From 60b8fc4aba3b0153bc7f2d2903582cc4ec03f0f1 Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Fri, 14 Nov 2025 13:27:44 +0000 Subject: [PATCH 01/18] added blog post on communicating architecture --- .../2025-11-12-communicating-architecture.md | 115 ++++++++++++++++++ sbreingan/assets/diagram-archimate.png | Bin 0 -> 254058 bytes sbreingan/assets/diagram-c4.png | Bin 0 -> 25824 bytes sbreingan/assets/diagram-cloudcraft.png | Bin 0 -> 641371 bytes sbreingan/assets/diagram-spectrum.png | Bin 0 -> 52584 bytes 5 files changed, 115 insertions(+) create mode 100644 _posts/2025-11-12-communicating-architecture.md create mode 100644 sbreingan/assets/diagram-archimate.png create mode 100644 sbreingan/assets/diagram-c4.png create mode 100644 sbreingan/assets/diagram-cloudcraft.png create mode 100644 sbreingan/assets/diagram-spectrum.png diff --git a/_posts/2025-11-12-communicating-architecture.md b/_posts/2025-11-12-communicating-architecture.md new file mode 100644 index 0000000000..cdb5fcd781 --- /dev/null +++ b/_posts/2025-11-12-communicating-architecture.md @@ -0,0 +1,115 @@ +# Communicating Architecture: From Whiteboards to Models + +One of the most important responsibilities of a software architect is communicating architecture effectively. Whether you're sketching out a new system or explaining how existing components fit together, the goal is always the same: help others understand the structure, purpose, and implications of the architecture. + +But architecture isn’t just about boxes and lines. It’s about conveying ideas clearly to different audiences — from engineers and product managers to stakeholders and partners — each with their own concerns and levels of technical depth. + +--- + +## Why Diagrams Matter (and Where to Start) + +In most situations, a large wall of text it not an effective way of describing how microservices interact or how data flows through a system. Diagrams are often the fastest way to communicate relationships, dependencies, and abstractions. But before you start drawing, it’s worth asking two questions: + +- **What** do I need to show? +- **How** should I show it? + +This is where we can distinguish between *modelling* and *diagramming*. + +--- + +## Modelling vs Diagramming + +Often we can be gatehred around a whiteboard, creating many boxes, adding components, drawing lines between them all. These ad-hoc sketches are great for brainstorming, but they rarely survive beyond the meeting. To create diagrams that are useful over time, we need to think about the underlying *model*. + +- **Modelling** is about defining the structure of what we want to present: actors, components, relationships, and abstractions. +- **Diagramming** is how we present that model — a visual slice tailored to a specific audience or concern. + +A diagram is a *view* onto a model. As we want to communicate to many different people, one diagram is rarely going to be enough. Real systems are complex, and we need multiple views to tell the full story. + +--- + +## Viewpoints: Tailoring Diagrams to Purpose + +Each diagram should be shaped by a **viewpoint** — a lens that reflects the concerns of a particular audience or question. For example: + +- A **system integration viewpoint** might show how services communicate across domains — ideal for business stakeholders. +- A **deployment viewpoint** might zoom into how a service is containerized and wired into infrastructure — helpful for engineers. + +By choosing the right viewpoint, we ensure diagrams are purposeful, consistent, and meaningful. + +--- + +## The Spectrum of Approaches + +When it comes to modelling and diagramming, there’s no one-size-fits-all. Instead, there’s a spectrum: + +### 1. Heavyweight & Structured +Tools like **UML** or **ArchiMate** offer formal modelling languages with strict semantics. These are great for enterprise-scale architecture, especially when aligning with frameworks like TOGAF. But they come with a cost: effort, discipline, and often a steep learning curve. + +### 2. Lightweight & Structured +Approaches like Simon Brown’s **C4 Model** strike a balance — offering structure without the overhead. C4 defines four abstraction levels and encourages consistent, understandable diagrams. Similarly, cloud architecture diagrams (e.g. AWS reference diagrams) use standardised icons to maintain clarity. + +### 3. Lightweight & Unstructured +At the other end are free-form sketches — whiteboards, Visio, diagrams.net. These are perfect for early ideation but can quickly become inconsistent and hard to maintain as systems evolve. + +![Tooling Spectrum]({{ site.baseurl }}/sbreingan/assets/diagram-spectrum.png) + + +Choosing the right approach is a trade-off between **consistency**, **flexibility**, and **complexity**. It depends on how long the diagram will live, who will maintain it, and how complex the system is. + +--- + +## Tooling Landscape + +There’s no shortage of tools, and they tend to fall into a few categories: + +- **Diagrams as Code**: Tools like **PlantUML**, **Mermaid**, and **Structurizr DSL** let you define diagrams in text. They’re version-controlled, CI/CD-friendly, and great for teams who treat architecture like code. The downside? Layout control and polish can be limited. + +``` +@startuml +!include https://raw.githubusercontent.com/plantuml-stdlib/C4-PlantUML/master/C4_Container.puml + +LAYOUT_LEFT_RIGHT() + +Person(user, "End User", "Calls the public API") + +System_Boundary(sys, "Serverless API System") { + Container(apiGw, "API Gateway", "Amazon API Gateway", "Entry point for HTTPS clients; routing & auth") + Container(lambdaFn, "Lambda Function", "AWS Lambda", "Executes business logic for incoming requests") + ContainerDb(backend, "Backend Service", "Database / Internal Service", "Stores and retrieves application data") +} + +Rel(user, apiGw, "Invokes API", "HTTPS/JSON") +Rel(apiGw, lambdaFn, "Triggers", "Lambda integration") +Rel(lambdaFn, backend, "Reads/Writes data", "SDK / JDBC") + +@enduml +``` + +![C4 Diagram]({{ site.baseurl }}/sbreingan/assets/diagram-c4.png) + + +- **Model-Driven Tools**: Enterprise tools like **Sparx**, **Archi**, and **Visual Paradigm** focus on maintaining a central model and generating views from it. These are powerful but require discipline and effort to keep up to date. + + +![Archi Mate]({{ site.baseurl }}/sbreingan/assets/diagram-archimate.png) + +- **Visual Diagramming Tools**: Tools like **Lucidchart**, **Miro**, and **diagrams.net** are intuitive and collaborative. They’re great for workshops and quick sketches but lack model consistency and versioning. + +- **Cloud-Specific Tools**: Tools like **Cloudcraft**, **Hava**, and vendor-native options like **AWS Workload Discovery** or **Azure Resource Visualizer** can auto-generate diagrams from live environments. These are brilliant for discovery and documentation — less so for future design. + + +![CloudCraft]({{ site.baseurl }}/sbreingan/assets/diagram-cloudcraft.png) + + +--- + +## Choosing the Right Tool (and Asking the Right Questions) + +Ultimately, the tool you choose should reflect: + +- **Why** you’re creating the diagram — is it for a pitch deck or a long-lived artifact? +- **Who** will maintain it — are they comfortable with code-based tools? +- **How complex** the architecture is — does it justify a formal model? + +And most importantly: **Is this diagram useful?** If it doesn’t help the intended audience understand what they need to, it’s just decoration. diff --git a/sbreingan/assets/diagram-archimate.png b/sbreingan/assets/diagram-archimate.png new file mode 100644 index 0000000000000000000000000000000000000000..9f7421e6478a26449b2e6bc60ca1c40824d4b285 GIT binary patch literal 254058 zcmd3OXIN9&7AWeVBM6Mr1Su-LD@Bm5NC{nfLKEp7A#?&(P^tt7(xrDoM`}h9kzN7` 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zlFJ=1Ex^OZ_LtiT{JY}5V6_R}nxhhjL+U$OO~HXr>aRKaLN{Jd9{!CFWgpW>}|L&T3GVqkZ-Va`|cl#zd!i<{{iay BB>DgV literal 0 HcmV?d00001 From 56c39ac434b8dc054c0752a1820d5281555f7a2e Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Fri, 14 Nov 2025 16:13:29 +0000 Subject: [PATCH 02/18] Updated to include diagrams --- .../2025-11-12-communicating-architecture.md | 150 +++++++++++------- 1 file changed, 91 insertions(+), 59 deletions(-) diff --git a/_posts/2025-11-12-communicating-architecture.md b/_posts/2025-11-12-communicating-architecture.md index cdb5fcd781..727b493ea6 100644 --- a/_posts/2025-11-12-communicating-architecture.md +++ b/_posts/2025-11-12-communicating-architecture.md @@ -1,115 +1,147 @@ # Communicating Architecture: From Whiteboards to Models -One of the most important responsibilities of a software architect is communicating architecture effectively. Whether you're sketching out a new system or explaining how existing components fit together, the goal is always the same: help others understand the structure, purpose, and implications of the architecture. +One of the most important responsibilities of a software architect is **communicating architecture effectively**. Whether you're sketching out a new system or explaining how existing components fit together, the goal is always the same: help others understand the structure, purpose, and implications of the architecture. -But architecture isn’t just about boxes and lines. It’s about conveying ideas clearly to different audiences — from engineers and product managers to stakeholders and partners — each with their own concerns and levels of technical depth. +Architecture communication often needs to operate at multiple levels of abstraction. A CTO may want to understand strategic alignment, while an engineer might need to know how a service is deployed and monitored. The challenge is to tailor the message without losing coherence. ---- +More often than not, this communication is **visual**. Diagrams are faster and clearer than text when conveying relationships between components, data flows, and infrastructure. But before drawing anything, we need to ask two fundamental questions: -## Why Diagrams Matter (and Where to Start) +- **What** do we want to show? +- **How** should we show it? -In most situations, a large wall of text it not an effective way of describing how microservices interact or how data flows through a system. Diagrams are often the fastest way to communicate relationships, dependencies, and abstractions. But before you start drawing, it’s worth asking two questions: +--- -- **What** do I need to show? -- **How** should I show it? +## Modelling vs Diagramming -This is where we can distinguish between *modelling* and *diagramming*. +Many of us have been in meetings gathered around a whiteboard, sketching out boxes and arrows to explore ideas. These ad-hoc diagrams are great for rapid ideation — they help teams align quickly and visually. But they rarely survive beyond the moment. As systems grow in complexity, we need more than just sketches. We need to understand **what** we’re showing, not just **how** we’re showing it. ---- +This is where the distinction between **modelling** and **diagramming** becomes critical. -## Modelling vs Diagramming +- **Modelling** is the process of defining the structure of a system: its actors, components, relationships, and abstractions. It creates a consistent representation of the architecture, independent of how it's visualised. +- **Diagramming** is the act of presenting that model — a visual slice tailored to a specific audience or concern. -Often we can be gatehred around a whiteboard, creating many boxes, adding components, drawing lines between them all. These ad-hoc sketches are great for brainstorming, but they rarely survive beyond the meeting. To create diagrams that are useful over time, we need to think about the underlying *model*. +A diagram is a **view** onto a model. It highlights certain elements while omitting others, depending on the story we want to tell. -- **Modelling** is about defining the structure of what we want to present: actors, components, relationships, and abstractions. -- **Diagramming** is how we present that model — a visual slice tailored to a specific audience or concern. +In organisations with complex digital estates, this becomes essential. Consider a single system: +- What other systems does it interact with? +- What components make up that system? +- How do those components relate to the underlying infrastructure? -A diagram is a *view* onto a model. As we want to communicate to many different people, one diagram is rarely going to be enough. Real systems are complex, and we need multiple views to tell the full story. +Trying to capture all of this in a single diagram is rarely helpful. Instead, we need **multiple views**, each shaped by a specific **viewpoint**. ---- +Without an underpinning model, creating multiple diagrams can lead to confusion — inconsistent boundaries, conflicting relationships, and misaligned assumptions. A shared model ensures coherence across views. -## Viewpoints: Tailoring Diagrams to Purpose +### 🧠 Analogy: Architecture as House Plans -Each diagram should be shaped by a **viewpoint** — a lens that reflects the concerns of a particular audience or question. For example: +Think of the model like the structural blueprint of a house. From that blueprint, you can generate different plans: +- A **floor plan** for layout and navigation. +- An **electrical plan** for wiring and sockets. +- A **plumbing plan** for water and waste systems. -- A **system integration viewpoint** might show how services communicate across