar: string);

class FunkyFoo {
    public Bar: string;
    public Baz(bar: string): string {
        return `Hello ${bar}`;

The problem is that, while this works, it’s not really giving you the full benefit of TS interfaces. TypeScript, being a super-set of JavaScript, is a functional language – unlike .NET, the classes aren’t the most important thing in it. Using the approach above, I was writing code like:

let foo: Array<IFoo>;
$.getJSON("foo/bar", json => {
    for (let i = 0; i < json.length; i++) {
        foo.push(new FunkyFoo(json[i]));

Ugh. Horrible and messy. If I’d used interfaces properly, I’d have something like this:

interface Foo {
  bar: string;
  baz: string;

// ...

let foo: Array<Foo>;
$.getJSON("foo/bar", json => {
    foo = json;

The realisation that dawned on me was that interfaces are just data contracts – nothing more. Due to the loose typing of JavaScript, I could quite happily say that an object was of type Foo, without doing any conversion.

So, what should I have been using interfaces for? Well, firstly, data contracts as seen above – basically just a way to define what data I expect to get from/send to the server. Secondly, for grouping sets of repeated parameters, as in:

function postComment(email: string, firstName: string, lastName: string, comment: string) {
  // etc

// becomes:
interface UserInfo {
    email: string;
    firstName: string;
    lastName: string;

// now the method is much cleaner,
// and we can re-use these parameters
function postComment(user: UserInfo, comment: string) {
  // etc

I’ve ended up thinking of interfaces as more akin to records in F# – just basic DTOs. Doing this has actually made my code better – now I have a clean separation between data and functionality, rather than mixing both in the same structure.