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## Overview
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The **SDD + GitOps Documentation Framework** is a comprehensive, structured approach to software development documentation that aligns technical work with business outcomes through clear separation of concerns.
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The **SDD (Software Design Documentation) + GitOps Documentation Framework** is a comprehensive, structured approach to software development documentation that aligns technical work with business outcomes through clear separation of concerns.
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This framework ensures that every piece of documentation serves a specific purpose, reaches the right audience, and can be measured for effectiveness. It's designed to prevent common pitfalls like feature creep, communication gaps, and operational fragility.
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This framework ensures that every piece of documentation serves a specific purpose, reaches the right audience, and is measurable through clear KPIs and SLOs.
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---
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## The Documentation Matrix
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| Document | Purpose & Rationale (The "Why") | Audience | Format / Content | Measurement (KPI/SLO) | Example (SaaS Context) |
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|----------|----------------------------------|----------|------------------|----------------------|------------------------|
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| **Requirements** | The Business North Star. Defines exactly what problem the user has and what success looks like. It prevents "feature creep" by setting hard boundaries on what we will NOT build. | Founder, Team, PM | Format: Shared Wiki (Notion/GitHub Wiki). Content: User stories, business constraints, competitive context, and success metrics. | **KPI**: Business Outcomes. Measured by User Retention, Conversion Rates, and Monthly Recurring Revenue (MRR). | "The system must process high-volume math so clients see reports instantly. Goal: 15% increase in daily active users." |
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| **Spec** | The Technical Contract. A machine-readable, strictly typed definition of all data interfaces. It is the "Single Source of Truth" that prevents bugs caused by communication gaps between services. | Developers, QA, Automation | Format: OpenAPI/YAML or Protobuf. Content: API endpoints, snake_case key naming, data validation rules, and error response codes. | **SLA/SLO**: System Performance. Measured by API Uptime (99.9%), Response Latency (<100ms), and Error Rates. | A `contract.yaml` defining exactly how Julia sends Arrow data to Node.js. It forces `user_id` to be a UUID. |
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| **Architecture** | The Structural Blueprint. A visual map of how the components (services, DBs, networks) fit together. It shows how the data flows through the 6-node cluster and where bottlenecks live. | Senior Devs, DevOps | Format: Diagrams-as-code (Mermaid.js). Content: System Context diagrams, Database ERDs, Network Security Policies, and Infrastructure maps. | **Efficiency Metrics**: Resource utilization. Measured by CPU Load (<70%), RAM per pod, and internal network throughput. | A diagram showing the data path: Caddy (Proxy) → Node.js (API) → NATS (Queue) → Julia (Math Engine). |
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| **Walkthrough** | The Intuition & Logic. A narrative guide that explains the "steps" and "rationale" behind end-to-end flows. It's about building a mental model so devs understand why the sequence matters. | The Team, New Hires | Format: TOUR.md file or Loom Video. Content: Step-by-step traces of core features, explanation of architectural trade-offs, and "The Big Picture" flow. | **Quality**: Developer Velocity. Measured by "Time-to-First-Commit" for new hires and reduction in conceptual bugs. | "End-to-End Trace": 1. UI sends JSON. 2. API wraps it in Claim-Check. 3. Julia pulls it. Rationale: To avoid NATS memory spikes. |
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| **Implementation** | The Functional Reality. The actual code that does the work. In SDD, the "boring" parts (types/routes) are auto-generated from the Spec to ensure the code never lies. | Developers, Reviewers | Format: Git Repository. Content: Business logic, internal helper functions, Unit Tests, and a README.md for local environment setup. | **Code Health**: Internal Quality. Measured by Test Coverage (90%+), Linting compliance, and Cyclomatic Complexity. | The SvelteKit frontend components and the specific Julia math-processing functions. |
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| **Validation** | The Enforcement Layer. Automated gates that prove the Implementation matches the Spec. It prevents human error (like changing a key name) from reaching production. | CI/CD Pipeline, QA | Format: GitHub Actions / Tests. Content: Contract tests (Dredd/Prism), Integration tests, and Security scans that run on every pull request. | **Compliance**: Safety Metrics. Measured by Build Success Rate and 0 "Contract Violations" in the production logs. | A CI job that blocks a Pull Request because a developer used camelCase in a database field instead of snake_case. |
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| **Maintenance** | The Health & Evolution. Defines how to upgrade dependencies, manage technical debt, and rotate secrets. It's the guide for "future-proofing" the software over time. | The Team, DevOps | Format: MAINTENANCE.md. Content: Dependency update schedules, Secret rotation steps, DB Migration logs, and Tech Debt "Graveyard" tracking. | **Sustainability**: System Longevity. Measured by "Package Age", "Security Vulnerabilities Found", and "Migration Success Rate". | "Steps to upgrade the Julia version across all 6 nodes without downtime using a Blue-Green deployment strategy." |