domains — ideal for business stakeholders. -- A **deployment viewpoint** might zoom into how a service is containerized and wired into infrastructure — helpful for engineers. +Each plan is a **view** onto the same underlying structure. If the walls, doors, and rooms aren’t aligned across these views, you end up with serious problems — wires running through non-existent walls, or pipes with nowhere to go. -By choosing the right viewpoint, we ensure diagrams are purposeful, consistent, and meaningful. +Architecture works the same way. The model is your source of truth. Diagrams are tailored views that help different people understand and work with it. --- ## The Spectrum of Approaches -When it comes to modelling and diagramming, there’s no one-size-fits-all. Instead, there’s a spectrum: +When deciding how to model and create views, there’s no one-size-fits-all solution. Instead, there’s a spectrum — ranging from highly structured, formal modelling approaches to informal, free-form sketches. Each approach has its place depending on the context, audience, and longevity of the diagram. + +At one end of the spectrum, we have **heavyweight and structured approaches** such as UML and [ArchiMate These approaches enforce strict semantics and provide a rich modelling language. They are ideal for enterprise-scale architecture where consistency, traceability, and alignment with frameworks like TOGAF are essential. However, they come with trade-offs: they require significant effort to maintain, a steep learning curve, and may not be accessible to non-architects. -### 1. Heavyweight & Structured -Tools like **UML** or **ArchiMate** offer formal modelling languages with strict semantics. These are great for enterprise-scale architecture, especially when aligning with frameworks like TOGAF. But they come with a cost: effort, discipline, and often a steep learning curve. +Moving toward the middle, we find **lightweight but structured approaches** such as C4 Model and Structurizr DSL. These techniques strike a balance by offering structure without the overhead of a full meta-model. They encourage consistency and clarity while remaining agile enough for modern development practices. AWS reference architecture diagrams also fall into this category, using standardised icons to maintain clarity. -### 2. Lightweight & Structured -Approaches like Simon Brown’s **C4 Model** strike a balance — offering structure without the overhead. C4 defines four abstraction levels and encourages consistent, understandable diagrams. Similarly, cloud architecture diagrams (e.g. AWS reference diagrams) use standardised icons to maintain clarity. +Finally, at the far end of the spectrum, we have **lightweight and unstructured approaches** — whiteboards, Miro, Lucidchart, and diagrams.net. These tools are perfect for early ideation and collaborative workshops. They are fast, intuitive, and flexible, but they lack an underlying model and can quickly become inconsistent as systems evolve. -### 3. Lightweight & Unstructured -At the other end are free-form sketches — whiteboards, Visio, diagrams.net. These are perfect for early ideation but can quickly become inconsistent and hard to maintain as systems evolve. +Choosing the right approach is always a trade-off between **consistency**, **flexibility**, and **complexity**. It depends on how long the diagram will live, who will maintain it, and how complex the system is. ![Tooling Spectrum]({{ site.baseurl }}/sbreingan/assets/diagram-spectrum.png) +## Tooling Landscape -Choosing the right approach is a trade-off between **consistency**, **flexibility**, and **complexity**. It depends on how long the diagram will live, who will maintain it, and how complex the system is. +Once you've decided how structured your approach needs to be, the next step is choosing the right tools. The tooling landscape is broad, and tools tend to fall into a few categories — each suited to different stages of the architecture lifecycle. ---- +### ✍️ Diagrams as Code -## Tooling Landscape +Tools like PlantUML, Mermaid, and Structurizr DSL allow you to define diagrams using text. These are ideal for teams who treat architecture like code — enabling version control, CI/CD integration, and automated documentation. -There’s no shortage of tools, and they tend to fall into a few categories: +They work particularly well when architecture needs to evolve alongside code. Diagrams can live in the same repository, be reviewed like any other code change, and even be generated automatically as part of a pipeline. The trade-off is that layout control can be limited, and the output may lack the polish of a hand-crafted diagram. -- **Diagrams as Code**: Tools like **PlantUML**, **Mermaid**, and **Structurizr DSL** let you define diagrams in text. They’re version-controlled, CI/CD-friendly, and great for teams who treat architecture like code. The downside? Layout control and polish can be limited. +![C4 Diagram]({{ site.baseurl }}/sbreingan/assets/diagram-c4.png) -``` -@startuml -!include https://raw.githubusercontent.com/plantuml-stdlib/C4-PlantUML/master/C4_Container.puml +### 🏛️ Model-Driven Tools -LAYOUT_LEFT_RIGHT() +Enterprise tools such as Archi, Sparx Enterprise Architect, and Visual Paradigm focus on maintaining a central model and generating views from it. This ensures consistency across diagrams and supports traceability — linking requirements to architecture and even to implementation. -Person(user, "End User", "Calls the public API") +These tools are powerful but require discipline and effort to keep up to date. They are best suited for large organisations with formal architecture governance or regulated environments where long-lived models are essential. -System_Boundary(sys, "Serverless API System") { - Container(apiGw, "API Gateway", "Amazon API Gateway", "Entry point for HTTPS clients; routing & auth") - Container(lambdaFn, "Lambda Function", "AWS Lambda", "Executes business logic for incoming requests") - ContainerDb(backend, "Backend Service", "Database / Internal Service", "Stores and retrieves application data") -} +![Archi Mate]({{ site.baseurl }}/sbreingan/assets/diagram-archimate.png) -Rel(user, apiGw, "Invokes API", "HTTPS/JSON") -Rel(apiGw, lambdaFn, "Triggers", "Lambda integration") -Rel(lambdaFn, backend, "Reads/Writes data", "SDK / JDBC") +### ✍️ Visual Diagramming Tools -@enduml -``` +Tools like Lucidchart, [Miro](https://www.miro.com), [draw.io](https://www.drawio.com/) prioriste collaboration and being simple to use. They mimic the experience of sketching on a whiteboard but add features like templates, real-time collaboration, and cloud storage. -![C4 Diagram]({{ site.baseurl }}/sbreingan/assets/diagram-c4.png) +These tools are great for workshops and stakeholder engagement, but they lack an underlying model. As a result, they can become inconsistent and hard to maintain as systems grow. -- **Model-Driven Tools**: Enterprise tools like **Sparx**, **Archi**, and **Visual Paradigm** focus on maintaining a central model and generating views from it. These are powerful but require discipline and effort to keep up to date. +### ☁️ Cloud-Specific Tools +Tools like [Cloudcraft](https://www.cloudcraft.co/), [Hava](https://www.hava.io/), [AWS Workload Discovery](https://aws.amazon.com/solutions/implementations/workload-discovery-on-aws/), and Azure Resource Visualizer integrate with live cloud environments to auto-generate diagrams. They can reflect the actual state of deployed systems, which is invaluable for audits, onboarding, and operational visibility. -![Archi Mate]({{ site.baseurl }}/sbreingan/assets/diagram-archimate.png) +These tools can even integrate with Infrastructure as Code (e.g., Terraform) to generate diagrams from real deployment scripts. However, they are less useful for future-state design and offer limited control over layout and emphasis. + +![CloudCraft]({{ site.baseurl }}/sbreingan/assets/diagram-cloudcraft.png) -- **Visual Diagramming Tools**: Tools like **Lucidchart**, **Miro**, and **diagrams.net** are intuitive and collaborative. They’re great for workshops and quick sketches but lack model consistency and versioning. -- **Cloud-Specific Tools**: Tools like **Cloudcraft**, **Hava**, and vendor-native options like **AWS Workload Discovery** or **Azure Resource Visualizer** can auto-generate diagrams from live environments. These are brilliant for discovery and documentation — less so for future design. +--- +## Future Direction: AI-Generated Diagrams -![CloudCraft]({{ site.baseurl }}/sbreingan/assets/diagram-cloudcraft.png) +As systems grow more complex and teams become more distributed, the need for fast, accurate, and adaptive architecture communication increases. AI-generated diagrams offer a promising future direction. + +Imagine being able to ask: +> “Show me how the payment service interacts with identity.” +And instantly receive a diagram generated from your codebase, IaC templates, or telemetry data. + +### Potential Applications +- **Code-to-diagram translation**: Automatically generate C4 or sequence diagrams from annotated code or Terraform scripts. +- **Live system introspection**: Use observability data to generate real-time architecture views. +- **Threat modelling automation**: AI interprets STRIDE or PASTA inputs and generates visual threat maps. +- **Natural language prompts**: Query architecture in plain English and receive diagrams tailored to your question. + +### Benefits +- Reduces manual effort and diagram drift. +- Enables non-technical stakeholders to explore architecture visually. +- Supports continuous documentation in CI/CD pipelines. + +### Challenges +- Ensuring accuracy and trust in generated views. +- Balancing automation with human intent and storytelling. +- Integrating with existing modelling tools and repositories. + +### Tools to Watch +- GPT-based plugins for Structurizr or Mermaid. +- AI-enhanced IDEs that generate diagrams from code context. +- Cloud-native AI visualizers that interpret Terraform or CloudFormation. --- -## Choosing the Right Tool (and Asking the Right Questions) +## Choosing the Right Tool + +There’s no single “best” tool — the right choice depends on: + +- **Why** the diagram is being created: + - Is it for a pitch deck or a long-lived artifact? + - Does it need to meet regulatory or audit requirements? -Ultimately, the tool you choose should reflect: +- **Who** will maintain it: + - Are they comfortable with code-based tools? + - Is it part of a CI/CD workflow? -- **Why** you’re creating the diagram — is it for a pitch deck or a long-lived artifact? -- **Who** will maintain it — are they comfortable with code-based tools? -- **How complex** the architecture is — does it justify a formal model? +- **How complex** the architecture is: + - Does it justify a formal model? + - Will multiple views need to stay consistent over time? -And most importantly: **Is this diagram useful?** If it doesn’t help the intended audience understand what they need to, it’s just decoration. +Above all, ask: **Is this diagram useful?** From 6e643c99c74056fe7c133030a6b9d600c31fad56 Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Mon, 17 Nov 2025 13:56:21 +0000 Subject: [PATCH 03/18] Updated content --- .../2025-11-12-communicating-architecture.md | 27 +++++++++++++++++++ 1 file changed, 27 insertions(+) diff --git a/_posts/2025-11-12-communicating-architecture.md b/_posts/2025-11-12-communicating-architecture.md index 727b493ea6..670bd1863b 100644 --- a/_posts/2025-11-12-communicating-architecture.md +++ b/_posts/2025-11-12-communicating-architecture.md @@ -1,3 +1,14 @@ +--- +title: Communicating Architecture with Diagrams +date: 2025-11-17 00:00:00 Z +categories: +- Architecture +- Tech +author: sbreingan +summary: An overview of approaches on how we communicate architecture +--- + + # Communicating Architecture: From Whiteboards to Models One of the most important responsibilities of a software architect is **communicating architecture effectively**. Whether you're sketching out a new system or explaining how existing components fit together, the goal is always the same: help others understand the structure, purpose, and implications of the architecture. @@ -68,6 +79,22 @@ Tools like PlantUML, Mermaid, and Structurizr DSL allow you to define diagrams u They work particularly well when architecture needs to evolve alongside code. Diagrams can live in the same repository, be reviewed like any other code change, and even be generated automatically as part of a pipeline. The trade-off is that layout control can be limited, and the output may lack the polish of a hand-crafted diagram. +```plantuml + +@startuml !include https://raw.githubusercontent.com/plantuml-stdlib/C4-PlantUML/master/C4_Container.puml + +LAYOUT_LEFT_RIGHT() + +Person(user, “End User”, “Calls the public API”) + +System_Boundary(sys, “Serverless API System”) { Container(apiGw, “API Gateway”, “Amazon API Gateway”, “Entry point for HTTPS clients; routing & auth”) Container(lambdaFn, “Lambda Function”, “AWS Lambda”, “Executes business logic for incoming requests”) ContainerDb(backend, “Backend Service”, “Database / Internal Service”, “Stores and retrieves application data”) } + +Rel(user, apiGw, “Invokes API”, “HTTPS/JSON”) Rel(apiGw, lambdaFn, “Triggers”, “Lambda integration”) Rel(lambdaFn, backend, “Reads/Writes data”, “SDK / JDBC”) + +@enduml + +``` + ![C4 Diagram]({{ site.baseurl }}/sbreingan/assets/diagram-c4.png) ### 🏛️ Model-Driven Tools From 