Rockford Lhotka

 Wednesday, August 21, 2019

The new .NET Core 3 release includes support for the gRPC protocol. This is an efficient binary protocol for making network calls, and so is something that CSLA .NET should obviously support.

CSLA already has an extensible channel-based model for network communication via the data portal. Over the years there have been numerous channels, including:

  • .NET Remoting (obsolete)
  • asmx services (obsolete)
  • WCF (of limited value in modern .NET)
  • Http

I'm sure there have been others as well. The current recommended channel is via Http (using the HttpProxy type), as it best supports performance, routing, and various other features native to HTTP and to the data portal channel implementation.

CSLA .NET version 5.0.0 will include a new gRPC channel. Like all the other channels, this is a drop-in replacement for your existing channel.

⚠ This requires CSLA .NET version 5.0.0-R19082107 or higher

Client Configuration

On the client it requires a new NuGet package reference and a configuration change.

  1. Reference the new Csla.Channels.Grpc NuGet package
  2. On app startup, configure the data portal as shown here:
        DataPortal().DefaultProxy(typeof(Csla.Channels.Grpc.GrpcProxy), "https://localhost:5001");

This configures the data portal to use the new GrpcProxy and provides the URL to the service endpoint. Obviously you need to provide a valid URL.

Server Configuration

On the server it requires a new NuGet package reference and a bit of code in Startup.cs to set up the service endpoint.

⚠ This requires an ASP.NET Core 3.0 project.

  1. Reference the new Csla.Channels.Grpc NuGet package
  2. In the ConfigureServices method you must configure gRPC: services.AddGrpc();
  3. In the Configure method add the data portal endpoint:

      app.UseEndpoints(endpoints =>

General Notes

As usual, both client and server need to reference the same business library assembly, which should be a .NET Standard 2.0 library that references the Csla NuGet package. This assembly contains implementations of all your business domain classes based on the CSLA .NET base classes.

The gRPC data portal channel uses MobileFormatter to serialize and deserialize all object graphs, and so your business classes need to use modern CSLA coding conventions so they work with that serializer.

All the version and routing features added to the Http data portal channel in CSLA version 4.9.0 are also supported in this new gRPC channel, allowing it to take full advantage of container orchestration environments such as Kubernetes.

Also, as with the Http channel, the GrpcProxy and GrpcPortal types have virtual methods you can optionally override to implement compression on the data stream, and (on the client) to support advanced configuration scenarios when creating the underlying HttpClient and gRPC client objects.

Wednesday, August 21, 2019 1:37:26 PM (Central Standard Time, UTC-06:00)  #    Disclaimer
 Tuesday, June 25, 2019

Containers and Kubernetes (k8s) are useful for building and deploying distributed systems in general. This includes service-based architectures (SOA, microservices) as well as n-tier client/server endpoints.

I do think container-based runtimes and service-based architecture go hand-in-hand. However, a lot of the benefits of container-based runtimes apply just as effectively to a well-architected n-tier client/server application as well.

By “well architected” I mean an n-tier app that has:

  1. Good separation of concerns between interface, interface control, business, data access, and data storage layers
  2. “Chunky” communication between client and server
    1. A limited number of server endpoints - the n-tier services have been well-considered and are cohesive
    2. Effective use of things like the unit of work pattern to minimize calls over the network by bundling “multiple calls” into a single unit of work (single call)
  3. Efficient use of data transfer - no blind use of ORM tools where extraneous data flows over the network just because it “made things easier to implement”
    1. Focus on decoupling over reuse (two sides of the same coin, where reuse leads to coupling and coupling is extremely bad)

In such an n-tier app, the client is often quite smart (whether mobile, Windows, Mac, WebAssembly, or even TypeScript), and the overall solution is architected to enable this smart client to efficiently interact with n-tier endpoints (really a type of service) to leverage server-side behaviors.

These n-tier endpoints are not designed for use by other apps. They are not “open”. This is arguably a good thing, because it means they can (and should) use much more efficient binary serialization protocols, as compared to the abysmally inefficient JSON or XML protocols used by “open” services.

At the end of the day, the key is that nothing stops you from hosting a n-tier endpoint/service in a container. Well, nothing beyond what might stop you from hosting any code in a container.

In other words, if you build (or update) your n-tier endpoint code to follow cloud-native best practices (such as embracing 12factor design and avoiding the fallacies of distributed computing) - just like you must with microservice implementations - your endpoint code can take advantage of container-based runtimes very effectively.

Now a lot of folks tend to look at any n-tier app and think “monolith”. Which can be true, but doesn’t have to be true. People can create good or bad n-tier solutions, just like they can create good or bad microservice solutions. These architectures aren’t silver bullets.

Look at MVC - a great design pattern - unless you put your business logic in the controller. And LOTS of people write business logic in their controllers. Horrible! Totally defeats the purpose of the design pattern. But it is expedient, so people do it.

What I’m saying, is that if you’ve done a good job designing your n-tier endpoints to be cohesive around business behaviors, and you can make them (at least mostly) 12factor-compliant, you can get container-based runtime benefits such as:

  1. Scaling/Elasticity - quickly spin up/down workers based on active load
  2. Functional grouping - have certain endpoints run on designated server nodes based on CPU, IO, or other workload requirements
  3. Manageability - the same management features that draw people to k8s for microservices are available for n-tier endpoints as well
  4. Resiliency - auto-fail over of k8s pods applies to n-tier endpoints just as effectively as microservices
  5. Infrastructure abstraction - k8s is basically the same (from a dev or code perspective) regardless of whether it is in your datacenter, or in Azure, or AWS

I’ll confess that I’m a little biased. I’ve spent many years talking about good n-tier client server architecture, and have over 22 years of experience maintaining the open source CSLA framework based on such an architecture.

The most recent versions of CSLA have some key features that allow folks to truly exploit container-based runtimes. Usually with little or no change to any existing code.

My key point is this: container-based runtimes offer fantastic benefits to organizations, for both service-based and n-tier client/server architectures.