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| **Runbook** | The Operational Life-Support. The instructions for when the system is alive (or dying). In GitOps, this is the "Desired State" of the infrastructure. | DevOps, SRE, On-call Devs | Format: K8s Manifests (Flux/Argo). Content: Deployment steps, Scaling triggers, Backup/Restore procedures, and "3:00 AM" troubleshooting guides. | **Reliability**: Operational Health. Measured by MTTR (Mean Time to Recovery) and Error-Free Deployments. | A Flux manifest that ensures 6 replicas of the Julia service are always healthy and restarts them if they hit 80% RAM. |
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|----------|---------------------------------|----------|------------------|----------------------|------------------------|
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| **Requirements** | The Business North Star. Defines exactly what problem the user has and what success looks like. It prevents "feature creep" by setting hard boundaries on what we will NOT build. | Founder, Team, PM | Format: Shared Wiki (Notion/GitHub Wiki). Content: User stories, business constraints, competitive context, and success metrics. | KPI: Business Outcomes. Measured by User Retention, Conversion Rates, and Monthly Recurring Revenue (MRR). | "The system must process high-volume math so clients see reports instantly. Goal: 15% increase in daily active users." |
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| **Spec** | The Technical Contract. A machine-readable, strictly typed definition of all data interfaces. It is the "Single Source of Truth" that prevents bugs caused by communication gaps between services. | Developers, QA, Automation | Format: OpenAPI/YAML or Protobuf. Content: API endpoints, snake_case key naming, data validation rules, and error response codes. | SLA/SLO: System Performance. Measured by API Uptime (99.9%), Response Latency (<100ms), and Error Rates. | A `contract.yaml` defining exactly how Julia sends Arrow data to Node.js. It forces `user_id` to be a UUID. |
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| **Architecture** | The Structural Blueprint. A visual map of how the components (services, DBs, networks) fit together. It shows how the data flows through the 6-node cluster and where bottlenecks live. | Senior Devs, DevOps | Format: Diagrams-as-code (Mermaid.js). Content: System Context diagrams, Database ERDs, Network Security Policies, and Infrastructure maps. | Efficiency Metrics: Resource utilization. Measured by CPU Load (<70%), RAM per pod, and internal network throughput. | A diagram showing the data path: Caddy (Proxy) → Node.js (API) → NATS (Queue) → Julia (Math Engine). |
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| **Walkthrough** | The Intuition & Logic. A narrative guide that explains the "steps" and "rationale" behind end-to-end flows. It's about building a mental model so devs understand why the sequence matters. | The Team, New Hires | Format: TOUR.md file or Loom Video. Content: Step-by-step traces of core features, explanation of architectural trade-offs, and "The Big Picture" flow. | Quality: Developer Velocity. Measured by "Time-to-First-Commit" for new hires and reduction in conceptual bugs. | "End-to-End Trace:" 1. UI sends JSON. 2. API wraps it in Claim-Check. 3. Julia pulls it. Rationale: To avoid NATS memory spikes. |
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| **Implementation** | The Functional Reality. The actual code that does the work. In SDD, the "boring" parts (types/routes) are auto-generated from the Spec to ensure the code never lies. | Developers, Reviewers | Format: Git Repository. Content: Business logic, internal helper functions, Unit Tests, and a README.md for local environment setup. | Code Health: Internal Quality. Measured by Test Coverage (90%+), Linting compliance, and Cyclomatic Complexity. | The SvelteKit frontend components and the specific Julia math-processing functions. |
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| **Validation** | The Enforcement Layer. Automated gates that prove the Implementation matches the Spec. It prevents human error (like changing a key name) from reaching production. | CI/CD Pipeline, QA | Format: GitHub Actions / Tests. Content: Contract tests (Dredd/Prism), Integration tests, and Security scans that run on every pull request. | Compliance: Safety Metrics. Measured by Build Success Rate and 0 "Contract Violations" in the production logs. | A CI job that blocks a Pull Request because a developer used camelCase in a database field instead of snake_case. |
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| **Maintenance** | The Health & Evolution. Defines how to upgrade dependencies, manage technical debt, and rotate secrets. It's the guide for "future-proofing" the software over time. | The Team, DevOps | Format: MAINTENANCE.md. Content: Dependency update schedules, Secret rotation steps, DB Migration logs, and Tech Debt "Graveyard" tracking. | Sustainability: System Longevity. Measured by "Package Age," "Security Vulnerabilities Found," and "Migration Success Rate." | "Steps to upgrade the Julia version across all 6 nodes without downtime using a Blue-Green deployment strategy." |
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| **Runbook** | The Operational Life-Support. The instructions for when the system is alive (or dying). In GitOps, this is the "Desired State" of the infrastructure. | DevOps, SRE, On-call Devs | Format: K8s Manifests (Flux/Argo). Content: Deployment steps, Scaling triggers, Backup/Restore procedures, and "3:00 AM" troubleshooting guides. | Reliability: Operational Health. Measured by MTTR (Mean Time to Recovery) and Error-Free Deployments. | A Flux manifest that ensures 6 replicas of the Julia service are always healthy and restarts them if they hit 80% RAM. |
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---
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## Detailed Document Descriptions
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## Detailed Breakdown of Each Document Type
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### 1. Requirements
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**Purpose**: Establish the Business North Star.