7f4e82b6d97ec651d39ad583ef1ab8bca43bbeb6 Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Mon, 17 Nov 2025 15:53:48 +0000 Subject: [PATCH 04/18] Added new diagram, updated text --- .../2025-11-12-communicating-architecture.md | 116 ++++++------------ sbreingan/assets/diagram-drawio.png | Bin 0 -> 13118 bytes 2 files changed, 39 insertions(+), 77 deletions(-) create mode 100644 sbreingan/assets/diagram-drawio.png diff --git a/_posts/2025-11-12-communicating-architecture.md b/_posts/2025-11-12-communicating-architecture.md index 670bd1863b..4b4e5dc15e 100644 --- a/_posts/2025-11-12-communicating-architecture.md +++ b/_posts/2025-11-12-communicating-architecture.md @@ -8,64 +8,56 @@ author: sbreingan summary: An overview of approaches on how we communicate architecture --- - # Communicating Architecture: From Whiteboards to Models -One of the most important responsibilities of a software architect is **communicating architecture effectively**. Whether you're sketching out a new system or explaining how existing components fit together, the goal is always the same: help others understand the structure, purpose, and implications of the architecture. +One of the most important responsibilities of a software architect is communicating architecture effectively. Whether you're sketching out a new system or explaining how existing components fit together, the goal is always the same: help others understand the structure, purpose, and implications of the architecture. -Architecture communication often needs to operate at multiple levels of abstraction. A CTO may want to understand strategic alignment, while an engineer might need to know how a service is deployed and monitored. The challenge is to tailor the message without losing coherence. +Architecture communication often needs to operate at multiple levels of abstraction. A CTO may want to understand strategic alignment, while an engineer might need to know how a service is deployed and monitored. The challenge is tailoring the message without losing coherence. -More often than not, this communication is **visual**. Diagrams are faster and clearer than text when conveying relationships between components, data flows, and infrastructure. But before drawing anything, we need to ask two fundamental questions: +More often than not, this communication is visual. Diagrams are faster and clearer than text when conveying relationships between components, data flows, and infrastructure. But before drawing anything, we need to ask two fundamental questions: - **What** do we want to show? - **How** should we show it? ---- - ## Modelling vs Diagramming -Many of us have been in meetings gathered around a whiteboard, sketching out boxes and arrows to explore ideas. These ad-hoc diagrams are great for rapid ideation — they help teams align quickly and visually. But they rarely survive beyond the moment. As systems grow in complexity, we need more than just sketches. We need to understand **what** we’re showing, not just **how** we’re showing it. +Many of us have been in meetings gathered around a whiteboard, sketching out boxes and arrows to explore ideas. These ad-hoc diagrams are great for rapid ideation — they help teams align quickly — but they are rarely useful outside that moment. As systems grow in complexity, sketches alone aren’t enough. We need to understand not just what we are drawing, but the underlying structure it represents. -This is where the distinction between **modelling** and **diagramming** becomes critical. +This is where we distinguish between modelling and diagramming: -- **Modelling** is the process of defining the structure of a system: its actors, components, relationships, and abstractions. It creates a consistent representation of the architecture, independent of how it's visualised. -- **Diagramming** is the act of presenting that model — a visual slice tailored to a specific audience or concern. +- **Modelling** defines the structure of a system: its actors, components, responsibilities, and relationships. It creates a consistent representation, independent of how it is visualised. +- **Diagramming** presents that model — a visual slice tailored to a specific audience or concern. -A diagram is a **view** onto a model. It highlights certain elements while omitting others, depending on the story we want to tell. +A diagram is a **view** onto a model. It highlights certain elements while omitting others, depending on the story we want to tell and who needs to understand it. -In organisations with complex digital estates, this becomes essential. Consider a single system: -- What other systems does it interact with? -- What components make up that system? -- How do those components relate to the underlying infrastructure? +Consider an organisation with multiple interacting systems. Each system may have different users (internal and external), logical components, and supporting infrastructure. The relationships between these layers can become complex very quickly. -Trying to capture all of this in a single diagram is rarely helpful. Instead, we need **multiple views**, each shaped by a specific **viewpoint**. +Trying to show all of this in a single diagram would be overwhelming. A CTO may care about high-level system interactions, while a security officer needs to understand low-level networking detail. Each stakeholder has different concerns — or **viewpoints** — and no single view can satisfy them all. -Without an underpinning model, creating multiple diagrams can lead to confusion — inconsistent boundaries, conflicting relationships, and misaligned assumptions. A shared model ensures coherence across views. +This is why we create multiple views, each shaped by a specific viewpoint and tailored to its audience. The model remains the single source of truth; the views simply expose different aspects of it. -### 🧠 Analogy: Architecture as House Plans +A helpful analogy is the architectural plans of a house. A single structural model can be used to generate: +- a **floor plan** for layout and navigation, +- an **electrical plan** for wiring and sockets, +- a **plumbing plan** for water and waste systems. -Think of the model like the structural blueprint of a house. From that blueprint, you can generate different plans: -- A **floor plan** for layout and navigation. -- An **electrical plan** for wiring and sockets. -- A **plumbing plan** for water and waste systems. +Each plan is a view of the same underlying structure, shaped by a particular discipline. If an architect moves a wall but doesn’t update the electrical or plumbing plans, the result would be chaos! -Each plan is a **view** onto the same underlying structure. If the walls, doors, and rooms aren’t aligned across these views, you end up with serious problems — wires running through non-existent walls, or pipes with nowhere to go. - -Architecture works the same way. The model is your source of truth. Diagrams are tailored views that help different people understand and work with it. - ---- +Software architecture works the same way. The model holds the truth about the system; diagrams are purposeful views that help different people understand and work with it. ## The Spectrum of Approaches When deciding how to model and create views, there’s no one-size-fits-all solution. Instead, there’s a spectrum — ranging from highly structured, formal modelling approaches to informal, free-form sketches. Each approach has its place depending on the context, audience, and longevity of the diagram. -At one end of the spectrum, we have **heavyweight and structured approaches** such as UML and [ArchiMate These approaches enforce strict semantics and provide a rich modelling language. They are ideal for enterprise-scale architecture where consistency, traceability, and alignment with frameworks like TOGAF are essential. However, they come with trade-offs: they require significant effort to maintain, a steep learning curve, and may not be accessible to non-architects. +At one end of the spectrum, we have heavyweight and structured approaches such as [UML](https://www.omg.org/uml/) and [ArchiMate](https://www.opengroup.org/archimate-forum/archimate-overview). These approaches enforce strict semantics and provide a rich modelling language. They are often used in enterprise-scale architecture where consistency, traceability, and alignment with frameworks like TOGAF are required. The trade-off is that they require significant effort to maintain, have steep learning curves, and may not be accessible to non-architects. + +In the middle, we find lightweight but structured approaches such as the [C4 Model](https://c4model.com/), which emphasise having a consistent model, but much more flexibilty and less rigous. This encourages an underlying model, but without the same level of prescriptiveness. This encourages consistency and clarity while remaining flexible enough that generating views does not become burdensome. -Moving toward the middle, we find **lightweight but structured approaches** such as C4 Model and Structurizr DSL. These techniques strike a balance by offering structure without the overhead of a full meta-model. They encourage consistency and clarity while remaining agile enough for modern development practices. AWS reference architecture diagrams also fall into this category, using standardised icons to maintain clarity. +Cloud diagrams that use AWS or Azure icon sets also sit broadly in this category. They offer a standardised visual vocabulary that improves clarity and consistency, but they stop short of providing a true modelling approach. -Finally, at the far end of the spectrum, we have **lightweight and unstructured approaches** — whiteboards, Miro, Lucidchart, and diagrams.net. These tools are perfect for early ideation and collaborative workshops. They are fast, intuitive, and flexible, but they lack an underlying model and can quickly become inconsistent as systems evolve. +At the far end of the spectrum, we have lightweight and unstructured approaches - free-form diagrams created on whiteboards or tools such as Miro, Lucidchart, and diagrams.net. These tools are perfect for generating quick and flexibile diagrams. They are fast, intuitive, and flexible, but they lack an underlying model and can quickly become inconsistent as systems evolve. -Choosing the right approach is always a trade-off between **consistency**, **flexibility**, and **complexity**. It depends on how long the diagram will live, who will maintain it, and how complex the system is. +Choosing the right approach is always a trade-off between consistency, flexibility, and complexity. It depends on how long the diagram will live, who will maintain it, and how complex the system is. ![Tooling Spectrum]({{ site.baseurl }}/sbreingan/assets/diagram-spectrum.png) @@ -79,7 +71,8 @@ Tools like PlantUML, Mermaid, and Structurizr DSL allow you to define diagrams u They work particularly well when architecture needs to evolve alongside code. Diagrams can live in the same repository, be reviewed like any other code change, and even be generated automatically as part of a pipeline. The trade-off is that layout control can be limited, and the output may lack the polish of a hand-crafted diagram. -```plantuml + +~~~ plantuml @startuml !include https://raw.githubusercontent.com/plantuml-stdlib/C4-PlantUML/master/C4_Container.puml @@ -92,8 +85,7 @@ System_Boundary(sys, “Serverless API System”) { Container(apiGw, “API Gate Rel(user, apiGw, “Invokes API”, “HTTPS/JSON”) Rel(apiGw, lambdaFn, “Triggers”, “Lambda integration”) Rel(lambdaFn, backend, “Reads/Writes data”, “SDK / JDBC”) @enduml - -``` +~~~ ![C4 Diagram]({{ site.baseurl }}/sbreingan/assets/diagram-c4.png) @@ -107,10 +99,11 @@ These tools are powerful but require discipline and effort to keep up to date. T ### ✍️ Visual Diagramming Tools -Tools like Lucidchart, [Miro](https://www.miro.com), [draw.io](https://www.drawio.com/) prioriste collaboration and being simple to use. They mimic the experience of sketching on a whiteboard but add features like templates, real-time collaboration, and cloud storage. +Tools like [Lucidchart](https://www.lucidchart.com/), [Miro](https://www.miro.com), [draw.io](https://www.drawio.com/) prioriste collaboration and being simple to use. They mimic the experience of sketching on a whiteboard but add features like templates, real-time collaboration, and cloud storage. These tools are great for workshops and stakeholder engagement, but they lack an underlying model. As a result, they can become inconsistent and hard to maintain as systems grow. +![CloudCraft]({{ site.baseurl }}/sbreingan/assets/diagram-drawio.png) ### ☁️ Cloud-Specific Tools @@ -120,55 +113,24 @@ These tools can even integrate with Infrastructure as Code (e.g., Terraform) to ![CloudCraft]({{ site.baseurl }}/sbreingan/assets/diagram-cloudcraft.png) +## What about AI-assisted diagrams? ---- - -## Future Direction: AI-Generated Diagrams - -As systems grow more complex and teams become more distributed, the need for fast, accurate, and adaptive architecture communication increases. AI-generated diagrams offer a promising future direction. - -Imagine being able to ask: -> “Show me how the payment service interacts with identity.” - -And instantly receive a diagram generated from your codebase, IaC templates, or telemetry data. +Automated diagramming tools already exist — cloud-native consoles can generate infrastructure maps and database tools can produce entity-relationship