Tuesday, June 25, 2019 1:47:26 PM (Central Standard Time, UTC-06:00)  #    Disclaimer
 Friday, April 5, 2019

One thing I’ve observed in my career is something I call the “pit of success”. People (often including me when I was younger) write quick-and-dirty software because what we’re doing is a “simple project” or “for just a couple users” or a one-off or a stopgap or a host of other diminutive descriptions.

What so often happens is that the software works well - it is successful. And months later you get a panicked phone call in the middle of the night because your simple app for a couple users that was only a stop-gap until the “real solution came online” is now failing for some users in Singapore.

You ask how it has users in Singapore, the couple users you wrote it for were in Chicago? The answer: oh, people loved it so much we rolled it out globally and it is used by a few hundred users.

OF COURSE IT FAILS, because you wrote it as a one-off (no architecture or thoughtful implementation) for a couple users. You tell them that fixing the issues requires a complete rearchitect and implementation job. And that it’ll take a team of 4 people 9 months. They are shocked, because you wrote this thing initially in 3 weeks.

This is often a career limiting move, bad news all around.

Now if you’d put a little more thought into the original architecture and implementation, perhaps using some basic separation of concerns, a little DDD or real OOD (not just using an ORM) the original system may well have scaled globally to a hundred users.

Even if you do have to enhance it to support the fact that you fell into the pit of success, at least the software is maintainable and can be enhanced without a complete rewrite.

This "pit of success" concept was one of the major drivers behind the design of CSLA .NET and the data portal. If you follow the architecture prescribed by CSLA you'll have clear separation of concerns:

  1. Interface
  2. Interface control
  3. Business logic
  4. Data access
  5. Data storage

And you'll be able to deploy your initial app as a 1- or 2-tier quick-and-easy thing for those couple users. Better yet, when that emergency call comes in the night, you can just:

  1. Stand up an app server
  2. Change configuration on all clients to use the app server

And now your quick app for a couple users is capable of global scaling for hundreds of users. No code changes. Just an app server and a configuration change.

(and that just scratches the surface - with a little more work you could stand up a Kubernetes cluster instead of just an app server and support tens of thousands of users)

So instead of a career limiting move, you are a hero. You get a raise, extra vacation, and the undying adoration of your users 😃

Friday, April 5, 2019 10:38:52 AM (Central Standard Time, UTC-06:00)  #    Disclaimer

How can a .NET developer remain relevant in the industry?

Over my career I've noticed that all technologies require developers to work to stay relevant. Sometimes that means updating your skills within the technology, sometimes it means shifting to a whole new technology (which is much harder).

Fortunately for .NET developers, the .NET platform is advancing rapidly, keeping up with new software models around containers, cloud-native, and cross-platform client development.

First it is important to recognize that the .NET Framework is not the same as .NET Core. The .NET Framework is effectively now in maintenance mode, and all innovation is occurring in the open source .NET Core now and into the future. So step one to remaining relevant is to understand .NET Core (and the closely related .NET Standard).

Effectively, you should plan for .NET Framework 4.8 to become stable and essentially unchanging for decades to come, while all new features and capabilities are built into .NET Core.

Right now, you should be working to have as much of your code as possible target .NET Standard 2.0, because that makes your code compatible with .NET Framework, .NET Core, and mono. See Migrating from .NET to .NET Standard.

Second, if you are a client-side developer (Windows Forms, WPF, Xamarin) you need to watch .NET Core 3, which is slated to support Windows Forms and WPF. This will require migration of existing apps, but is a way forward for Windows client developers. Xamarin is a cross-platform client technology, and in this space you should learn Xamarin.Forms because it lets you write a single app that can run on iOS, Android, Mac, Linux desktop, and Windows.

Third, if you are a client-side developer (web or smart client) you should be watching WebAssembly. Right now .NET has experimental support for WebAssembly via the open source mono runtime. And also a wasm UI framework called Blazor, and another XAML-based UI framework called the Uno Platform. This is an evolving space, but in my opinion WebAssembly has great promise and is something I’m watching closely.

Fourth, if you are a server-side developer it is important to understand the major industry trends around containers and container orchestration. Kubernetes, Microsoft Azure, Amazon AWS, and others all have support for containers, and containers are rapidly becoming the defacto deployment model for server-side code. Fortunately .NET Core and ASP.NET both have very good support for cloud-native development.

Finally, that’s all from a technology perspective. In a more general sense, regardless of technology, modern developers need good written and verbal communication skills, the ability to understand business and user requirements, at least a basic understanding of agile workflows, and a good understanding of devops.

I follow my own guidance, by the way. CSLA .NET 4.10 (the current version) targets .NET Standard 2.0, supports WebAssembly, and has a bunch of cool new features to help you leverage container-based cloud-native server environments.

Friday, April 5, 2019 10:19:15 AM (Central Standard Time, UTC-06:00)  #    Disclaimer
 Friday, January 11, 2019

During 2018 I gave a talk at some VS Live events discussing how one might migrate existing .NET Framework enterprise apps/code to .NET Core. In this talk I have some assumptions I think are reasonable:

  • Most of us can't do a "big bang" rewrite of our apps/code all in one shot
    • It'll take months or years to migrate from .NET to .NET Core
    • During this time it is necessary to maintain the existing code while working on the new code
  • A lot of existing code is still on .NET 2, 3, and 4
  • We're talking Windows Forms, WPF, and ASP.NET code - lots of variety
    • In most cases business logic is embedded in the UI - code-behind forms/pages or in controllers
    • Editorial observation: More people should be using CSLA to gain separation of concerns: keep their business logic in a separate and reusable layer from the UI or data access 😃
  • In most cases you are not just migrating from .NET Framework to .NET Core, but also modernizing/rewriting the UI to also be modern
    • Replacing Windows Forms and WPF with ASP.NET Core Razor Pages or MVC, or Xamarin Forms
    • Maybe upgrading Windows Forms or WPF to the new .NET Core 3.0 support once it is available

Several people have asked if I'd blog the gist of my presentation, so here it is.

In summary:

  • Step 0: Understand .NET Core vs .NET Standard
  • Step 1: Get to .NET 4.6.1 or Higher
  • Step 2: Separation of Concerns
  • Step 3: Move Business Code to Shared Library
  • Step 4: Create .NET Standard Project
  • Step 5: Mitigate Dependency Conflicts
  • Step 6: Mitigate Code Conflicts
  • Step 7: Have a Glass of Bourbon

The code used in my talk and this post is the Net2NetStandard solution on GitHub.

