Architecture and resilience

Disaster Recovery Dependency Mapping

AI-assisted dependency discovery and diagram-as-code workflows for disaster recovery planning across hundreds of components.

Professional case study

200+ components mapped

SME validation accelerated

Diagram-as-code workflow

Problem

Disaster recovery planning needed accurate service dependency maps, but manual discovery across hundreds of repositories and components would have been slow and error-prone.

Action

Used AI-assisted repository analysis, C4-style modeling, and diagram-as-code workflows to create dependency maps that subject-matter experts could validate.

Outcome

Mapped 200+ components and compressed discovery work into a shorter validation workflow, helping the DR initiative move from unknowns to actionable architecture review.

engineering takeaways

Reusable patterns from the work.

These notes focus on the engineering judgment, tradeoffs, and patterns behind the work.

  • Used automation to create an initial dependency view before expert validation.
  • Kept the model maintainable by preferring diagram-as-code over static whiteboard artifacts.
  • Connected technical dependency discovery to business continuity planning.

stack

ArchitectureC4StructurizrAI WorkflowsDisaster Recovery

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