diagrams. These are useful, but they reflect the *raw state* of a system rather than a *modelled* view. They rarely show intent, abstraction, or logical groupings, and because they generate everything at once they are difficult to tailor for different audiences or architectural viewpoints. -### Potential Applications -- **Code-to-diagram translation**: Automatically generate C4 or sequence diagrams from annotated code or Terraform scripts. -- **Live system introspection**: Use observability data to generate real-time architecture views. -- **Threat modelling automation**: AI interprets STRIDE or PASTA inputs and generates visual threat maps. -- **Natural language prompts**: Query architecture in plain English and receive diagrams tailored to your question. +One of the most prominent uses of LLMs in software development is code generation. Diagram-as-code formats such as Mermaid and PlantUML make it possible to describe a model in natural language and let an LLM generate the diagram code. This can speed up early drafts, but the approach still has a major limitation: diagrams are spatial and visual, while LLMs only predict text. They cannot reliably judge whether the resulting layout is readable, balanced, or visually coherent. -### Benefits -- Reduces manual effort and diagram drift. -- Enables non-technical stakeholders to explore architecture visually. -- Supports continuous documentation in CI/CD pipelines. +To address that gap, AI features are emerging inside visual diagramming tools themselves — for example [Miro](https://miro.com/ai/diagram-ai/), [Lucidchart](https://www.lucidchart.com/pages/use-cases/diagram-with-AI), and dedicated tools like [Eraser](https://www.eraser.io/). These combine language input with layout engines, constraint solving, and interactive prompts, giving them a better chance of producing structured, visually coherent diagrams while still keeping the human in control of the modelling. -### Challenges -- Ensuring accuracy and trust in generated views. -- Balancing automation with human intent and storytelling. -- Integrating with existing modelling tools and repositories. +LLMs also have potential to support the modelling process more directly. By connecting to codebases or live infrastructure, they can answer natural-language questions (“which services call this API?”), help infer relationships, and assist with maintaining consistent architectural models that stay aligned with the real system. -### Tools to Watch -- GPT-based plugins for Structurizr or Mermaid. -- AI-enhanced IDEs that generate diagrams from code context. -- Cloud-native AI visualizers that interpret Terraform or CloudFormation. - ---- +Overall, AI in diagramming is most effective as an augmentation rather than full automation. By combining automated insights with natural-language interaction, these tools can reduce the effort required to create and maintain diagrams — while architects still provide the intent, abstraction, and viewpoint needed to communicate effectively. ## Choosing the Right Tool -There’s no single “best” tool — the right choice depends on: - -- **Why** the diagram is being created: - - Is it for a pitch deck or a long-lived artifact? - - Does it need to meet regulatory or audit requirements? - -- **Who** will maintain it: - - Are they comfortable with code-based tools? - - Is it part of a CI/CD workflow? +There’s no single “best” approach to architecture diagrams. The right tool depends on: -- **How complex** the architecture is: - - Does it justify a formal model? - - Will multiple views need to stay consistent over time? +- **Why** the diagram is being created +- **Who** will maintain it +- **How complex** the system is -Above all, ask: **Is this diagram useful?** +What matters far more than the tool itself is clarity of intent. 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date: 2025-11-17 00:00:00 Z categories: - Architecture - Tech author: sbreingan -summary: An overview of approaches on how we communicate architecture +summary: In this blog post I provide an overview of approaches in communicating architecture and explore the variety of tools that can assist. --- -# Communicating Architecture: From Whiteboards to Models +# How do we effectively communicate architecture? One of the most important responsibilities of a software architect is communicating architecture effectively. Whether you're sketching out a new system or explaining how existing components fit together, the goal is always the same: help others understand the structure, purpose, and implications of the architecture. @@ -49,23 +49,27 @@ Software architecture works the same way. The model holds the truth about the sy When deciding how to model and create views, there’s no one-size-fits-all solution. Instead, there’s a spectrum — ranging from highly structured, formal modelling approaches to informal, free-form sketches. Each approach has its place depending on the context, audience, and longevity of the diagram. -At one end of the spectrum, we have heavyweight and structured approaches such as [UML](https://www.omg.org/uml/) and [ArchiMate](https://www.opengroup.org/archimate-forum/archimate-overview). These approaches enforce strict semantics and provide a rich modelling language. They are often used in enterprise-scale architecture where consistency, traceability, and alignment with frameworks like TOGAF are required. The trade-off is that they require significant effort to maintain, have steep learning curves, and may not be accessible to non-architects. +At one end of the spectrum, we have *heavyweight and structured* approaches such as [UML](https://www.omg.org/uml/) and [ArchiMate](https://www.opengroup.org/archimate-forum/archimate-overview). These approaches enforce strict semantics and provide a rich modelling language. They are often used in enterprise-scale architecture where consistency, traceability, and alignment with frameworks like TOGAF are required. The trade-off is that they require significant effort to maintain, have steep learning curves, and may not be accessible to non-architects. -In the middle, we find lightweight but structured approaches such as the [C4 Model](https://c4model.com/), which emphasise having a consistent model, but much more flexibilty and less rigous. This encourages an underlying model, but without the same level of prescriptiveness. This encourages consistency and clarity while remaining flexible enough that generating views does not become burdensome. +In the middle, we find *lightweight but structured* approaches such as the [C4 Model](https://c4model.com/), which emphasise having a consistent model, but much more flexibilty and less rigous. This encourages an underlying model, but without the same level of prescriptiveness. This encourages consistency and clarity while remaining flexible enough that generating views does not become burdensome. Cloud diagrams that use AWS or Azure icon sets also sit broadly in this category. They offer a standardised visual vocabulary that improves clarity and consistency, but they stop short of providing a true modelling approach. -At the far end of the spectrum, we have lightweight and unstructured approaches - free-form diagrams created on whiteboards or tools such as Miro, Lucidchart, and diagrams.net. These tools are perfect for generating quick and flexibile diagrams. They are fast, intuitive, and flexible, but they lack an underlying model and can quickly become inconsistent as systems evolve. +At the far end of the spectrum, we have *lightweight and unstructured* approaches - free-form diagrams created on whiteboards or tools such as Miro, Lucidchart, and diagrams.net. These tools are perfect for generating quick and flexibile diagrams. They are fast, intuitive, and flexible, but they lack an underlying model and can quickly become inconsistent as systems evolve. Choosing the right approach is always a trade-off between consistency, flexibility, and complexity. It depends on how long the diagram will live, who will maintain it, and how complex the system is. -![Tooling Spectrum]({{ site.baseurl }}/sbreingan/assets/diagram-spectrum.png) - ## Tooling Landscape -Once you've decided how structured your approach needs to be, the next step is choosing the right tools. The tooling landscape is broad, and tools tend to fall into a few categories — each suited to different stages of the architecture lifecycle. +Once you've decided how structured your approach needs to be, the next step is choosing the right tools. -### ✍️ Diagrams as Code +The following diagram shows how different tools fit into the spectrum of different approaches. + +![Tooling Spectrum]({{ site.baseurl }}/sbreingan/assets/diagram-spectrum.png) + +These tools tend to fit into a few key categories. + +### Diagrams as Code Tools like PlantUML, Mermaid, and Structurizr DSL allow you to define diagrams using text. These are ideal for teams who treat architecture like code — enabling version control, CI/CD integration, and automated documentation. @@ -80,16 +84,21 @@ LAYOUT_LEFT_RIGHT() Person(user, “End User”, “Calls the public API”) -System_Boundary(sys, “Serverless API System”) { Container(apiGw, “API Gateway”, “Amazon API Gateway”, “Entry point for HTTPS clients; routing & auth”) Container(lambdaFn, “Lambda Function”, “AWS Lambda”, “Executes business logic for incoming requests”) ContainerDb(backend, “Backend Service”, “Database / Internal Service”, “Stores and retrieves application data”) } +System_Boundary(sys, “Serverless API System”) { + Container(apiGw, “API Gateway”, “Amazon API Gateway”, “Entry point for HTTPS clients; routing & auth”) + Container(lambdaFn, “Lambda Function”, “AWS Lambda”, “Executes business logic for incoming requests”) + ContainerDb(backend, “Backend Service”, “Database / Internal Service”, “Stores and retrieves application data”) +} -Rel(user, apiGw, “Invokes API”, “HTTPS/JSON”) Rel(apiGw, lambdaFn, “Triggers”, “Lambda integration”) Rel(lambdaFn, backend, “Reads/Writes data”, “SDK / JDBC”) +Rel(user, apiGw, “Invokes API”, “HTTPS/JSON”) Rel(apiGw, lambdaFn, “Triggers”, “Lambda integration”) +Rel(lambdaFn, backend, “Reads/Writes data”, “SDK / JDBC”) @enduml ~~~ -![C4 Diagram]({{ site.baseurl }}/sbreingan/assets/diagram-c4.png) +![C4 Diagram]({{ site.baseurl }}/sbreingan/assets/diagram-c4.png "A generated C4 Diagram from PlantUML") -### 🏛️ Model-Driven Tools +### Model-Driven Tools Enterprise tools such as Archi, Sparx Enterprise Architect, and Visual Paradigm focus on maintaining a central model and generating views from it. This ensures consistency across diagrams and supports traceability — linking requirements to architecture and even to implementation. @@ -97,7 +106,7 @@ These tools are powerful but require discipline and effort to keep up to date. T ![Archi Mate]({{ site.baseurl }}/sbreingan/assets/diagram-archimate.png) -### ✍️ Visual Diagramming Tools +### Visual Diagramming Tools Tools like [Lucidchart](https://www.lucidchart.com/), [Miro](https://www.miro.com), [draw.io](https://www.drawio.com/) prioriste collaboration and being simple to use. They mimic the experience of sketching on a whiteboard but add features like templates, real-time collaboration, and cloud storage. @@ -105,7 +114,7 @@ These tools are great for workshops and stakeholder engagement, but they lack an ![CloudCraft]({{ site.baseurl }}/sbreingan/assets/diagram-drawio.png) -### ☁️ Cloud-Specific Tools +### Cloud-Specific Tools Tools like [Cloudcraft](https://www.cloudcraft.co/), [Hava](https://www.hava.io/), [AWS Workload Discovery](https://aws.amazon.com/solutions/implementations/workload-discovery-on-aws/), and Azure Resource Visualizer integrate with live cloud environments to auto-generate diagrams. They can reflect the actual state of deployed systems, which is invaluable for audits, onboarding, and operational visibility. @@ -115,22 +124,18 @@ These tools can even integrate with Infrastructure as Code (e.g., Terraform) to ## What about AI-assisted diagrams? -Automated diagramming tools already exist — cloud-native consoles can generate infrastructure maps and database tools can produce entity-relationship diagrams. These are useful, but they reflect the *raw state* of a system rather than a *modelled* view. They rarely show intent, abstraction, or logical groupings, and because they generate everything at once they are difficult to tailor for different audiences or architectural viewpoints. +Automated diagramming tools already exist — cloud-native consoles can generate infrastructure maps and database tools can produce entity-relationship diagrams. These are useful, but they reflect the *raw state* of a system rather than a *modelled* view. They rarely show intent, abstraction, or logical grouping, and because they generate everything at once they are difficult to tailor for different audiences or architectural viewpoints. -One of the most prominent uses of LLMs in software development is code generation. Diagram-as-code formats such as Mermaid and PlantUML make it possible to describe a model in natural language and let an LLM generate the diagram code. This can speed up early drafts, but the approach still has a major limitation: diagrams are spatial and visual, while LLMs only predict text. They cannot reliably judge whether the resulting layout is readable, balanced, or visually coherent. +Because diagrams can be defined as code, we can use LLM's to help generate them in formats such as Mermaid or PlantUML from natural-language