Step 0: Understand .NET Core vs .NET Standard

I've encountered a lot of confusion between .NET Core and .NET Standard and .NET Framework. It is important to have a good understanding of these terms before moving forward at all, so you end up in the right place.

  • .NET Framework is the "legacy" .NET implementation we've been using since 2002, and the long-term goal is to move off .NET Framework onto something more modern
  • .NET Core is a new implementation of .NET that currently supports two types of UI: console and web server. .NET Core 3 is slated to also support Windows Forms and WPF UI frameworks. It does not currently support Xamarin (iOS, Android, Mac, Linux), or WebAssembly (mono-wasm/Blazor).
  • .NET Standard is an interface against which you can write code, and that interface is implemented by .NET Framework 4.6.1+ and by .NET Core 2+ and by Xamarin (and by mono and mono-wasm). If you write your code against .NET Standard, then your compiled DLL can be deployed to .NET Framework, .NET Core, Xamarin, and other .NET implementations.

As a result, my recommendation is that you should always get as much of your code into .NET Standard as possible, because the resulting compiled DLL can run essentially anywhere.

If all you do is get your code to .NET Core, that currently blocks you from reusing that code on .NET Framework, Xamarin, WebAssembly, and other .NET implementations.

All that said, it is important to understand that your UI code will almost certainly be .NET platform specific. In other words, you'll choose to write a console app, a web site, a mobile app, or a desktop app in a specific implementation of .NET. So your UI is not portable or reusable to the same degree as non-UI code.

Your non-UI code should always be built with .NET Standard so it is as portable as possible, enabling reuse of that code in current and future .NET implementations and UI technologies.

This is why my talk (and this post) are about how to get to .NET Standard, not .NET Core. .NET Standard gets you to .NET Core plus Xamarin and other platforms.

Step 1: Get to .NET 4.6.1 or Higher

Version 4.6.1 of the .NET Framework is special, because this is the earliest version that is compatible with .NET Standard 2.0. In reality you'll probably want to get to 4.7.1 or whatever version exists when you start this journey, but the minimum bar is 4.6.1.

Basically, if your existing code won't run on .NET 4.6.1, you'll need to take whatever steps are necessary to get from your older unsupported version (2? 3? 3.5? 4.0? 4.5?) to 4.6.1 or higher.

Fortunately this is usually not that difficult, because Microsoft has done a good job of minimizing breaking changes and preserving backward compatibility over time.

Step 2: Separation of Concerns

This is almost certainly the hardest step: if your existing code is "typical" it probably has tons of non-UI logic in button click or lostfocus event handlers, postback handlers, or controller methods. People have "enjoyed" this style of coding since VB3 back in the early 1990's and it persists through today.

The problem is that moving the UI to .NET Standard is a whole different thing from moving business logic or even data access logic to .NET Standard. Yes, .NET Core 3.0 is planned to have Windows Forms and WPF support, so that should help. But I suspect for most people the migration from .NET Framework to .NET Core ultimately means rewriting the UI into something more modern.

As a result, any code embedded in the UI or presentation layer needs to be cleaned up. You need to apply the concept of separation of concerns and get non-UI code out of the UI. That means no business or data access logic in code-behind or controllers or viewmodels. The goal should be (in my view) that all business logic (validation, calculations, manipulation, rules, authorization) is in a separate business layer, and all data access logic is in its own layer.

In short, you'll have a much easier time migrating code outside the UI to .NET Standard than any code inside the UI.

Step 3: Move Business Code to Shared Library

Now we get to the fun part. This step is in some ways the simplest and yet the most scary.

Right now your code is in a .NET Framework Class Library project. That means it compiles specifically for the .NET Framework, and uses .NET Framework specific dependency references. And this is your existing, running code, so we want to minimize risk in changing it, because changes to this code and existing references and even the csproj file will have a direct impact on your production environment.

The Net2NetStandard solution is intentionally stripped down to the bare minimum. My talk is often a 20 minute lightning talk, so the demo needs to be concise, and this qualifies. The start point is a .NET Framework Class Library project with some existing production code. That code uses Newtonsoft.Json and Entity Framework, with NuGet references to both dependencies.

Importantly, this project is already targeting .NET Framework 4.6.1.

What we want to do is get the code from this project into a location where it can continue to be used to build the existing .NET Framework DLL and also build a .NET Standard DLL. And we want to do this without duplicating the code or files, as that would make maintainability much harder.

Fortunately Visual Studio includes a feature called Shared Projects that solves this issue. A Shared Project is not a normal project at all, it is nothing more than a location to store code files. Those code files are then pulled into a real project at compile time as though they were part of that real project.

To see this in action, add a new C# Shared Project to the solution.

What you'll see in Solution Explorer is that this new project is missing common things like a References or Dependencies node, or a Properties folder. Again, this is not a normal project, it is nothing more than a placeholder to contain code files.

Next, select the source files from the .NET Framework project and drag-drop them into the new SharedLibrary project. That'll copy the files, so there's no risk here.

Before proceeding with any real code, now is the time to make sure you've done a commit to source control so you have an easy way to revert in case something does go wrong!

However, this next step might make your heart race and palms sweat a little, because I want you to highlight and delete the source files from the original .NET Framework project. I know, this sounds scary, but trust me (and your backups).

And here's the key: go to the .NET Framework project and add a reference to the SharedProject.

At this point you can build the original .NET Framework project and you'll get the exact same DLL output as before. Zero changes to your existing code or build result. And yet your code is now in a physical location that'll enable forward movement.

Hopefully your heart has slowed and your palms are now dry 😃

This is the point where you'd do a commit/push/PR of your code to finalize the shift of the files to their new shared project home. All in preparation for the next step where you'll finally get to .NET Standard.

Step 4: Create .NET Standard Project

To recap, you've updated to .NET Framework 4.6.1+, you've moved non-UI code out of the UI to its own class library, and now those code files are in a shared project, while still being compiled by the .NET Framework class library so production is unaffected.

