Disclaimer
Note, the majority of this article was written by me but I did employ AI tools to help me generate the outline and some of the major talking points. I do appreciate the use of AI tools to help me bring you great content like this, and I hope you don't mind me employing such tools to help me convey complex ideas like software architecture visualization in a simple, easy-to-understand manner. Thank you for your consideration.
Introduction
Software architecture is difficult, and visualizing complex architectures can be a challenging process. In this article we'll examine the C4 Model for software architecture visualization and how it simplifies the process of visualizing complex architectures. We'll discuss a history of the model, its benefits and limitations, and we will examine the 4'Cs, Context, Container, Component, and Code, and explain the hierarchal nature of the model. Next, we will explore the use of the Structurizr DSL for creating C4 model diagrams. We will follow up with a conclusion and a recap of what we discussed.
Introduction to the C4 Model: What it is and why it's beneficial?
The C4 model is a software architecture visualization model invented by Simon Brown, a software architect and author, as a lightweight and scalable approach to communicate software architecture effectively. The model emphasizes a hierarchal view of the architecture at four levels: context, containers, components, and code.
The Context level provides a birds-eye view of the system, giving an overview of system boundaries, external actors (users), and their interactions with the system.
The Container level focuses on the major architectural building blocks of the system. This can include web servers, databases, desktop apps, microservices, or external services such as APIs. It communicates how these systems interact with each other.
The Component level zooms into a container, showing the internal structure and building blocks of that container and how those building blocks relate to one another. It focuses on the key responsibilities within the container and how they interact with one another.
The Code level provides a detailed view of the code structure of the component, showing details such as the classes, modules, and packages. This aids developers in understanding the actual implementation of these components.
The C4 model strives to promote simplicity and clarity in visualization, using a small set of symbols and notations to represent the different elements. This allows for readability of the diagrams. As a communication tool, the C4 model enables all stakeholders, not just developers, to use the model to understand and communicate about the structure of the software system. Project managers and product owners can use the Context and Container levels to discuss the high-level overview of the system, while Software Architects, Designers, and Implementers can use the Component and Code level to focus on the low-level details.
In addition, the C4 model allows for documentation support, creating documentation alongside the code and helping to capture the architecture effectively. It can easily be updated as the architecture and design of the system changes, thereby ensuring that the documentation always reflects the current state of the system.
Why Do We Need the C4 Model
The Challenge of Software Architecture Visualization
Modern software is a complex combination of many moving pieces and parts that often interact in sometimes unpredictable ways. Being able to visualize and model the containers and components of a software architecture effectively and document the code well is an essential step in any project. Traditional models and methods of modeling software architecture have attempted to accomplish this with some success. Traditional textual documentation, which involves writing detailed descriptions of the software architecture including its components and interactions, can be effective but does come with its disadvantages. As the architecture changes sometimes the documentation remains an afterthought and doesn't change with the system. It can be time consuming and its hard to visualize a complex system from a textual description.
Other methods such as UML Diagrams and Data Flow Diagrams (DFDs), provide visual representations of the software architecture and the flow of data within the system respectively. These capture a visual representation of the software architecture and provide high level insights into the design and architecture of the system, but they too come with their own sets of disadvantages. UML diagrams are very technical and are usually only useful to the implementers, designers, and architects working on the system. If a non-technical stakeholder needed to communicate about the system, they would find it difficult to look at such a diagram and effectively understand the relationships and meaning of the symbols without studying UML and the meaning of the various arrows and symbols used to denote relationships such as "Is-A" and 'Has-A'".
The Role of Software Architecture Visualization
The role of software architecture visualization, as employed by the C4 Model, is to facilitate the high level visualization of complex architectures so that all stakeholders, both technical and non-technical, can communicate effectively about the design and implementation of complex systems. It facilitates communication, collaboration, decision-making, and maintaining a shared understanding among stakeholders. As the system grows in complexity, the diagram and software visualization can grow in complexity as well, enabling a continued understanding of the system.
