Software architecture diagrams are essential for understanding complex systems, but traditional tools like PlantUML often trap models in rigid, non-reusable text files. Enter Overarch, an open-source framework that reimagines architectural modeling by treating systems as structured, extensible data. Built on Clojure, Overarch leverages formats like EDN (Extensible Data Notation) and JSON to create composable models that serve as a single source of truth for everything from C4 diagrams to deployment pipelines.

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Why Static Models Fall Short

Current tools conflate architectural intent with visual representation. A PlantUML file describing a banking system, for example, is merely a rendering script—not a reusable data asset. This forces teams to duplicate efforts across diagrams, documentation, and code while struggling with synchronization. As the Overarch documentation notes:

"The model should capture the essence of the architecture and not its representation."

Overarch solves this by separating the model (the architecture’s core elements and relationships) from views (visualizations like diagrams). Models become queryable datasets, enabling:
- Dynamic composition: Combine subsystems or organizational structures.
- Multi-output generation: Export PlantUML diagrams, GraphViz visualizations, documentation, or even infrastructure code from one model.
- Consistency: Changes propagate across all artifacts.

Core Capabilities in Action

Overarch supports comprehensive modeling constructs:
- C4 model diagrams (system context, containers, components)
- UML diagrams (use cases, state machines, class diagrams)
- Deployment topologies and organizational structures

Here’s a snippet modeling part of a banking system in EDN:

{:el :system
 :id :banking.internet-banking/internet-banking-system
 :name "Internet Banking System"
 :ct [{:el :container
       :id :web-app
       :tech "Clojure, Luminus"}]}

Views then transform this data into diagrams. A context view specification generates PlantUML output, rendering clean visualizations without embedding layout details in the model:

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System Context View for a banking application, auto-generated from Overarch’s data model.

The Developer Workflow Shift

For teams, Overarch introduces paradigm shifts:
1. Version-controlled architecture: Models are editable EDN/JSON files, not binary blobs.
2. Automated artifact generation: Templates produce docs, code scaffolds, or CI/CD pipelines.
3. Toolchain integration: Works with VS Code (via Calva/PlantUML plugins) and CLI workflows.

Installation is streamlined via Homebrew (brew install overarch) or Java JAR, and the watch mode auto-regenerates outputs on file changes—ideal for iterative design.

Why This Matters for Modern Engineering

In an era of microservices and cloud-native systems, Overarch addresses critical gaps:
- Traceability: Query models to audit dependencies or impacts.
- Scalability: Compose enterprise-scale architectures from domain-specific submodels.
- Knowledge retention: Onboard teams with living documentation synced to code.

As architectures grow more distributed, tools that treat design as data will become indispensable. Overarch isn’t just another diagramming utility—it’s a foundational step toward truly reusable, executable architectural knowledge.

Source: Overarch GitHub Repository