Now you can add a new .NET Standard Class Library project to the solution, the first real step toward the future!

With that done you can add a reference to the same SharedLibrary project so that exact same set of code files will be compiled by this new project as well.

If you try and build the solution or .NET Standard project now you'll find that it won't build. That's because the project is missing some dependencies. However, the original .NET Framework project should keep building fine, production remains unaffected.

Step 5: Mitigate Dependency Conflicts

The new .NET Standard project needs references to Newtonsoft.Json and the Entity Framework, much like the original .NET Framework project. The code makes use of these two packages and won't build without them.

I didn't pick these two dependencies by accident. Newtonsoft.Json has a NuGet package that supports .NET Standard. Entity Framework does not. These two dependencies exemplify likely scenarios you'll encounter with real code. The possible scenarios are that your existing dependencies:

  1. Do not have .NET Standard support, and there's no alternative
  2. Already have .NET Standard support with the current version
  3. Already have .NET Standard support if you upgrade to the latest version
  4. Do not have .NET Standard support, but a new equivalent exists

Scenario 1

Scenario 1 is a worst-case scenario that may be a roadblock to forward movement. If you have a dependency on a DLL or NuGet package that has no .NET Standard support, and there's no modern equivalent to the functionality, then you'll almost certainly have to wait until such support does exist or write it yourself.

Scenarios 2 and 3

If you are in scenario 2, where the existing version of your dependency already has .NET Standard support, then reference the same version in your .NET Standard project as in your exisitng projects and your code should continue to compile and work as-is. This is the simplest scenario.

The dependency may fit into scenario 3, where a newer version of the package supports .NET Standard, but not the version you are currently using. This is quite common with Newtonsoft.Json, where the most commonly used version is quite old, but the more recent versions support .NET Standard.

In this case you may be able to upgrade your production projects to the latest version and use the same version for both .NET Framework and .NET Standard. This incurs some risk to production, because you are upgrading a dependency, but it is often the best solution.

In the case that you can't upgrade the version used by production, you'll need to leave the old package version reference in your .NET Framework project and use a newer version in the .NET Standard project. In this case however, you may have to deal with behavior or API differences between package versions and you should treat this as scenario 4.

Scenario 4

Entity Framework is an example of scenario 4. Microsoft chose not to carry the existing (legacy?) Entity Framework forward. Instead they implemented something new called Entity Framework Core. This new equivalent offers the same conceptual functionality, but with a new implementation and API, so it is absolutely not code-compatible with the old Entity Framework in use in production.

I'll discuss two solutions to scenario 4: compiler directives and upgrading production.

Scenario 4: Compiler Directives

In the .NET Standard project, add references to the latest Newtonsoft.Json and EntityFrameworkCore packages from NuGet.

You'll find that the project still won't build, because the existing code uses the old Entity Framework API. It is an scenario 4 dependency.

But you shouldn't get any errors compiling the code using Newtonsoft.Json, because it is a scenario 2 dependency.

The offending Entity Framework code is in the PersonFactory class:

using System.Data.Entity;

namespace FullNetLibrary
  public class PersonFactory
    public void GetPerson()
      using (var db = new DbContext(""))

There are two problems in this trivial case. First, the namespaces are different, so the using statement is invalid. Second, the API for interacting with entity contexts has changed, so the new DbContext statement is invalid. In a more realistic scenario more parts of the API would be invalid as well.

The goal is to minimize changes and risk to production code, while enabling the .NET Standard code to move forward. Remember that this exact same code file is being compiled for two different targets: once for .NET Framework, and once for .NET Standard (where it fails).

The solution is to use compiler directives so the code file can include code that is only compiled for one target or the other. The first step is to define a constant in the .NET Standard project's Build tab.

You can name the constant whatever you'd like, but NETSTANDARD2_0 is a defacto standard.

Then in your code file you can use this constant in a compiler directive. For example:

using Microsoft.EntityFrameworkCore;
using System.Data.Entity;

What happens here is that when the .NET Framework project builds there's no NETSTANDARD2_0 constant defined, so the compiler only uses the using System.Data.Entity; code. Conversely, when the .NET Standard project builds the constant is defined, so the compiler only uses the using Microsoft.EntityFrameworkCore; code.

At this point you may ask whether this won't get extremely messy to have these #if statements scattered throughout your code. And that is a valid concern. There are three scenarios to consider within a code file:

  1. No code differences exist between the .NET Framework and .NET Core targets
  2. Very few code differences exist between the targets
  3. Many code differences exist between the targets

In scenario 1 you don't need compiler directives, so there's no issue. And that'll happen quite often with business logic, where the use of external dependencies is often very low.

Scenario 2 is a judgment call. What qualifies as "few"? My recommendation is that if 80% of the code is common and 20% is different, then you should use #if statements on a line-by-line or focused block-by-block scenario. This will result in a code file having numerous compiler directives, but most of the code will remain common across both targets.

Scenario 3 is where so much code is different that if you start scattering compiler directives through the code it would become unreadable. Again, my recommendation is that if more than 20% of your code will be different you should consider scenario 3. In this case you should duplicate the code within the file, essentially creating a different set of code for each platform. For example:

using Microsoft.EntityFrameworkCore;

namespace FullNetLibrary
  public class PersonContext : DbContext
    public DbSet<Person> Persons { get; set; }

  public class PersonFactory
    public void GetPerson()
      using (var db = new PersonContext())

using System.Data.Entity;

namespace FullNetLibrary
  public class PersonFactory
    public void GetPerson()
      using (var db = new DbContext(""))

Notice that there's no code that's compiled for both targets. Instead the #if statement is used to create an implementation for .NET Standard, and another implementation for .NET Framework.

In a sense this is the lowest risk solution, because the .NET Framework production code is entirely unchanged. However, it is also the least maintainable solution, because the entire class has been duplicated, so future changes must be made to both sets of code.

Option 3: Upgrading Production Code

There's another alternative to using compiler directives, and that is to upgrade your production code to use the new dependency. This solution is only available in the case that the new NuGet package not only supports .NET Standard, but also supports .NET Framework. EntityFrameworkCore is an example of this, where you can use the new EntityFrameworkCore package from .NET Framework code.