descriptions. This accelerates early drafts, but it has a core limitation: diagrams are spatial and visual, while LLMs only predict text. They cannot reliably assess whether the final layout will be readable, balanced, or meaningful. -To address that gap, AI features are emerging inside visual diagramming tools themselves — for example [Miro](https://miro.com/ai/diagram-ai/), [Lucidchart](https://www.lucidchart.com/pages/use-cases/diagram-with-AI), and dedicated tools like [Eraser](https://www.eraser.io/). These combine language input with layout engines, constraint solving, and interactive prompts, giving them a better chance of producing structured, visually coherent diagrams while still keeping the human in control of the modelling. +To address that gap, AI features are emerging inside visual diagramming tools themselves — for example [Miro](https://miro.com/ai/diagram-ai/), [Lucidchart](https://www.lucidchart.com/pages/use-cases/diagram-with-AI), and dedicated tools like [Eraser](https://www.eraser.io/). These combine language input with layout engines, constraint solving, and interactive prompts, producing more coherent visuals while still keeping the human in control of the modelling. -LLMs also have potential to support the modelling process more directly. By connecting to codebases or live infrastructure, they can answer natural-language questions (“which services call this API?”), help infer relationships, and assist with maintaining consistent architectural models that stay aligned with the real system. +LLMs also have potential to support the modelling process more directly. By connecting to codebases or live infrastructure, they can answer natural-language questions (“Which services call this API?”), help infer relationships, and assist in keeping architectural models aligned with the real system. -Overall, AI in diagramming is most effective as an augmentation rather than full automation. By combining automated insights with natural-language interaction, these tools can reduce the effort required to create and maintain diagrams — while architects still provide the intent, abstraction, and viewpoint needed to communicate effectively. +AI-assisted diagramming is most effective as augmentation rather than automation. By combining automated insights with natural-language interaction, these tools have the potential to reduce the effort of creating and maintaining diagrams — while architects still provide the intent, abstraction, and viewpoint needed for effective communication. ## Choosing the Right Tool -There’s no single “best” approach to architecture diagrams. The right tool depends on: - -- **Why** the diagram is being created -- **Who** will maintain it -- **How complex** the system is +There’s no single “best” approach to architecture diagrams. The right tool depends on **why** the diagram is being created, **who** is going to maintain it and for how long, and **how complex** the system being communciated is. -What matters far more than the tool itself is clarity of intent. Effective architectural communication starts with a solid model, chooses the right viewpoints for the audience, and uses diagrams to tell a clear and purposeful story. +What matters far more than the tool itself is clarity of intent. 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zCZJoUf331^b=*ast=+jC*1NY^=Ve3~rf5`iX?Lc3)=_Iw?AKfaTY_mw_>Oo~l65BVOcQfRenfsZIXDKcB6OCcytFL!(`Hc5Yo585^M zPkkP#QfRd~>pOJt>m_~P5(V=WbC~VF*il>t++wKPta(}rE9^xZ6a+`G!{7or8H*Zu2zm^qGCs!^%>EzE#`X5WQ_g7f) zbaLhL!@#pHzWD6yx@C6YN(X;H%AaRfbnu@CB+|k9_){MTB+|i?mu#)}KAoGLF6z4` z*i9Y$-0XBI|4fJLpFM8Ujlxopfm`d^LRZ?*)wQOHkJ0pU)qPT!PIj1*?i700 zF<~hLujyoy`+yPn#}1H>)AX=uL*QR*T%dQ|DHEhK@%-M6Bd*Z*XMI{nKPB+{k~;c* z$A#%+hyS=QiN5}wn2+9ca4Ok%QS7JsdUf+@K|0&Wr8e~QDWT6C0ev%uUvccdFctX+ r?j{VsROn+goiwK0$s#{|qO$)#X}4p5Ds0=C00000NkvXXu0mjfw#`=C literal 0 HcmV?d00001 From 0de7c0918b7d46dbc145b372ed5653a3c9bd3940 Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Mon, 17 Nov 2025 18:10:59 +0000 Subject: [PATCH 06/18] Updated blog content --- .../2025-11-12-communicating-architecture.md | 26 +++++++++---------- 1 file changed, 12 insertions(+), 14 deletions(-) diff --git a/_posts/2025-11-12-communicating-architecture.md b/_posts/2025-11-12-communicating-architecture.md index 4d0970d57d..5d82ee49c9 100644 --- a/_posts/2025-11-12-communicating-architecture.md +++ b/_posts/2025-11-12-communicating-architecture.md @@ -63,12 +63,6 @@ Choosing the right approach is always a trade-off between consistency, flexibili Once you've decided how structured your approach needs to be, the next step is choosing the right tools. -The following diagram shows how different tools fit into the spectrum of different approaches. - -![Tooling Spectrum]({{ site.baseurl }}/sbreingan/assets/diagram-spectrum.png) - -These tools tend to fit into a few key categories. - ### Diagrams as Code Tools like PlantUML, Mermaid, and Structurizr DSL allow you to define diagrams using text. These are ideal for teams who treat architecture like code — enabling version control, CI/CD integration, and automated documentation. @@ -80,18 +74,22 @@ They work particularly well when architecture needs to evolve alongside code. Di @startuml !include https://raw.githubusercontent.com/plantuml-stdlib/C4-PlantUML/master/C4_Container.puml -LAYOUT_LEFT_RIGHT() +@startuml +!include https://raw.githubusercontent.com/plantuml-stdlib/C4-PlantUML/master/C4_Container.puml -Person(user, “End User”, “Calls the public API”) +Person(user, "End User", "Calls the public API") -System_Boundary(sys, “Serverless API System”) { - Container(apiGw, “API Gateway”, “Amazon API Gateway”, “Entry point for HTTPS clients; routing & auth”) - Container(lambdaFn, “Lambda Function”, “AWS Lambda”, “Executes business logic for incoming requests”) - ContainerDb(backend, “Backend Service”, “Database / Internal Service”, “Stores and retrieves application data”) +System_Boundary(sys, "Serverless API System") { + Container(apiGw, "API Gateway", "Amazon API Gateway", "Entry point for HTTPS clients") + Container(lambdaFn, "Lambda Function", "AWS Lambda", "Executes business logic for incoming requests") + ContainerDb(backend, "Backend Service", "DynamoDB", "Stores and retrieves application data") } -Rel(user, apiGw, “Invokes API”, “HTTPS/JSON”) Rel(apiGw, lambdaFn, “Triggers”, “Lambda integration”) -Rel(lambdaFn, backend, “Reads/Writes data”, “SDK / JDBC”) +Rel(user, apiGw, "Invokes API", "HTTPS/JSON") +Rel_R(apiGw, lambdaFn, "Triggers", "Lambda integration") +Rel_D(lambdaFn, backend, "Reads/Writes data", "SDK / JDBC") + +@enduml @enduml ~~~ From 5eb1de331fce6cf58eaa96ee73f576374f44fa3f Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Mon, 17 Nov 2025 18:54:41 +0000 Subject: [PATCH 07/18] Updates to text --- .../2025-11-12-communicating-architecture.md | 47 +++++++++---------- 1 file changed, 22 insertions(+), 25 deletions(-) diff --git a/_posts/2025-11-12-communicating-architecture.md b/_posts/2025-11-12-communicating-architecture.md index 5d82ee49c9..c2069189e6 100644 --- a/_posts/2025-11-12-communicating-architecture.md +++ b/_posts/2025-11-12-communicating-architecture.md @@ -12,8 +12,6 @@ summary: In this blog post I provide an overview of approaches in communicating One of the most important responsibilities of a software architect is communicating architecture effectively. Whether you're sketching out a new system or explaining how existing components fit together, the goal is always the same: help others understand the structure, purpose, and implications of the architecture. -Architecture communication often needs to operate at multiple levels of abstraction. A CTO may want to understand strategic alignment, while an engineer might need to know how a service is deployed and monitored. The challenge is tailoring the message without losing coherence. - More often than not, this communication is visual. Diagrams are faster and clearer than text when conveying relationships between components, data flows, and infrastructure. But before drawing anything, we need to ask two fundamental questions: - **What** do we want to show? @@ -21,29 +19,29 @@ More often than not, this communication is visual. Diagrams are faster and clear ## Modelling vs Diagramming -Many of us have been in meetings gathered around a whiteboard, sketching out boxes and arrows to explore ideas. These ad-hoc diagrams are great for rapid ideation — they help teams align quickly — but they are rarely useful outside that moment. As systems grow in complexity, sketches alone aren’t enough. We need to understand not just what we are drawing, but the underlying structure it represents. +Many of us have been in meetings gathered around a whiteboard, sketching out boxes and arrows to explore ideas. These ad-hoc diagrams are great for rapid ideation — they help teams align quickly — but they are rarely useful outside that moment. As systems grow in complexity, sketches alone aren’t enough. We need a clearer understanding of the underlying structure we are trying to represent. -This is where we distinguish between modelling and diagramming: +This brings us to an important distinction: **modelling versus diagramming**. -- **Modelling** defines the structure of a system: its actors, components, responsibilities, and relationships. It creates a consistent representation, independent of how it is visualised. -- **Diagramming** presents that model — a visual slice tailored to a specific audience or concern. +- **Modelling** defines the structure of a system — its actors, components, responsibilities, and relationships. It gives us a consistent source of truth for the architecture, independent of how it is visualised. +- **Diagramming** presents that model in a particular way — a visual slice tailored to a specific audience or concern. -A diagram is a **view** onto a model. It highlights certain elements while omitting others, depending on the story we want to tell and who needs to understand it. +A diagram is therefore a **view** onto the model. It highlights certain elements while omitting others, depending on the story we need to tell. -Consider an organisation with multiple interacting systems. Each system may have different users (internal and external), logical components, and supporting infrastructure. The relationships between these layers can become complex very quickly. +But different people care about different stories. In any organisation, systems may have multiple users, internal and external teams, logical components, and supporting infrastructure. The relationships between these layers quickly become complex. -Trying to show all of this in a single diagram would be overwhelming. A CTO may care about high-level system interactions, while a security officer needs to understand low-level networking detail. Each stakeholder has different concerns — or **viewpoints** — and no single view can satisfy them all. +Trying to show everything in one diagram would be overwhelming. A CTO may care about high-level system interactions, while a security officer needs low-level networking details. Each stakeholder has different concerns — or **viewpoints** — and no single view can satisfy them all. -This is why we create multiple views, each shaped by a specific viewpoint and tailored to its audience. The model remains the single source of truth; the views simply expose different aspects of it. +This is why we create **multiple views**, each shaped by a specific **viewpoint** and tailored to its audience. The model remains the one source of truth; each view shows only the part that matters for a given concern. -A helpful analogy is the architectural plans of a house. A single structural model can be used to generate: +As an analogy, think about the the architectural plans of a house. A single structural model can be used to produce: - a **floor plan** for layout and navigation, -- an **electrical plan** for wiring and sockets, -- a **plumbing plan** for water and waste systems. +- an **electrical plan** for wiring, +- a **plumbing plan** for water and waste. -Each plan is a view of the same underlying structure, shaped by a particular discipline. If an architect moves a wall but doesn’t update the electrical or plumbing plans, the result would be chaos! +Each plan is a view of the same underlying structure, created from a different viewpoint. If an architect moves a wall but the electrical and plumbing plans aren't updated to reflect it, the result would be chaos! -Software architecture works the same way. The model holds the truth about the system; diagrams are purposeful views that help different people understand and work with it. +Software architecture works the same way. The model holds the truth about the system; diagrams are purposeful views that help different people understand and make decisions about it. ## The Spectrum of Approaches @@ -51,17 +49,17 @@ When deciding how to model and create views, there’s no one-size-fits-all solu At one end of the spectrum, we have *heavyweight and structured* approaches such as [UML](https://www.omg.org/uml/) and [ArchiMate](https://www.opengroup.org/archimate-forum/archimate-overview). These approaches enforce strict semantics and provide a rich modelling language. They are often used in enterprise-scale architecture where consistency, traceability, and alignment with frameworks like TOGAF are required. The trade-off is that they require significant effort to maintain, have steep learning curves, and may not be accessible to