Modern Functional Programming: The Onion Architecture Leave a comment

They all suggest approaches to make software architectures more manageable and testable, but do so in their own way. Even though you said application layer doesn’t depend on any other layers, you immediately leak entity Framework and core into it by the means of dbset and iservicecollection. This is effectively the same as leaking infrastructure and presentation layer into application layer, you’re bound to the technologies and cannot replace them with anything else.

onion architecture life learning

Putting business-specific rules in a centralized place is something suggested by both Clean and Onion Architecture. Although they use different names for very similar concepts, they both encourage us to think about business logic in the same way. If we look at them all together, they offer some useful architectural takeaways onion architecture that are applicable regardless of the design approach you choose to use. We’ll explore them shortly, but first let’s have a look at what each of these patterns are about individually and how they compare to one another. You can swap out Oracle or SQL Server, for Mongo, BigTable, CouchDB, or something else.

Once you have dynamic scoping (surprise! also not referentially transparent) everything that DI does becomes trivial. It basically wraps around the domain layer, adding specific business rules on top (e.g. how much fees should the app charge to a customer, etc). Software development career is very rewarding. Being able to code with simple, efficient and clean architecture will not only help you crack your interviews, but also take your career to a whole new level. I believe the Dependency Injection container should mostly take care of this for you.


Instead of building a highly decoupled structure, we often end up with several layers that are depending on each other. This is something really bad in building scalable applications and may pose issues with the growth of the codebase. To keep it clear, in the above diagram we can see that the presentation layer depends on the logics layer, which in turn depends on the data access and so on.

onion architecture life learning

Domain-Driven Design together with Onion Architecture is a combination that Wade Waldronin a presentation states has increased his code quality dramatically since he started using it a few years back. At first glance, Clean Architecture provides a better understanding of boundaries and provides a clearer separation of concerns compared to Onion Architecture. They are very closely related and advocate similar ideas, but with different layers. Clean architecture makes it distinctly clear why each layer exists and what their respective responsibilities are. That’s why it’s also known as screaming architecture — it makes everything explicit. One such caution is as company gets larger and larger through M&A and as portfolio of applications get larger, you will be challenged with the operational side of maintaining lots of Microservices.

Implementing Onion Architecture in ASP.NET Core WebApi Project

There are few things that aren’t really some other thing, just with something else added or removed. What the op is really complaining about is the hype used to get us to listen to the lesson. If you come away saying “I knew that already” then great. I’m happy if we can keep down the number of names for identical things. Layered is not the same as onion but ports & adapters as well as clean architecture sure seem the same to me. I think the real question should be “What is difference between layered architecture and layered architecture with DIP?” .

  • This isolation is supported through the concept of ports and adapters.
  • And to me, that difference is huge and critical to what onion architecture really is about.
  • In other words, this is where we hook up the Data access logic or logging logic or service calls logic.
  • Hierarchical layering, careful interfaces, dynamic programming, functional composition, refinement, event-based simulation…
  • In terms of validation, there is an interface, INotifyDataError, which the MVVM toolkit should implement.
  • These posts are the result of this reasoning, as I try to understand how these concepts came to be, in a somewhat chronological way.

But I guess there is a lot of room for optimizing the content. However, you could also check the code on my GitHub to get a detailed understanding. Database Independent – Since we have a clean separation of data access, it is quite easy to switch between different database providers.

The last, third part, after all that we have learned about the theory and architecture, will cover all you need to know about labelson those diagrams, or in other words – separate components. We will show you a real life clean architecture applied on Android. We would like the data to be able to flow from the outer layers to the inner ones and vice versa, but the dependency rule doesn’t allow that. Let’s strip that down to the simplest example. Clean architecture is the brainchild of previously-mentioned Uncle Bob, who also wrote books on Clean Code and Clean Coder. The main point of this approach is that the business logic, also known as domain, is at the center of the universe.

Onion architecture

The result was seven layers to perform a simple CRUD operation. The cognitive load needed to understand such flow and the inertia is so big that it demotivates to make changes. Development costs are rising, and understanding within the team is low. Using a DI container allows you to inject repositories into the unit of work class. The unit of work class can then be injected into the service or controller in your business layer, without referencing any repositories. The DI container is responsible for building the whole object graph, starting with the repositories needed by the unit of work class, and then creating the unit of work class needed by the service.

I am also the one to blame because I made such multi-layered applications. My personal record is a class with 14 generic parameters (sic!). Currently, I prefer to focus on the composition of smaller pieces and cut the application into vertical slices according to the CQRS rules. The simpler and more self-documenting, the better.

Generate the Migrations and the Database

It gives a nice abstraction over the DB Provider as well. Meaning you can switch to another database technology with ease. Hi Mukesh, I was new to building API’s with Microservice Architecture using Core. I went through your articles and I can say ur aticles are one of the best. Can you please make articles on Logging, Validation and Transactional Behavior.

onion architecture life learning

The most interesting thing to notice that there are no special references in this project, and the domain objects are flat objects as they should be, without any heavy code or dependencies. However, the flexibility with technology upgrades doesn’t come handy with tightly coupled systems. How you implement the dependency rule is up to you. You can put it in different packages, but be careful not to use “outer” packages from “inner” packages.

Appwrite – CRA App template with DI, onion-architecture

On top, some advanced scaling methods in this architecture heavily relies on distributed computing methods and techniques. One major takeaway from this article – Understand your business domain via domain modeling. Understanding this will help you breakdown the business problem, then follow the three principles I laid out above (loose coupling, separation of concern and fit-for-purpose). There is no silver bullet obviously, yet but at least we have a path forward if we so desire. Core is the building blocks not specific to any domain or technology, containing generic building blocks like lists, graphs, any advanced data structures, case classes and actors.

Few Fundamental Principles of Software Development

The main programmer had already been exposed to ALGOL, loved the heck out of it, and took some inspiration from SimScript. If a function wants to log something it’s not a simple reader anymore but something more complex. The fact that in Haskell this is reflected in the type signature of the function is again a good thing.

Domain services

A key part of the onion architecture is that outer layers can use the inner layers, but inner layers have no knowledge of outer layers. This means that the infrastructure can see ValueObjects but ValueObjects have no knowledge of the Database. This forces us to keep things simple and to put logic where it belongs, no bleeding of details that will make future changes difficult.

It’s not “polluting” the method signature; it’s putting more information in the method signature. Not letting you hide side effects in a computation that appears to have no externalities is a strength of Haskell, not a weakness. Further, dependency injection is a completely idiotic and broken pattern and IMO the worst thing to come out of object oriented programming.

Cannot change anything except the database object . This is finer control than pure functional programming and safer than imperative/object-oriented programming. I understand the value of referential transparency and how it makes “certain” things easy, but saying that it automatically makes testing functional code easy is a myth. But the abstraction there is a lot more battle-hardened than your business logic at $COMPANY.

Why Onion Architecture?

This is another variant that I have noticed in many huge solutions. Let’s say you have around 100 interfaces and 100 implementations. Do you add all these 100 lines of code to the Startup.cs to register them in the container? That would be insane from the maintainability point of view. To keep things clean, what we can do is, Create a DependencyInjection static Class for every layer of the solution and only add the corresponding.

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