Obviously this solution brings risk, because you are rewriting your existing production code to use the new library. That'll require good unit and acceptance testing of your production code to make sure nothing is broken by the changes.

On the upside, this solution helps keep the common codebase clean and unified. In the Net2NetStandard example, the PersonFactory code can end up looking like this:

using Microsoft.EntityFrameworkCore;

namespace FullNetLibrary
  public class PersonContext : DbContext
    public DbSet<Person> Persons { get; set; }

  public class PersonFactory
    public void GetPerson()
      using (var db = new PersonContext())


Same code for both the .NET Framework and .NET Standard targets. But only if the old Entity Framework reference in the production .NET Framework project is replaced with the new EntityFrameworkCore reference.

This often comes dangerously close to a "big bang" solution, and incurs real risk to the existing software. But there's also a very real upside in terms of maintaining a common codebase for development, testing, and maintenance over time.

Step 6: Mitigate Code Conflicts

The final issue you may encounter is pure code conflicts between your .NET Framework code and what can be done in .NET Standard. This is very uncommon, because .NET Standard describes so much of the functionality normally used by .NET code. However, if you are using some fancy bit of reflection or other "non-mainstream" parts of .NET you could find that your code won't compile for .NET Standard.

Solving this is really the same as Option 3 when dealing with dependency differences: use compiler directives. Or rewrite your "non-mainstream" production code to use techniques that are supported by .NET Standard.

Step 7: Have a Glass of Bourbon

or your beverage of choice

Not that you are done at this point, but you are on the path. In some ways finding the path and getting onto the path is the hardest part. The rest of the work might take months or years, but at least your code is in a structure where it is possible to migrate forward, while still maintaining the legacy deployment.

Yes there's some risk and additional unit testing (and acceptance testing) required as you make changes to the legacy code, which also changes the future code. That's a net benefit though, because at least you don't have to write those changes twice every time thanks to having a unified codebase.

There's a bit more risk (and therefore testing) required when making changes to the unified codebase for future code, because those changes will usually also impact the legacy app. But you have some control over that impact via compiler directives, and in many cases your business stakeholders will see this also as an advantage because they'll get some new features/capabilities in the existing legacy app even as you build them for the future state.

The point is that you've done the heavy lifting to establish a way forward that is at least achievable. So take a little time and have a small celebration. You deserve it!

Friday, January 11, 2019 12:06:07 PM (Central Standard Time, UTC-06:00)  #    Disclaimer
 Wednesday, December 12, 2018

CSLA .NET 4.9.0 includes some exciting new features, primarily focused on server-side capabilities for containers, .NET Core, and ASP.NET Core. There are a number of data portal enhancements, as well as powerful new configuration options based around the .NET Core configuration subsystem.

Data Portal Enhancements

Many of the enhancements are focused on enabling powerful cloud/container based scenarios with the data portal. Most notably, the data portal now supports two different types of routing to enable the use of multiple server instances. It also has the option to track recent activity with the intent of supporting a basic health dashboard, the ability to force a client "offline", and support for the .NET Core IoC/DI model.

Client-side data portal routing

One common request is that it would be nice if a subset of data portal requests could be routed to some server endpoint other than the default. This idea supports a number of scenarios, including security, logging, multi-tenant server farms, and I'm sure many others.

When you configure the client-side data portal on a web server, mobile device, PC, Mac, or Linux desktop you can now provide mappings so specific business domain types (root object types) cause the data portal to call server-side endpoints other than the default. This can be done on a per-type basis, or by applying the DataPortalServerResource attribute to a root domain type.

As the client app starts up, the data portal must be configured with mappings from domain types or DataPortalServerResource attribute values to specific server endpoint definitions. For example:

      // set up default data portal for most types
      ApplicationContext.DataPortalProxy = typeof(Csla.DataPortalClient.HttpProxy).AssemblyQualifiedName;
      ApplicationContext.DataPortalUrlString = "";

      // add mapping for DataPortalServerResource attribute
        new Csla.DataPortalClient.DataPortalProxyDescriptor
        { ProxyTypeName = typeof(Csla.DataPortalClient.HttpProxy).AssemblyQualifiedName, DataPortalUrl = "" });

      // add mapping for specific business type
        new Csla.DataPortalClient.DataPortalProxyDescriptor
        { ProxyTypeName = typeof(Csla.DataPortalClient.HttpProxy).AssemblyQualifiedName, DataPortalUrl = "" });

Notice that the server-side data portal endpoint is defined not just by a URL, but also by the proxy type, so you can use different network transport technologies to access different data portal servers.

Server-side data portal routing

One of the most common issues we all face when hosting server-side endpoints is dealing with client-side app versioning and having server endpoints that support clients running older software. This is particularly important when deploying mobile apps through the Apple/Google/Microsoft stores, when you can't directly control the pace of rollout for client apps.

Additionally, in a clustered server-side environment such as Kubernetes or Cloud Foundry it is likely that you'll want to organize your containers based on various characteristics, such as CPU consumption, memory requirements, or the need for specialized hardware.

The HTTP data portal (Csla.Server.Hosts.HttpPortalController) now supports a solution for both scenarios via server-side data portal routing. It is now possible to set up a public gateway server that hosts a data portal endpoint, which in turn routes all calls to other data portal endpoints within your server environment. Typically these other endpoints are not public, forcing all client apps to route all data portal requests through that gateway router endpoint.

Note that using technologies like Kubernetes it is entirely realistic for the gateway router to be composed of multiple container instances to provide scaling and fault tolerance.

To minimize overhead, the data portal router does not deserialize the inbound data stream from the client. Instead, it uses a header value to determine how to route the request to a worker node where the data stream is deserialized and processed. That header value is created by the client-side data portal by combining two concepts.

First is an optional application version value. If this value is set by the client-side app it is then passed through to the server-side data portal where the value is used to route requests to a worker node running a corresponding version of the server-side app. This allows you to leave versionA nodes running while also running versionB nodes, and once all client devices have migrated off versionA then you can shut down those versionA nodes with no disruption to your users.