Brief History of the C4 Model
The C4 Model, as mentioned above was created by Simon Brown and first introduced in a blog post titled "The C4 software architecture model" in 2011. Since then, Brown has gone on to develop and speak extensively about the merits and benefits of the C4 model. The inspiration behind the C4 model lies in various sources, including the ideas of the 4+1 architecture model by Philippe Kruchten and the work of Ivar Jacobson on use case diagrams and the Unified Modeling Language (UML).
Key Advantages of the C4 Model
The C4 model aimed to be a lightweight approach to more traditional heavyweight approaches, such as the use of UML diagrams and large architectural diagrams. It focuses on simplicity and clarity for its visual representations. It accomplishes this by focusing on 4 abstraction levels, Context, Containers, Components, and Codes. These levels allow architects, developers, and other stakeholders to visualize the architecture at various levels of detail and to discern details that are relevant to them depending on the stated objective.
Limitations of the C4 Model
Despite its benefits, the C4 model does have some limitations and drawbacks. Some of these include limited detail at the code level, meaning it doesn't capture some fine-grained details when focusing closer on implementation details. It lacks a formal notation, so how it is interpreted can vary from one use case to another use case. It has trouble capturing dependency management between components or containers. While it can be depicted informally, more complex relationships might require additional documentation on the part of the user of the C4 model. Finally, it struggles with modeling dynamic behavior and focuses more on static aspects of modeling software visualization. Still, despite these drawbacks the C4 model offers a powerful set of abstractions and structure for defining a software architecture visualization framework for modeling complex systems.
Overview of the C4 Model
Hierarchy of the C4 Model
The C4 model comprises a hierarchal model of abstractions that centers around 4 levels, each with different intended audiences. These are the Context level, the Container level, the Component level, and the Code level. Each of these can be viewed as subcategories or nested within the each, the Context level gives way to the Container level, the Container level to the Component level, and the Component level to the Code level. As we get deeper and deeper into the abstractions, more and more details are revealed to us about the software architecture.
Context Level
At the top level we have the highest level of abstraction, the Context level. This level answers the question, "What is the system and how does it interface with the external world? How does it interact with actors, or users?" It provides a very high-level overview of the overall software architecture. This view of the system can be understood by both technical and non-technical stakeholders, providing valuable insights into the high-level architecture of the system.
Container Level
The next level of abstraction is the Container level, and shows the "containers" of the system. Containers are not to be thought of in the traditional sense of Docker containers, or lightweight, standalone, executable units that encapsulate software and its dependencies. Rather, containers here refer to anything like web severs, databases, mobile apps, desktop apps, filesystems, microservices, external APIs, etc. This level is still useful for both technical and non-technical stakeholders, but provides a more detailed look at the internals of the software architecture. Here we are able to define various interactions between the containers, for example, do the web servers read and write to the database or do they interface with the external APIs? How do the web servers interact with microservices? How does the database interact with the file system? All this is modeled at the Container level.
Component Level
As we dive deeper we start to get into more technical details and start to delve into the realm that is more exclusively for designers, architects, and the software implementers. Next we have the Component level, and this is what we get when we zoom in on a container and see the building blocks that it comprises of. For example, suppose we zoom in on an ETL Pipeline and look at the components that make it up. We might see an extraction component, a validation component, a transform component, a loading component, and a monitoring and logging component. This is the layer of services, controllers, repositories, etc. and provides a more granular view of the structure of the overall system architecture. This is especially important for the architects and the developers because it provides details necessary for developing the actual code.
Code Level
The final level of the C4 model is the code level and represents the individual code elements within the software architecture. These are the tiniest elements of the model, and represent specific classes, modules, interfaces, and other code elements. It provides an extremely detailed view of the architecture and is useful for developers implementing the code and answering questions like, "What does this class look like" and "How do I implement this interface" and "What is the relationship between these classes?"
Using Structurizr To Design a Machine Learning C4 Model
Structurizr, available at https://structurizr.com/ and also has a free plan available with a single workspace available, is a tool that allows you to build out a C4 model using its Structurizr DSL to outline the Containers, Components, and Contexts of the architecture. It is a valuable tool for designing and visualizing a software architecture. In this example we'll build out a simple Machine Learning Pipeline, I mean a very basic one, featuring an ETL Pipeline and a model that trains images that classifies it as a image of planet earth or not. To begin, lets define our work space.