non-architects. -In the middle, we find *lightweight but structured* approaches such as the [C4 Model](https://c4model.com/), which emphasise having a consistent model, but much more flexibilty and less rigous. This encourages an underlying model, but without the same level of prescriptiveness. This encourages consistency and clarity while remaining flexible enough that generating views does not become burdensome. +In the middle, we find *lightweight but structured* approaches such as the [C4 Model](https://c4model.com/), which emphasise having a consistent model, but much more flexibility and less rigour. This provides an underlying model without the same level of prescriptiveness, supporting consistency and clarity while remaining flexible enough that generating views does not become burdensome. Cloud diagrams that use AWS or Azure icon sets also sit broadly in this category. They offer a standardised visual vocabulary that improves clarity and consistency, but they stop short of providing a true modelling approach. -At the far end of the spectrum, we have *lightweight and unstructured* approaches - free-form diagrams created on whiteboards or tools such as Miro, Lucidchart, and diagrams.net. These tools are perfect for generating quick and flexibile diagrams. They are fast, intuitive, and flexible, but they lack an underlying model and can quickly become inconsistent as systems evolve. +At the far end of the spectrum, we have *lightweight and unstructured* approaches - free-form diagrams created on whiteboards, both physical and virtual. This approach is perfect for generating quick and flexibile diagrams. They are fast, intuitive, and flexible, but they lack an underlying model and can quickly become inconsistent as systems evolve. Choosing the right approach is always a trade-off between consistency, flexibility, and complexity. It depends on how long the diagram will live, who will maintain it, and how complex the system is. ## Tooling Landscape -Once you've decided how structured your approach needs to be, the next step is choosing the right tools. +Once you've decided how structured your approach needs to be, the next step is choosing the right tools. Broadly speaking, diagramming and modelling tools can be grouped under the following categories. ### Diagrams as Code @@ -69,11 +67,8 @@ Tools like PlantUML, Mermaid, and Structurizr DSL allow you to define diagrams u They work particularly well when architecture needs to evolve alongside code. Diagrams can live in the same repository, be reviewed like any other code change, and even be generated automatically as part of a pipeline. The trade-off is that layout control can be limited, and the output may lack the polish of a hand-crafted diagram. - ~~~ plantuml -@startuml !include https://raw.githubusercontent.com/plantuml-stdlib/C4-PlantUML/master/C4_Container.puml - @startuml !include https://raw.githubusercontent.com/plantuml-stdlib/C4-PlantUML/master/C4_Container.puml @@ -106,7 +101,7 @@ These tools are powerful but require discipline and effort to keep up to date. T ### Visual Diagramming Tools -Tools like [Lucidchart](https://www.lucidchart.com/), [Miro](https://www.miro.com), [draw.io](https://www.drawio.com/) prioriste collaboration and being simple to use. They mimic the experience of sketching on a whiteboard but add features like templates, real-time collaboration, and cloud storage. +Tools like [Lucidchart](https://www.lucidchart.com/), [Miro](https://www.miro.com) and [draw.io](https://www.drawio.com/) prioritise collaboration and simplicity. They mimic the experience of sketching on a whiteboard but add features like templates, real-time collaboration, and cloud storage. These tools are great for workshops and stakeholder engagement, but they lack an underlying model. As a result, they can become inconsistent and hard to maintain as systems grow. @@ -132,8 +127,10 @@ LLMs also have potential to support the modelling process more directly. By conn AI-assisted diagramming is most effective as augmentation rather than automation. By combining automated insights with natural-language interaction, these tools have the potential to reduce the effort of creating and maintaining diagrams — while architects still provide the intent, abstraction, and viewpoint needed for effective communication. -## Choosing the Right Tool +## Using these approaches effectively + +Effective architecture communication is less about the tool and more about the thinking behind it. A clear model provides the structure; viewpoints help us understand what different audiences care about; and diagrams turn those ideas into views that tell the right story at the right level of abstraction. -There’s no single “best” approach to architecture diagrams. The right tool depends on **why** the diagram is being created, **who** is going to maintain it and for how long, and **how complex** the system being communciated is. +There is a wide spectrum of approaches available — from formal modelling languages like UML and ArchiMate, to lightweight frameworks such as C4, to completely free-form sketches on a whiteboard. Each has strengths depending on the context, longevity, and the decisions it needs to support. -What matters far more than the tool itself is clarity of intent. Effective architectural communication starts understanding what needs to be modelled, what the viewpoints need to be captured and how diagrams will be used to tell a clear and purposeful story. +But it isn’t the tooling that communicates architecture effectively — architects do. What matters most is clarity of intent, and ensuring that whatever we produce, with whichever tool we choose, genuinely reflects that intent. From f8315a65e2687097655336c50a23374d4caf79b5 Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Mon, 17 Nov 2025 18:56:06 +0000 Subject: [PATCH 08/18] Updated list --- _posts/2025-11-12-communicating-architecture.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/_posts/2025-11-12-communicating-architecture.md b/_posts/2025-11-12-communicating-architecture.md index c2069189e6..dc8d7c443b 100644 --- a/_posts/2025-11-12-communicating-architecture.md +++ b/_posts/2025-11-12-communicating-architecture.md @@ -35,9 +35,9 @@ Trying to show everything in one diagram would be overwhelming. A CTO may care a This is why we create **multiple views**, each shaped by a specific **viewpoint** and tailored to its audience. The model remains the one source of truth; each view shows only the part that matters for a given concern. As an analogy, think about the the architectural plans of a house. A single structural model can be used to produce: -- a **floor plan** for layout and navigation, -- an **electrical plan** for wiring, -- a **plumbing plan** for water and waste. + - a **floor plan** for layout and navigation, + - an **electrical plan** for wiring, + - a **plumbing plan** for water and waste. Each plan is a view of the same underlying structure, created from a different viewpoint. If an architect moves a wall but the electrical and plumbing plans aren't updated to reflect it, the result would be chaos! From 9ce698d669809dbaf164defabf855bfd22623ed1 Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Tue, 18 Nov 2025 08:55:59 +0000 Subject: [PATCH 09/18] Updated content and fixed image link --- _posts/2025-11-12-communicating-architecture.md | 14 ++++++++------ .../assets/{diagram_aws.png => diagram-aws.png} | Bin 2 files changed, 8 insertions(+), 6 deletions(-) rename sbreingan/assets/{diagram_aws.png => diagram-aws.png} (100%) diff --git a/_posts/2025-11-12-communicating-architecture.md b/_posts/2025-11-12-communicating-architecture.md index dc8d7c443b..ada18074a3 100644 --- a/_posts/2025-11-12-communicating-architecture.md +++ b/_posts/2025-11-12-communicating-architecture.md @@ -10,11 +10,13 @@ summary: In this blog post I provide an overview of approaches in communicating # How do we effectively communicate architecture? -One of the most important responsibilities of a software architect is communicating architecture effectively. Whether you're sketching out a new system or explaining how existing components fit together, the goal is always the same: help others understand the structure, purpose, and implications of the architecture. +One of the key responsibilities of a software architect is communicating architecture effectively. Architecture never exists in a vacuum — it exists to align people, guide decisions, and help teams move toward the same goals. Whether you're sketching a new system or explaining how existing components fit together, effective communication means helping others understand the structure, purpose, and implications of the architecture. -More often than not, this communication is visual. Diagrams are faster and clearer than text when conveying relationships between components, data flows, and infrastructure. But before drawing anything, we need to ask two fundamental questions: +While it’s possible to describe a system using a wall of text, it’s rarely the best way. Architecture is complex, and most of the time the fastest and clearest way to convey it is visually. Diagrams help people see relationships, boundaries, and flows at a glance. -- **What** do we want to show? +But before drawing anything, it’s important to pause and ask two fundamental questions: + +- **What** do we want to show? - **How** should we show it? ## Modelling vs Diagramming @@ -97,7 +99,7 @@ Enterprise tools such as Archi, Sparx Enterprise Architect, and Visual Paradigm These tools are powerful but require discipline and effort to keep up to date. They are best suited for large organisations with formal architecture governance or regulated environments where long-lived models are essential. -![Archi Mate]({{ site.baseurl }}/sbreingan/assets/diagram-archimate.png) +![Archi Mate]({{ site.baseurl }}/sbreingan/assets/diagram-archimate.png "A diagram and model created in Archi") ### Visual Diagramming Tools @@ -105,7 +107,7 @@ Tools like [Lucidchart](https://www.lucidchart.com/), [Miro](https://www.miro.co These tools are great for workshops and stakeholder engagement, but they lack an underlying model. As a result, they can become inconsistent and hard to maintain as systems grow. -![CloudCraft]({{ site.baseurl }}/sbreingan/assets/diagram-drawio.png) +![CloudCraft]({{ site.baseurl }}/sbreingan/assets/diagram-drawio.png "A diagram created in draw.io") ### Cloud-Specific Tools @@ -113,7 +115,7 @@ Tools like [Cloudcraft](https://www.cloudcraft.co/), [Hava](https://www.hava.io/ These tools can even integrate with Infrastructure as Code (e.g., Terraform) to generate diagrams from real deployment scripts. However, they are less useful for future-state design and offer limited control over layout and emphasis. -![CloudCraft]({{ site.baseurl }}/sbreingan/assets/diagram-cloudcraft.png) +![CloudCraft]({{ site.baseurl }}/sbreingan/assets/diagram-aws.png "A diagram created in CloudCraft") ## What about AI-assisted diagrams? diff --git a/sbreingan/assets/diagram_aws.png b/sbreingan/assets/diagram-aws.png similarity index 100% rename from sbreingan/assets/diagram_aws.png rename to sbreingan/assets/diagram-aws.png From 4318d1778706473526c27f9f396d809493380005 Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Tue, 18 Nov 2025 09:05:08 +0000 Subject: [PATCH 10/18] Removed title --- _posts/2025-11-12-communicating-architecture.md | 2 -- 1 file changed, 2 deletions(-) diff --git a/_posts/2025-11-12-communicating-architecture.md b/_posts/2025-11-12-communicating-architecture.md index ada18074a3..cbac0e5485 100644 --- a/_posts/2025-11-12-communicating-architecture.md +++ b/_posts/2025-11-12-communicating-architecture.md @@ -8,8 +8,6 @@ author: sbreingan summary: In this blog post I provide an overview of approaches in communicating architecture and explore the variety of tools that can assist. --- -# How do we effectively communicate architecture? - One of the key responsibilities of a software architect is communicating architecture effectively. Architecture never exists in a vacuum — it exists to align people, guide decisions, and help teams move toward the same goals. Whether you're sketching a new system or explaining how existing components fit together, effective communication means helping others understand the structure, purpose, and implications of the architecture. While it’s possible to describe a system using a wall of text, it’s rarely the best way. Architecture is complex, and most of the time the fastest and clearest way to convey it is visually. Diagrams help people see relationships, boundaries, and flows at a glance. From fdd3fd89e9df7480a50f9c9094b3cc62f7f036fd Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Tue, 18 Nov 2025 09:09:00 +0000 Subject: [PATCH 11/18] Updated summary --- _posts/2025-11-12-communicating-architecture.