Second is a DataPortalServerRoutingTag attribute you can apply to root domain types. This attribute provides a routing tag value that is also passed to the server-side data portal. The intent of this attribute is that you can specify that certain root domain types have characteristics that should be used for server-side routing. For example, you might tag domain types that you know will require a lot of CPU or memory on the server so they are routed to Kubernetes pods that are hosted on fast or large physical servers (Kubernetes nodes), while all other requests go to pods running on normal sized Kubernetes nodes.

Another example would be where the server-side processing requires access to specialized hardware. In that case your Kubernetes nodes would have a taint indicating that they have that hardware, and the DataPortalServerRoutingTag is used to tell the data portal router to send requests for that root domain type only to server-side data portal instances running on those nodes.

What makes this data portal feature a little complex is that the data portal router uses both the version and routing tag to route calls. This is obviously required to support both scenarios at the same time, but it does mean you need to define your routes such that they consider both version and routing tag elements.

The client-side data portal passes a routing tag to the server with the following format:

  • null - neither routing tag nor version are specified
  • routingTag-versionTag - both routing tag and version are specified
  • routingTag- - a routing tag is specified, but no version
  • -versionTag - a version is specified, but no routing tag

Your server-side data portal gateway router is configured on startup with code like this (in the data portal controller class):

  public class DataPortalController : HttpPortalController
    public DataPortalController()
      RoutingTagUrls.Add("routingTag-versionTag", "https://serviceName:36123/api/DataPortal");

You can specify as many routing tag/version keys as necessary to handle routing to the data portal endpoints running in your server environment.

If a key can't be found, or if the target URL is localhost then the request will be processed directly on the data portal router instance. Of course you may choose not to deploy any of your business DLLs to the router instance, in which case all such requests will fail, returning an exception to the client.

Offline mode

A common feature request, especially for mobile devices and laptops, is for the application to force itself into "offline mode" where all data portal calls are directed only to the local data portal. The client-side data portal now supports this via the Csla.ApplicationContext.IsOffline property.

If you set IsOffline to true the client-side data portal will immediately route all data portal requests to the local app rather than a remote server. It is as if all your data portal methods had the RunLocal attribute applied.

Clearly you need to build your DataPortal_XYZ methods to behave properly when they are running on the client (Csla.ApplicationContext.ExecutionLocation == ExecutionLocations.Client) vs the server (Csla.ApplicationContext.ExecutionLocation == ExecutionLocations.Server). Typically you'd have your code delegate to a DAL provider specific to the client or server based on execution location using the encapsulated invocation model as described in Using CSLA 4: Data Access.

Save and Merge

CSLA has included the GraphMerger type for some time now. This type allows you to merge the results of a SaveAsync call back into the existing domain object graph. The BusinessBase and BusinessListBase types now implement a simpler SaveAndMergeAsync method you can use to save a root domain object such that the results are automatically merged into the object graph.

DataPortalFactory in ASP.NET Core dependency injection

ASP.NET Core includes a dependency injection model based on IServiceCollection, with dependencies defined in the ConfigureServices method of the Startup.cs file. CSLA .NET now supports that scenario via an AddCsla extension method for IServiceCollection.

    public void ConfigureServices(IServiceCollection services)
      // ...

The only service that is defined is a new IDataPortalFactory, implemented by DataPortalFactory. The factory is a singleton, and is used to create instances of the data portal for use in a page. For example, in a Razor Page you might have code like this:

  public class EditModel : PageModel
    private IDataPortal<Customer> dataPortal;

    public EditModel(IDataPortalFactory factory)
      dataPortal = factory.GetPortal<Customer>();
    // ...

Configuration Enhancements

An important design pattern for success in both DevOps and container-based server deployment is to store config in the environment. The .NET Core configuration subsystem supports this pattern, and now CSLA .NET does as well. Not only that, but we now support an optional fluent configuration model if you want to set configuration in code (common in Xamarin apps for example), and integration with the .NET Core and ASP.NET Core configuration models.

.NET Core configuration subsystem integration

The .NET Core configuration subsystem supports modern configuration concepts, while still supporting legacy concepts like config files. It is also extensible, allowing providers to load configuration values from many different sources.

The base type used in .NET Core configuration is a ConfigurationBuilder. An instance of this type is provided to you by ASP.NET Core, or you can create your own instance for use in console apps. CSLA .NET provides an extension method to integrate into this configuration model. For example, in a console app you might write code like this:

  var config = new ConfigurationBuilder()

In ASP.NET Core you'd simply use the ConfigurationBuilder instance already avalable to invoke the ConfigureCsla method.

The result of the ConfigureCsla method is that the configuration values are loaded for use by CSLA .NET based on any configuration sources defined by the ConfigurationBuilder. In many cases that includes a config file, environment values, and command line parameters. It might also include secrets loaded from Azure, Docker, or whatever environment is hosting your code. That's all outside the scope of CSLA itself - those are features of .NET Core. The point is that the ConfigureCsla method takes the results of the Build method and maps the config values for use by CSLA .NET.

Note that nothing we've done here has any impact on .NET Framework code. All your existing .NET 4.x code will continue to function against web.config/app.config files.

Fluent configuration API

Although it is best to follow the 12 Factor guidance around config, there are times when you just need to set config values through code. This is particularly true in Xamarin and WebAssembly scenarios, where the configuration systems are weak or non-existant.

In the past you've been able to directly set propery values on Csla.ApplicationContext, various data portal types, and elsewhere in CSLA. That's confusing and inconsistent, and is a source of bugs in many people's code.

There's a new fluent API for configuration you can use when you need to set configuration through code. The entry point for this API is Csla.Configuration.CslaConfiguration, which implements Csla.Configuration.ICslaConfiguration. The model uses extension methods for sub-configuration, extending the ICslaConfiguration type.

Basic configuration is done like this:

      new Csla.Configuration.CslaConfiguration()

Data portal configuration can be chained like this:

      new Csla.Configuration.CslaConfiguration()
        .DataPortal().DefaultProxy(typeof(HttpProxy), "")

Client-side data portal descriptors for client-side data portal routing (see above) can be configured like this:

      new CslaConfiguration()
        .DataPortal().ProxyDescriptors(new List<Tuple<string, string, string>>

Configuration of Csla.Data options:

      new CslaConfiguration()

Security options:

      new CslaConfiguration()

You should consider using this new fluent API instead of the old/fragmented configuration options at all times - for setting config values. CSLA .NET itself continues to rely on Csla.ApplicationContext to read config values for use throughout the code.


