4+1 Architectural View Model

It’s incredibly difficult to describe a complex system, regardless if you are developing a monolith or (micro) services. Use cases, code organization/navigation, interactions between services, and deployment/infrastructure are just some of the aspects that comprise the architecture of an entire system.

Depending on your role as a stakeholder, your view of the system can be very different than another stakeholder.

This blog post is in a series. To catch up check out these other posts:

Context Matters

There are many different stakeholders related to a software system, which all have different perspectives. Project/Project Managers, Developers, System Engineers, End Users all view a system in completely different ways. They view the system based on their own context.

In order to describe a system, it would be useful to define all the different viewpoints and how the overall use cases of the system.

4+1 Architectural View Model

We all have seen many books and articles where one diagram attempts to capture the gist of the architecture of a system. But looking carefully at the set of boxes and arrows shown on these diagrams, it becomes clear that their authors have struggled hard to represent more on one blueprint than it can actually express. Are the boxes representing running programs? Or chunks of source code? Or physical computers? Or merely logical groupings of functionality? Are the arrows representing compilation dependencies? Or control flows? Or data flows? Usually it is a bit of everything.

The paper by Philippe Kruchten, Architectural Blueprints—The “4+1” View Model of Software Architecture, defines 4 concurrent views from the point of view of the various stakeholders.

4+1 Architecture View Model

I recommend reading the paper but for an incredibly simplified version of the views:

  • Logical View: The functionality. The service.
  • Process View: Communication between processes and/or services.
  • Physical View: Deployment of your services.
  • Development View: File/Folder Structure of your codebase. What you’re looking at in your IDE/Editor

The +1 comes in from the scenarios view which is what your end users actually care about. It’s the system functionality/capabilities. The scenarios view is what guides all the other views.

Service Boundaries

Where I think general guidance has fallen short when developing (micro)services is just because you’ve identified multiple logical views ( services), does not mean that each must have their own independent deployment (physical view) or git repo (development view).

To be clear, there are obvious benefits to having independent deployments, but there are many disadvantages as well. But it’s not a requirement.

As an example, in .NET, you could have a solution with various projects that represent different logical views. None of these projects reference each other, they are simply in the same solution. There may however be an ASP.NET Core project that hosts these projects as a single process.

Point being is that just because you have multiple services does not necessarily mean they need to be developed independently or deployed independently.

The four views are representations of the system depending on the context. They don’t need to map 1:1.

When not everything maps 1:1, that’s when it makes it a bit more challenging finding service boundaries. Focus on the scenarios.

Blog Series

More on all of these topics will be covered in greater length in other posts. If you have any questions or comments, please reach out to me in the comments section or on Twitter.

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Focus on Service Capabilities, not Entities

Service Capabilities

One of the most common pitfalls I think I’ve fallen into is focusing too much on data entities rather than service capabilities. What tends to happen is building up a domain model of behaviors related to single entities.

As I’ve mentioned in my post about using language to find service boundaries, you can have the same entity that lives in a different context, but that owns specific behaviors and data.

This blog post is in a series. To catch up check out these other posts:

Entities

I’m not entirely sure where the focus on entities comes from. I suspect it the rise of ORMs has something to do with it as well as the general relational database table design.

In the world of monolithic applications and databases, it’s common to see a singular table that represents an entity. A massive Product table with 100 columns isn’t unusual.

What is unusual when living in a monolith is to think of that Product table being split up into multiple Product tables across multiple databases. This is a big mental leap.

Service Capabilities

But the reality is your application doesn’t often require all of the data related to an entity. Likely it needs very little of it. An exercise to see what it actually needs is by looking at the business logic related to a particular capability.

In our distribution example I’ve been using through this series, if I were to look at the Inventory Adjustment functionality in the Warehouse Service, do you think it requires the Product Selling Price?

An inventor adjustment is used to reconcile the deviation from what physically is in the warehouse for a product and what our system says. Why would there be a deviation from the system, well physical products sitting in a warehouse can be broke or be stolen. The real point of truth is the physical warehouse, not a number in a database.

As you might have guessed, an Inventory Adjustment doesn’t need the selling price.

What this illustrates is we don’t need to have a singular Product entity backed by a singular product table. We can separate these entities into multiple Product entities that live in various services.

What they will share is a common identifier, in our case a SKU to identify the product.

Once you start focusing on the behaviors and capabilities you can identify the data they encapsulate you can start splitting them into multiple entities across the services that own those behaviors.

Blog Series

More on all of these topics will be covered in greater length in other posts. If you have any questions or comments, please reach out to me in the comments section or on Twitter.

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Autonomous Services

Autonomous Services

In my previous post, I explored how words and language used by users of our system in our domain space can have different meaning based on their context. This establishes which services own which behavior and data. In this post, I’m going to explore why services are autonomous and how we can communicate between them

This blog post is in a series. To catch up check out these other posts:

Autonomy

Autonomy is the capacity to make an informed, uncoerced decision. Autonomous services are independent or self-governing. 

What does autonomy mean for services? A Service is the authority of a set of business capabilities. It doesn’t rely on other services.

We are constantly in a push/pull battle between coupling and cohesion. High coupling ultimately leads to the big ball of mud.

What’s unfortunate is the move to (micro)services with non-autonomous services that rely on RPC (usually via HTTP) hasn’t reduced coupling at all. It’s actually made the problem worse by introducing an unreliable network turning the big ball of mud into a distributed big ball of mud.

Prefer Messaging over RPC

We want services to be autonomous and not rely on other services over RPC to reduce coupling. One way to do this is to communicate state changes between our services with events.

When Service A has a state change, we publish that event to our message broker. Any other service can subscriber to that event and perform whatever action it needs to internally. The producer of the event (Service A) doesn’t care about who may consume that event.

Services that don’t Serve

This may seem completely counter-intuitive since the definition of a service is an act of assistance. However, an autonomous service does not want to assist other services synchronously via behaviors, rather exposing to other services things that have happened to it via asynchronous messaging.

An example of this in our distribution domain is in the form of Sales services and the quantity on hand of a product.

Does Sales need the quantity on hand of a product?

Sort of. You could assume without knowing this domain that you do not want to oversell. However, in my experience in distribution, overselling isn’t really a sales problem as it is a purchasing problem.

Sales want to know the quantity on hand of a product, as well as what has purchasing ordered from the vendor but has not yet been received. This is called Available to Promise (ATP) and is used by sales to determine if they can fulfill an order for a customer.

Another interesting point is related to Quantity on Hand. The quantity on hand that is owned by the warehouse service is still not really the point of truth for the real quantity on hand. Whatever the quantity on hand is for a product in a database isn’t the truth. The real truth is what’s physically in the warehouse. Products get damaged or stolen and aren’t immediately reflected in the system. This is why physical stock counts exist which end up as inventory adjustments in our warehouse service.

If we’re using RPC, for the Sales Service to calculate ATP it would need to make synchronous RPC to:

  • Purchasing Service to get what purchase orders have not yet been received.
  • Warehouse Service to get the quantity on hand.
  • Invoicing Service to determine what other orders have been placed but not yet shipped.

However, if we want our Sales Service to be autonomous it needs to manage ATP itself. It can do so by subscribing to the events of the other services.

Sales can manage it’s own ATP for a product subscribing to the various events. When a purchase order is placed it will increase the ATP. When inventory is adjusted it will increase or decrease the ATP. And finally when an order is invoiced it will decrease it’s ATP.

Blog Series

More on all of these topics will be covered in greater length in other posts. If you have any questions or comments, please reach out to me in the comments section or on Twitter.

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