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_posts/2025-11-12-communicating-architecture.md b/_posts/2025-11-12-communicating-architecture.md index cbac0e5485..a5a3a22c20 100644 --- a/_posts/2025-11-12-communicating-architecture.md +++ b/_posts/2025-11-12-communicating-architecture.md @@ -5,7 +5,7 @@ categories: - Architecture - Tech author: sbreingan -summary: In this blog post I provide an overview of approaches in communicating architecture and explore the variety of tools that can assist. +summary: One of the key responsibilities of a software architect is communicating effectively. This post explores the approaches and tools that can help. --- One of the key responsibilities of a software architect is communicating architecture effectively. Architecture never exists in a vacuum — it exists to align people, guide decisions, and help teams move toward the same goals. Whether you're sketching a new system or explaining how existing components fit together, effective communication means helping others understand the structure, purpose, and implications of the architecture. From 9d72dd2edb68ac8800365c247597523a3a4945a7 Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Tue, 18 Nov 2025 09:58:24 +0000 Subject: [PATCH 12/18] Added extra diagrams --- .../2025-11-12-communicating-architecture.md | 15 ++++++++------- sbreingan/assets/diagram-c4.png | Bin 25824 -> 47212 bytes sbreingan/assets/spectrum-approach.png | Bin 0 -> 84425 bytes 3 files changed, 8 insertions(+), 7 deletions(-) create mode 100644 sbreingan/assets/spectrum-approach.png diff --git a/_posts/2025-11-12-communicating-architecture.md b/_posts/2025-11-12-communicating-architecture.md index a5a3a22c20..6fa9e68c3c 100644 --- a/_posts/2025-11-12-communicating-architecture.md +++ b/_posts/2025-11-12-communicating-architecture.md @@ -34,7 +34,7 @@ Trying to show everything in one diagram would be overwhelming. A CTO may care a This is why we create **multiple views**, each shaped by a specific **viewpoint** and tailored to its audience. The model remains the one source of truth; each view shows only the part that matters for a given concern. -As an analogy, think about the the architectural plans of a house. A single structural model can be used to produce: +As an analogy, think about the architectural plans of a house. A single structural model can be used to produce: - a **floor plan** for layout and navigation, - an **electrical plan** for wiring, - a **plumbing plan** for water and waste. @@ -53,10 +53,13 @@ In the middle, we find *lightweight but structured* approaches such as the [C4 M Cloud diagrams that use AWS or Azure icon sets also sit broadly in this category. They offer a standardised visual vocabulary that improves clarity and consistency, but they stop short of providing a true modelling approach. -At the far end of the spectrum, we have *lightweight and unstructured* approaches - free-form diagrams created on whiteboards, both physical and virtual. This approach is perfect for generating quick and flexibile diagrams. They are fast, intuitive, and flexible, but they lack an underlying model and can quickly become inconsistent as systems evolve. +At the far end of the spectrum, we have *lightweight and unstructured* approaches - free-form diagrams created on whiteboards, both physical and virtual. This approach is perfect for generating quick and flexible diagrams. They are fast, intuitive, and flexible, but they lack an underlying model and can quickly become inconsistent as systems evolve. Choosing the right approach is always a trade-off between consistency, flexibility, and complexity. It depends on how long the diagram will live, who will maintain it, and how complex the system is. +![Spectrum of Approaches]({{ site.baseurl }}/sbreingan/assets/spectrum-approaches.png "Spectrum of different approaches") + + ## Tooling Landscape Once you've decided how structured your approach needs to be, the next step is choosing the right tools. Broadly speaking, diagramming and modelling tools can be grouped under the following categories. @@ -84,8 +87,6 @@ Rel(user, apiGw, "Invokes API", "HTTPS/JSON") Rel_R(apiGw, lambdaFn, "Triggers", "Lambda integration") Rel_D(lambdaFn, backend, "Reads/Writes data", "SDK / JDBC") -@enduml - @enduml ~~~ @@ -105,13 +106,13 @@ Tools like [Lucidchart](https://www.lucidchart.com/), [Miro](https://www.miro.co These tools are great for workshops and stakeholder engagement, but they lack an underlying model. As a result, they can become inconsistent and hard to maintain as systems grow. -![CloudCraft]({{ site.baseurl }}/sbreingan/assets/diagram-drawio.png "A diagram created in draw.io") +![draw.io]({{ site.baseurl }}/sbreingan/assets/diagram-drawio.png "A diagram created in draw.io") ### Cloud-Specific Tools -Tools like [Cloudcraft](https://www.cloudcraft.co/), [Hava](https://www.hava.io/), [AWS Workload Discovery](https://aws.amazon.com/solutions/implementations/workload-discovery-on-aws/), and Azure Resource Visualizer integrate with live cloud environments to auto-generate diagrams. They can reflect the actual state of deployed systems, which is invaluable for audits, onboarding, and operational visibility. +Tools like [Cloudcraft](https://www.cloudcraft.co/), [Hava](https://www.hava.io/) and [AWS Workload Discovery](https://aws.amazon.com/solutions/implementations/workload-discovery-on-aws/) integrate with live cloud environments to auto-generate diagrams. They can reflect the actual state of deployed systems which can be helpful for audits, onboarding, and operational visibility. These tools can also integrate with Infrastructure as Code (e.g., Terraform) to generate diagrams from real deployment scripts. -These tools can even integrate with Infrastructure as Code (e.g., Terraform) to generate diagrams from real deployment scripts. 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1356f1b3b5c0b995d198c64618415b52c382d666 Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Tue, 18 Nov 2025 10:00:04 +0000 Subject: [PATCH 13/18] Fixed some styling --- _posts/2025-11-12-communicating-architecture.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/_posts/2025-11-12-communicating-architecture.md b/_posts/2025-11-12-communicating-architecture.md index 6fa9e68c3c..35a3588451 100644 --- a/_posts/2025-11-12-communicating-architecture.md +++ b/_posts/2025-11-12-communicating-architecture.md @@ -47,13 +47,13 @@ Software architecture works the same way. The model holds the truth about the sy When deciding how to model and create views, there’s no one-size-fits-all solution. Instead, there’s a spectrum — ranging from highly structured, formal modelling approaches to informal, free-form sketches. Each approach has its place depending on the context, audience, and longevity of the diagram. -At one end of the spectrum, we have *heavyweight and structured* approaches such as [UML](https://www.omg.org/uml/) and [ArchiMate](https://www.opengroup.org/archimate-forum/archimate-overview). These approaches enforce strict semantics and provide a rich modelling language. They are often used in enterprise-scale architecture where consistency, traceability, and alignment with frameworks like TOGAF are required. The trade-off is that they require significant effort to maintain, have steep learning curves, and may not be accessible to non-architects. +At one end of the spectrum, we have **heavyweight and structured** approaches such as [UML](https://www.omg.org/uml/) and [ArchiMate](https://www.opengroup.org/archimate-forum/archimate-overview). These approaches enforce strict semantics and provide a rich modelling language. They are often used in enterprise-scale architecture where consistency, traceability, and alignment with frameworks like TOGAF are required. The trade-off is that they require significant effort to maintain, have steep learning curves, and may not be accessible to non-architects. -In the middle, we find *lightweight but structured* approaches such as the [C4 Model](https://c4model.com/), which emphasise having a consistent model, but much more flexibility and less rigour. This provides an underlying model without the same level of prescriptiveness, supporting consistency and clarity while remaining flexible enough that generating views does not become burdensome. +In the middle, we find **lightweight but structured** approaches such as the [C4 Model](https://c4model.com/), which emphasise having a consistent model, but much more flexibility and less rigour. This provides an underlying model without the same level of prescriptiveness, supporting consistency and clarity while remaining flexible enough that generating views does not become burdensome. Cloud diagrams that use AWS or Azure icon sets also sit broadly in this category. They offer a standardised visual vocabulary that improves clarity and consistency, but they stop short of providing a true modelling approach. -At the far end of the spectrum, we have *lightweight and unstructured* approaches - free-form diagrams created on whiteboards, both physical and virtual. This approach is perfect for generating quick and flexible diagrams. They are fast, intuitive, and flexible, but they lack an underlying model and can quickly become inconsistent as systems evolve. +At the far end of the spectrum, we have **lightweight and unstructured** approaches - free-form diagrams created on whiteboards, both physical and virtual. This approach is perfect for generating quick and flexible diagrams. They are fast, intuitive, and flexible, but they lack an underlying model and can quickly become inconsistent as systems evolve. Choosing the right approach is always a trade-off between consistency, flexibility, and complexity. It depends on how long the diagram will live, who will maintain it, and how complex the system is. From 378a4490343a983d3a6cb092c9fd039ca593c794 Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Tue, 18 Nov 2025 10:09:14 +0000 Subject: [PATCH 14/18] Fixed image link --- _posts/2025-11-12-communicating-architecture.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/_posts/2025-11-12-communicating-architecture.md b/_posts/2025-11-12-communicating-architecture.md index 35a3588451..1c222ff22b 100644 --- a/_posts/2025-11-12-communicating-architecture.md +++ b/_posts/2025-11-12-communicating-architecture.md @@ -35,6 +35,7 @@ Trying to show everything in one diagram would be overwhelming. A CTO may care a This is why we create **multiple views**, each shaped by a specific **viewpoint** and tailored to its audience. The model remains the one source of truth; each view shows only the part that matters for a given concern. As an analogy, think about the architectural plans of a house. A single structural model can be used to produce: + - a **floor plan** for layout and navigation, - an **electrical plan** for wiring, - a **plumbing plan** for water and waste. @@ -57,7 +58,7 @@ At the far end of the spectrum, we have **lightweight and unstructured** approac Choosing the right approach is always a trade-off between consistency, flexibility, and complexity. It depends on how long the diagram will live, who will maintain it, and how complex the system is. -![Spectrum of Approaches]({{ site.baseurl }}/sbreingan/assets/spectrum-approaches.png "Spectrum of different approaches") +![Spectrum of Approaches]({{ site.baseurl }}/sbreingan/assets/spectrum-approach.png "Spectrum of different approaches") ## Tooling Landscape From 4a15a91b8fa35d06f13d125a5c212a7e7f7e0a16 Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Tue, 18 Nov 2025 10:40:21 +0000 Subject: [PATCH 15/18] Updated content --- .../2025-11-12-communicating-architecture.md | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/_posts/2025-11-12-communicating-architecture.md b/_posts/2025-11-12-communicating-architecture.md index 1c222ff22b..af5fdd5870 100644 --- a/_posts/2025-11-12-communicating-architecture.md +++ b/_posts/2025-11-12-communicating-architecture.md @@ -46,17 +46,17 @@ Software architecture works the same way. The model holds the truth about the sy ## The Spectrum of Approaches -When deciding how to model and create views, there’s no one-size-fits-all solution. Instead, there’s a spectrum — ranging from highly structured, formal modelling approaches to informal, free-form sketches. Each approach has its place depending on the context, audience, and longevity of the diagram. +When deciding how to model and create views, there’s no one-size-fits-all solution. Instead, there’s a spectrum - ranging from highly structured, formal modelling approaches to informal, free-form sketches. Each approach has its place depending on the context, audience, and longevity of the diagram. At one end of the spectrum, we have **heavyweight and structured** approaches such as [UML](https://www.omg.org/uml/) and [ArchiMate](https://www.opengroup.org/archimate-forum/archimate-overview). These approaches enforce strict semantics and provide a rich modelling language. They are often used in enterprise-scale architecture where consistency, traceability, and alignment with frameworks like TOGAF are required. The trade-off is that they require significant effort to maintain, have steep learning curves, and may not be accessible to non-architects. -In the middle, we find **lightweight but structured** approaches such as the [C4 Model](https://c4model.com/), which emphasise having a consistent model, but much more flexibility and less rigour. This provides an underlying model without the same level of prescriptiveness, supporting consistency and clarity while remaining flexible enough that generating views does not become burdensome. +In the middle, we find **lightweight but structured** approaches such as the [C4 Model](https://c4model.com/), which emphasise maintaining a consistent underlying model, but with far less formality. This supports clarity and coherence without the prescriptiveness of a full modelling language, and makes producing and evolving views far more manageable. Cloud diagrams that use AWS or Azure icon sets also sit broadly in this category. They offer a standardised visual vocabulary that