CSLA .NET version 4.9 is very exciting for server-side developers, or people using a remote data portal where versioning or advanced routing scenarios are important. Between the data portal enhancements and more modern configuration techniques available in this version, your life should be improved as a CSLA .NET developer.

Wednesday, December 12, 2018 1:38:51 PM (Central Standard Time, UTC-06:00)  #    Disclaimer
 Friday, November 30, 2018

For some time now it has been the case that people are all excited about "microservices".

I want to start by saying that I think this is a horrible name for what we're trying to accomplish, because the term attempts to put the concept of size onto services.

Calling a service is expensive. You are creating a message, serializing that message, sending it over a network via http or a queue (or both), where it is deserialized, and finally the service can do some work. Any response goes through all that same overhead to get back to the caller. That overhead is measured in milliseconds - usually 10's of milliseconds.

So if your "micro"service does work that takes less than 10-20 milliseconds to complete, then you've paid this massive performance cost to get to/from the service over the network, only to have the actual work take less time than the overhead.

That's like paying your auto mechanic for a full hour, just so they can do a 5 minute fix to your car. Nobody would do that without being forced (and sometimes we are - due to specialized skills or tools/parts availability).

This analogy translates to the services world too. Calling a service is fine if the service:

  1. does enough work to be worth the overhead of calling the service (the work took longer than the network overhead)
  2. needs to run in a secure location
  3. is required to run in a geo-bounded location (think GDPR)
  4. must run on specialized hardware that doesn't exist elsewhere
  5. contains code that is so valuable that, if reverse engineered, would destroy your organization (variation on security)

I've tried to put those in order from most to least likely, but everyone's scenario is a bit different.

The point I'm really getting at, is that in the majority of cases it is important to make sure a service does enough work to make it worth the non-trivial overhead of getting to/from the service over http and/or a queue.

In those other less common scenarios there's a business decision to be made. If the service is very small and fast, you will be paying massive overhead for very little work to be done. Presumably the business is saying that those other concerns outweigh the fact that your app will be far slower than it could be.

(hint: as a developer you should make this clear to the business stakeholders up front - head off the question you know is coming later: "why is this app so slow???" - you want to be able to pull out the email thread where you explained that it will be slow because the business decision maker chose to put some tiny-but-critical bit of functionality in a service)

Friday, November 30, 2018 11:21:25 AM (Central Standard Time, UTC-06:00)  #    Disclaimer
 Tuesday, October 2, 2018

For many months (maybe years) I tried to use the Netflix app on my Surface Pro 3 and then Surface Pro 4.

The audio would always get out of sync with the video when streaming shows. Once Netflix allowed download of shows then it worked ok - but only with downloaded content.

This was true as recently as February 2018.

Searching the web revealed that other people had the issues too, and the concensus was something to do with the audio driver for the chipset used in Surface (and maybe other devices).

Recently I got a Surface Go, and to my surprise Netflix worked fine.

So I tried it again on my Surface Pro 4, and it works fine there too now.

I assume that either a Surface driver update or a Netflix app update (or both) occurred since February that finally resolved the issue with streaming and audio playback sync.

In any case, the news is good, and the Netflix app is working great on both my Surface Pro and Surface Go. This makes life in hotels a whole lot nicer, as the last thing I want is to be stuck with cable! 😃

Tuesday, October 2, 2018 4:12:24 PM (Central Standard Time, UTC-06:00)  #    Disclaimer
 Tuesday, September 25, 2018

As people reading my blog know, I'm an advocate of container-based deployment of server software. The most commonly used container technology at the moment is Docker. And the most popular way to orchestrate or manage clusters of Docker containers is via Kubernetes (K8s).

Azure, AWS, and GCE all have managed K8s offerings, so if you can use the public cloud there's no good reason I can see for installing and mananaging your own K8s environment. It is far simpler to just use one of the pre-existing managed offerings.

But if you need to run K8s in your own datacenter then you'll need some way to get a cluster going. I thought I'd figure this out from the base up, installing everything. There are some pretty good docs out there, but as with all things, I ran into some sharp edges and bumps on the way, so I thought I'd write up my experience in the hopes that it helps someone else (or me, next time I need to do an install).

Note: I haven't been a system admin of any sort since 1992, when I was admin for a Novell file server, a Windows NT server, and a couple VAX computers. So if you are a system admin for Linux and you think I did dumb stuff, I probably did 😃

The environment I set up is this:

  1. 1 K8s control node
  2. 2 K8s worker nodes
  3. All running as Ubuntu server VMs in HyperV on a single host server in the Magenic data center

Install Ubuntu server

So step 1 was to install Ubuntu 64 bit server on three VMs on our HyperV server.

Make sure to install Ubuntu server, not client, otherwise this article has good instructions.

This is pretty straightforward, the only notes are:

  1. When the server install offers to pre-install stuff, DON'T (at least don't pre-install Docker)
  2. Make sure the IP addresses won't change over time - K8s doesn't like that
  3. Make sure the MAC addresses for the virtual network cards won't change over time - Ubuntu doesn't like that

Install Docker

The next step is to install Docker on all three nodes. There's a web page with instructions

⚠ Just make sure to read to the bottom, because most Linux install docs are seem to read like those elementary school trick tests where the last step in the quiz is to do nothing - you know, a PITA.

In this case, the catch is that there is a release version of Docker so don't use the test version. Here's the bash steps to get stable Docker for Ubuntu 18.04:

sudo apt install apt-transport-https ca-certificates curl software-properties-common
curl -fsSL | sudo apt-key add -
sudo add-apt-repository "deb [arch=amd64] bionic stable"
sudo apt update
sudo apt install docker-ce

Later on the K8s instructions will say to install, but that's for Ubuntu desktop, while docker-ce is for Ubuntu server.

You will probably want to grant your current user id permission to interact with docker:

sudo usermod -aG docker $USER

Repeat this process on all three nodes.