Unfortunately, there is no syntax highlighting for structurizr as far as I can tell so I'll format it as best as I can.
workspace "ML Pipeline" "Machine Learning Pipeline Example" {
}
Here we define our Workspace. We give it a name, "ML Pipeline", and a description.
Next, we declare a model.
workspace "ML Pipeline" "Machine Learning Pipeline Example" {
model {
}
}
Next, we're declare our user and our software system.
workspace "ML Pipeline" "Machine Learning Pipeline Example" {
model {
user = person "ML Engineer"
mlSystem = softwareSystem "ML System" {
}
user -> mlSystem "Uses"
}
}
We can render the image and produce the following Context diagram:
We can define a few Containers now for our ETL engine and our ML engine and define a reliance on the ML engine to use the ETL engine.
workspace "ML Pipeline" "Machine Learning Pipeline Example" {
model {
user = person "ML Engineer"
mlSystem = softwareSystem "ML System" {
etlEngine = container "ETL Engine"
mlEngine = container "ML Engine"
}
user -> mlSystem "Uses"
mlEngine -> etlEngine "Loads data from"
}
}
Rendering this gives us the following Container diagram:
Now we can define our components for the ETL Engine and ML Engine respectively, and their relationships.
workspace "ML Pipeline" "Machine Learning Pipeline Example" {
model {
user = person "ML Engineer"
mlSystem = softwareSystem "ML System" {
etlEngine = container "ETL Engine" {
extractionComponent = component "Extraction Component"
validationComponent = component "Validation Component"
transformationComponent = component "Transformation Component"
loadingComponent = component "Loading Component"
monitoringAndLoggingComponent = component "Monitoring and Logging Component"
}
mlEngine = container "ML Engine" {
dataLoadingComponent = component "Data Loading Component"
featureExtractionComponent = component "Feature Extraction Component"
modelLoadingComponent = component "Model Loading Component"
modelTrainingComponent = component "Model Training Component"
modelValidationComponent = component "Model Validation Component"
}
}
user -> mlSystem "Uses"
mlEngine -> etlEngine "Loads data from"
extractionComponent -> validationComponent "Sends data to for validation"
validationComponent -> transformationComponent "Sends data to for transformation"
transformationComponent -> loadingComponent "Sends data to for loading"
dataLoadingComponent -> featureExtractionComponent "Loads data into for feature extraction"
featureExtractionComponent -> modelLoadingComponent "Sends data into model for loading"
modelLoadingComponent -> modelTrainingComponent "Sends model into component for training"
modelTrainingComponent -> modelValidationComponent "Sends model into component for validation"
}
}
And we have two diagrams, the ETL Engine component diagram and the ML Engine component diagram
Now we have a fully realized and defined software architecture for our simple ML pipeline. The Structurizr tool doesn't actually allow you to dive into the Code level at all. In fact, Simon Brown recommends you not generate the Code level often because it changes so frequently and you often generate the code diagrams from your IDE rather than the other way around.
Conclusion
In this article we examined the complexities of software architecture and why software architecture visualization makes sense. In particular, we examined the C4 model for software architecture visualization and its merits and some of its drawbacks. We looks at its hierarchal nature and its four levels, Context, Container, Component, and Code, and explained what each one entails. We then provided an examination of the Structurizr DSL for documenting and architecting a software visualizing using a simple ETL and ML engine pipeline as an example.
Now that you have a better understanding of the C4 model, you have the necessary knowledge and tools at your disposal to use the C4 model to better visualize your complex software architectures. As always, please feel free to reply with your comments, questions, or concerns. I hope you enjoyed this article, and please feel free to read my other articles on Dev.to. Thank you for reading, and have a wonderful day!
References
C4 Model - The C4 Model Website, outlining the model in great detail.
Structurizr - The Structurizr website, where you can sign up for free and create your own software visualizations.
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