improves clarity and consistency, but they stop short of providing a true modelling approach. -At the far end of the spectrum, we have **lightweight and unstructured** approaches - free-form diagrams created on whiteboards, both physical and virtual. This approach is perfect for generating quick and flexible diagrams. They are fast, intuitive, and flexible, but they lack an underlying model and can quickly become inconsistent as systems evolve. +At the far end of the spectrum, we have **lightweight and unstructured** approaches - free-form diagrams created on whiteboards, both physical and virtual. These are ideal for exploring or conveying an idea quickly and for collaborative workshops. They are fast, intuitive, and unconstrained, but they lack an underlying model and can quickly become inconsistent as systems evolve. -Choosing the right approach is always a trade-off between consistency, flexibility, and complexity. It depends on how long the diagram will live, who will maintain it, and how complex the system is. +Choosing the right approach is always a trade-off between consistency, governance, and ease of use. It depends on how long the diagram will live, who will maintain it, and how complex the system is. ![Spectrum of Approaches]({{ site.baseurl }}/sbreingan/assets/spectrum-approach.png "Spectrum of different approaches") @@ -111,19 +111,19 @@ These tools are great for workshops and stakeholder engagement, but they lack an ### Cloud-Specific Tools -Tools like [Cloudcraft](https://www.cloudcraft.co/), [Hava](https://www.hava.io/) and [AWS Workload Discovery](https://aws.amazon.com/solutions/implementations/workload-discovery-on-aws/) integrate with live cloud environments to auto-generate diagrams. They can reflect the actual state of deployed systems which can be helpful for audits, onboarding, and operational visibility. These tools can also integrate with Infrastructure as Code (e.g., Terraform) to generate diagrams from real deployment scripts. +Tools like [Cloudcraft](https://www.cloudcraft.co/), [Hava](https://www.hava.io/), and [AWS Workload Discovery](https://aws.amazon.com/solutions/implementations/workload-discovery-on-aws/) integrate with live cloud environments to automatically generate diagrams. These tools reflect the *actual* state of deployed systems, which is invaluable for audits, onboarding, troubleshooting, and operational visibility. Many can also ingest Infrastructure as Code (e.g., Terraform) to visualise deployments directly from source. -They are less useful for future-state design and offer limited control over layout and emphasis, meaning it can be hard to convey the logical meaning of what the instructure. +Although automation makes these diagrams quick to produce, it also constrains them. Because they mirror the raw cloud resources exactly as they exist, there is very little scope for layout, grouping, or abstraction. As a result, they are not well suited to **future-state design**, architectural storytelling, or conveying **logical intent** rather than physical infrastructure. ![CloudCraft]({{ site.baseurl }}/sbreingan/assets/diagram-aws.png "A diagram created in CloudCraft") ## What about AI-assisted diagrams? -Automated diagramming tools already exist — cloud-native consoles can generate infrastructure maps and database tools can produce entity-relationship diagrams. These are useful, but they reflect the *raw state* of a system rather than a *modelled* view. They rarely show intent, abstraction, or logical grouping, and because they generate everything at once they are difficult to tailor for different audiences or architectural viewpoints. +LLMs introduce a new angle: because diagrams can be defined as code, we can now generate formats such as Mermaid or PlantUML directly from natural-language descriptions. This makes it much faster to produce early drafts and explore different ways of expressing a model. -Because diagrams can be defined as code, we can use LLM's to help generate them in formats such as Mermaid or PlantUML from natural-language descriptions. This accelerates early drafts, but it has a core limitation: diagrams are spatial and visual, while LLMs only predict text. They cannot reliably assess whether the final layout will be readable, balanced, or meaningful. +But this approach has a fundamental limitation: diagrams are spatial and visual, while LLMs predict text. An LLM can create valid syntax, but it cannot reliably judge whether a diagram will be readable, balanced, or visually coherent. -To address that gap, AI features are emerging inside visual diagramming tools themselves — for example [Miro](https://miro.com/ai/diagram-ai/), [Lucidchart](https://www.lucidchart.com/pages/use-cases/diagram-with-AI), and dedicated tools like [Eraser](https://www.eraser.io/). These combine language input with layout engines, constraint solving, and interactive prompts, producing more coherent visuals while still keeping the human in control of the modelling. +To address this gap, AI features are emerging inside visual diagramming tools themselves — for example [Miro](https://miro.com/ai/diagram-ai/), [Lucidchart](https://www.lucidchart.com/pages/use-cases/diagram-with-AI), and dedicated tools like [Eraser](https://www.eraser.io/). These combine language input with layout engines, constraint solving, and interactive prompts, producing more coherent visuals while still keeping the human in control of the modelling. LLMs also have potential to support the modelling process more directly. By connecting to codebases or live infrastructure, they can answer natural-language questions (“Which services call this API?”), help infer relationships, and assist in keeping architectural models aligned with the real system. From 7da95c138d197a9af66566a173d6889b792785d6 Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Thu, 20 Nov 2025 15:31:18 +0000 Subject: [PATCH 16/18] Updated blog content and date --- ...itecture.md => 2025-11-20-communicating-architecture.md} | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) rename _posts/{2025-11-12-communicating-architecture.md => 2025-11-20-communicating-architecture.md} (95%) diff --git a/_posts/2025-11-12-communicating-architecture.md b/_posts/2025-11-20-communicating-architecture.md similarity index 95% rename from _posts/2025-11-12-communicating-architecture.md rename to _posts/2025-11-20-communicating-architecture.md index af5fdd5870..0971f3c9f5 100644 --- a/_posts/2025-11-12-communicating-architecture.md +++ b/_posts/2025-11-20-communicating-architecture.md @@ -1,6 +1,6 @@ --- title: How Do We Effectively Communicate Architecture? -date: 2025-11-17 00:00:00 Z +date: 2025-11-20 00:00:00 Z categories: - Architecture - Tech @@ -123,9 +123,9 @@ LLMs introduce a new angle: because diagrams can be defined as code, we can now But this approach has a fundamental limitation: diagrams are spatial and visual, while LLMs predict text. An LLM can create valid syntax, but it cannot reliably judge whether a diagram will be readable, balanced, or visually coherent. -To address this gap, AI features are emerging inside visual diagramming tools themselves — for example [Miro](https://miro.com/ai/diagram-ai/), [Lucidchart](https://www.lucidchart.com/pages/use-cases/diagram-with-AI), and dedicated tools like [Eraser](https://www.eraser.io/). These combine language input with layout engines, constraint solving, and interactive prompts, producing more coherent visuals while still keeping the human in control of the modelling. +To address this gap, AI features are emerging inside visual diagramming tools themselves — for example [Miro](https://miro.com/ai/diagram-ai/), [Lucidchart](https://www.lucidchart.com/pages/use-cases/diagram-with-AI), and dedicated tools like [Eraser](https://www.eraser.io/). These may be able to more intelligently integrate with layout engines and can prompt a user to clarify their intent; producing more coherent visuals while still keeping a human in the loop. AI tools are also being integrated directly into code-bases to generate documenation, including diagrams - such as Google's [CodeWiki](https://codewiki.google/) or Devin's [DeepWiki][https://deepwiki.com/]. -LLMs also have potential to support the modelling process more directly. By connecting to codebases or live infrastructure, they can answer natural-language questions (“Which services call this API?”), help infer relationships, and assist in keeping architectural models aligned with the real system. +LLMs also have potential to support the modelling process more directly. By connecting to codebases or live infrastructure, they can answer natural-language questions (“Which services call this API?”), help infer relationships, and assist in keeping architectural models aligned with the real system. Some examples are AI-assisted diagramming is most effective as augmentation rather than automation. By combining automated insights with natural-language interaction, these tools have the potential to reduce the effort of creating and maintaining diagrams — while architects still provide the intent, abstraction, and viewpoint needed for effective communication. From 3ce3679f744e388e4823bf5df15702f0ef0e4fa9 Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Thu, 20 Nov 2025 15:48:56 +0000 Subject: [PATCH 17/18] Fixed link. --- _posts/2025-11-20-communicating-architecture.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_posts/2025-11-20-communicating-architecture.md b/_posts/2025-11-20-communicating-architecture.md index 0971f3c9f5..85cb9482c6 100644 --- a/_posts/2025-11-20-communicating-architecture.md +++ b/_posts/2025-11-20-communicating-architecture.md @@ -123,7 +123,7 @@ LLMs introduce a new angle: because diagrams can be defined as code, we can now But this approach has a fundamental limitation: diagrams are spatial and visual, while LLMs predict text. An LLM can create valid syntax, but it cannot reliably judge whether a diagram will be readable, balanced, or visually coherent. -To address this gap, AI features are emerging inside visual diagramming tools themselves — for example [Miro](https://miro.com/ai/diagram-ai/), [Lucidchart](https://www.lucidchart.com/pages/use-cases/diagram-with-AI), and dedicated tools like [Eraser](https://www.eraser.io/). These may be able to more intelligently integrate with layout engines and can prompt a user to clarify their intent; producing more coherent visuals while still keeping a human in the loop. AI tools are also being integrated directly into code-bases to generate documenation, including diagrams - such as Google's [CodeWiki](https://codewiki.google/) or Devin's [DeepWiki][https://deepwiki.com/]. +To address this gap, AI features are emerging inside visual diagramming tools themselves — for example [Miro](https://miro.com/ai/diagram-ai/), [Lucidchart](https://www.lucidchart.com/pages/use-cases/diagram-with-AI), and dedicated tools like [Eraser](https://www.eraser.io/). These may be able to more intelligently integrate with layout engines and can prompt a user to clarify their intent; producing more coherent visuals while still keeping a human in the loop. AI tools are also being integrated directly into code-bases to generate documenation, including diagrams - such as Google's [CodeWiki](https://codewiki.google/) or Devin's [DeepWiki](https://deepwiki.com/). LLMs also have potential to support the modelling process more directly. By connecting to codebases or live infrastructure, they can answer natural-language questions (“Which services call this API?”), help infer relationships, and assist in keeping architectural models aligned with the real system. Some examples are From 3454793687021df0c277eb75d54c313407d5a3bc Mon Sep 17 00:00:00 2001 From: Stuart Breingan Date: Fri, 21 Nov 2025 12:50:11 +0000 Subject: [PATCH 18/18] Updated date and description. --- ...hitecture.md => 2025-11-21-communicating-architecture.md} | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) rename _posts/{2025-11-20-communicating-architecture.md => 2025-11-21-communicating-architecture.md} (98%) diff --git a/_posts/2025-11-20-communicating-architecture.md b/_posts/2025-11-21-communicating-architecture.md similarity index 98% rename from _posts/2025-11-20-communicating-architecture.md rename to _posts/2025-11-21-communicating-architecture.md index 85cb9482c6..6a72dae90c 100644 --- a/_posts/2025-11-20-communicating-architecture.md +++ b/_posts/2025-11-21-communicating-architecture.md @@ -1,11 +1,10 @@ --- title: How Do We Effectively Communicate Architecture? -date: 2025-11-20 00:00:00 Z +date: 2025-11-21 00:00:00 Z categories: -- Architecture - Tech author: sbreingan -summary: One of the key responsibilities of a software architect is communicating effectively. This post explores the approaches and tools that can help. +summary: One of the key responsibilities of a software architect is communicating effectively—more often than not, that means using visuals rather than relying on text. This post explores approaches and tools for modelling architecture and creating diagrams. --- One of the key responsibilities of a software architect is communicating architecture effectively. Architecture never exists in a vacuum — it exists to align people, guide decisions, and help teams move toward the same goals. Whether you're sketching a new system or explaining how existing components fit together, effective communication means helping others understand the structure, purpose, and implications of the architecture.