Install kubeadm, kubectl, and kubelet

All three nodes need Docker and also the Kubernetes tools: kubeadm, kubectl, and kubelet.

There's a good instruction page on how to install the tools. Notes:

  1. Ignore the part about installing Docker, we already did that
  2. In fact, you can read-but-ignore all of the page except for the section titled Installing kubeadm, kubelet and kubectl. Only this one bit of bash is necessary:

Become root:

sudo su -

Then install the tools:

apt-get update && apt-get install -y apt-transport-https curl
curl -s | apt-key add -
cat <<EOF >/etc/apt/sources.list.d/kubernetes.list
deb kubernetes-xenial main
apt-get update
apt-get install -y kubelet kubeadm kubectl
apt-mark hold kubelet kubeadm kubectl

I have no doubt that all the other instructions are valuable if you don't follow the default path. But in my case I wanted a basic K8s cluster install, so I followed the default path - after a lot of extra reading related to the non-critical parts of the doc about optional features and advanced scenarios.

Install Kubernetes on the master node

One of my three nodes is the master node. By default this node doesn't run any worker containers, only containers necessary for K8s itself.

Again, there's a good instruction page on how to create a Kubernetes cluster. The first part of the doc describes the master node setup, followed by the worker node setup.

This doc is another example of read-to-the-bottom. I found it kind of confusing and had some false starts following these instructions: hence this blog post.

Select pod network

One key thing is that before you start you need to figure out the networking scheme you'll be using between your K8s nodes and pods: the pod network.

I've been unable to find a good comparison or explanation as to why someone might use any of the numerous options. In all my reading the one that came up most often is Flannel, so that's what I chose. Kind of arbitrary, but what are you going to do?

Note: A colleague of mine found that Flannel didn't interact well with the DHCP server when installing on his laptop. He used Weave instead and it seemed to resolve the issue. I guess your mileage may vary when it comes to pod networks.

Once you've selected your pod network then you can proceed with the instructions to set up the master node.

Set up master node

Read the doc referenced earlier for more details, but here are the distilled steps to install the master K8s node with the Flannel pod network.

Kubernetes can't run if swap is enabled, so turn it off:

swapoff -a

This command only affects the current session. You also need to turn off swap after a reboot. To do this you need to edit the /etc/fstab file and comment out the lines regarding the swap file. For example, I've added a # to comment out these two lines in mine:

#UUID=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx / ext4 defaults 0 0
#/swap.img	none	swap	sw	0	0

You can, optionally, pre-download the required container images before continuing. They'll get downloaded either way, but if you want to make sure they are local before initializing the cluster you can do this:

kubeadm config images pull

Now it is possible to initialize the cluster:

kubeadm init --pod-network-cidr=

💡 The output of kubeadm init includes a lot of information. It is important that you take note of the kubeadm join statement that's part of the output, as we'll need that later.

Next make kubectl work for the root user:

export KUBECONFIG=/etc/kubernetes/admin.conf

Pass bridged IPv4 traffic to iptables (as per the Flannel requirements):

sysctl net.bridge.bridge-nf-call-iptables=1

Apply the Flannel v0.10.0 pod network configuration to the cluster:

kubectl apply -f

⚠ Apparently once v0.11.0 is released this URL will change.

Now the master node is set up, so you can test to see if it is working:

kubectl get pods --all-namespaces

Optionally allow workers to run on master

If you are ok with the security ramifications (such as in a dev environment), you might consider allowing the master node to run worker containers.

To do this run the following command on the master node (as root):

kubectl taint nodes --all

Configure kubectl for admin users

The last step in configuring the master node is to allow the use of kubectl if you aren't root, but are a cluster admin.

⚠ This step should only be followed for the K8s admin users. Regular users are different, and I'll cover that later in the blog post.

First, if you are still root, exit:


Then the following bash is used to configure kubectl for the K8s admin user:

mkdir -p $HOME/.kube
sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
sudo chown $(id -u):$(id -g) $HOME/.kube/config

What this does is take the K8s keys that are in a secure location and copy them to the admin user's ~/.kube directory. That's where kubectl looks for the config file with the information necessary to run as cluster admin.

At this point the master node should be up and running.

Set up worker nodes

In my case I have 2 worker nodes. Earlier I talked about installing Docker and the K8s tools on each node, so all that work is done. All that remains is to join each worker node to the cluster controlled by the master node.

Like the master node, worker nodes must have swap turned off. Follow the same instructions from earlier to turn off swap on each worker node before joining it to the cluster.

That 'kubeadm join' statement that was display as a result of 'kubeadm init' is the key here.

Log onto each worker node and run that bash command as root. Something like:

sudo kubeadm join --token <token> <master-ip>:<master-port> --discovery-token-ca-cert-hash sha256:<hash>

That'll join the worker node to the cluster.

Once you've joined the worker nodes, back on the master node you can see if they are connected:

kubectl get nodes

That is it - the K8s cluster is now up and running.

Grant access to developers

The final important requirement is to allow developers access to the cluster.

Earlier I copied the admin.conf file for use by the cluster admin, but for regular users you need to create a different conf file. This is done with the following command on the master node:

sudo kubeadm alpha phase kubeconfig user --client-name user > ~/user.conf

The result is a user.conf file that provides non-admin access to the cluster. Users need to put that file in their own '/.kube/' directory with the file name ofconfig:~/.kube/config`.

If you plan to create user accounts going forward, you can put this file into the /etc/skel/ directory as a default for new users:

sudo mkdir /etc/skel/.kube
sudo cp ~/user.conf /etc/skel/.kube/config

As you create new users (on the master node server) they'll now already have the keys necessary to use kubectl to deploy their images.

Recovering from a mistake

If you somehow end up with a non-working cluster (which I did a few times as I experimented), you can use:

kubeadm reset

Do this on the master node to reset the install so you can start over.


There are a lot of options and variations on how to install Kubernetes using kubeadm. My intent with this blog post is to have a linear walkthrough of the process based as much as possible on defaults; the exception being my choice of Flannel as the pod network.

Of course the world is dynamic and things change over time, so we'll see how long this blog post remains valid into the future.

Tuesday, September 25, 2018 9:17:32 AM (Central Standard Time, UTC-06:00)  #    Disclaimer