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**Purpose**: Establish the Business North Star
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**Why It Matters**: Without clear requirements, teams drift into "feature creep" - building things that don't solve the actual problem. This document anchors the project in business outcomes.
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The Requirements document is your anchor point. It answers the fundamental question: "What problem are we solving, and how do we know we've succeeded?"
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**Key Elements**:
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- **User Stories**: What the user needs to accomplish
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- **Business Constraints**: Budget, timeline, regulatory requirements
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- **Competitive Context**: What competitors do and how you differentiate
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- **Success Metrics**: Quantifiable goals that define "done"
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**Key Characteristics**:
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- **Business-Focused**: Written in business terms, not technical jargon
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- **Boundary-Setting**: Explicitly defines what we will NOT build
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- **Outcome-Oriented**: Focuses on user outcomes, not features
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**Best Practices**:
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- Keep it in a shared wiki (Notion, GitHub Wiki) for collaborative editing
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- Focus on outcomes, not solutions
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- Explicitly state what you will NOT build
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- Include user stories that describe the user's perspective
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- Document business constraints (regulatory, legal, compliance)
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- Define competitive context and market positioning
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- Establish clear success metrics from day one
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**Common Pitfalls to Avoid**:
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- Vague descriptions like "improve user experience"
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- Changing requirements without updating the document
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- Not defining what's out of scope
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---
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### 2. Spec (Specification)
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**Purpose**: Create a machine-readable technical contract.
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**Purpose**: Create the Technical Contract
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**Why It Matters**: Communication gaps between services cause bugs. A strict, typed spec prevents these by being the Single Source of Truth.
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The Spec serves as the Single Source of Truth for all data interfaces. It's a machine-readable definition that ensures consistency across services.
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**Key Elements**:
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- **API Endpoints**: All routes with HTTP methods
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- **Data Types**: Strict typing with validation rules
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- **Error Codes**: Comprehensive error response definitions
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- **Naming Conventions**: snake_case keys, consistent patterns
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**Key Characteristics**:
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- **Machine-Readable**: Can be parsed by tools for validation and code generation
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- **Strictly Typed**: Enforces data types and validation rules
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- **Comprehensive**: Covers all endpoints, request/response formats, and error codes
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**Best Practices**:
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- Use OpenAPI (YAML/JSON) for REST APIs or Protobuf for gRPC
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- Automate generation of client/server code from the spec
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- Run contract tests against the spec in CI/CD
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- Use OpenAPI/Swagger for REST APIs or Protobuf for gRPC
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- Enforce consistent naming conventions (e.g., snake_case)
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- Define validation rules for all data fields
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- Document all possible error responses
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**Common Pitfalls to Avoid**:
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- Letting the spec diverge from the implementation
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- Incomplete error handling documentation
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- Not versioning the API spec
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---
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### 3. Architecture
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**Purpose**: Visualize the system structure and data flow.
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**Purpose**: Visualize the System Structure
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**Why It Matters**: Complex systems (like your 6-node cluster) need clear maps. Without them, teams can't identify bottlenecks or make informed decisions.
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The Architecture document provides a visual map of how components fit together. It helps identify bottlenecks and understand data flow.
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**Key Elements**:
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- **System Context Diagram**: Shows the system and its external dependencies
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- **Database ERD**: Entity-Relationship diagrams for data model
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- **Network Security Policies**: Firewall rules, service mesh configs
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- **Infrastructure Maps**: Cloud resources, scaling groups
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**Key Characteristics**:
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- **Visual**: Uses diagrams to represent complex relationships
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- **Comprehensive**: Covers system context, data flow, and infrastructure
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- **Living Document**: Updated as the system evolves
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**Best Practices**:
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- Use Mermaid.js for diagrams-as-code (versionable, diffable)
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- Update diagrams when architecture changes
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- Focus on data flow and decision points
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- Use Mermaid.js for diagrams-as-code (versionable in Git)
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- Include multiple views: System Context, C4 model, ERDs, network topology
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- Document trade-offs and architectural decisions
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- Show data flow through the system
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**Common Pitfalls to Avoid**:
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- Over-engineering diagrams with unnecessary detail
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- Not updating diagrams when the architecture changes
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- Using static images instead of diagrams-as-code
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---
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### 4. Walkthrough
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**Purpose**: Build a mental model through narrative.
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**Purpose**: Build Mental Models
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**Why It Matters**: Code doesn't explain *why*. Walkthroughs capture the reasoning behind architectural trade-offs, making onboarding faster and reducing conceptual bugs.
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The Walkthrough document explains the "why" behind the "how." It helps developers understand the rationale behind design decisions.
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**Key Elements**:
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- **Step-by-step traces**: End-to-end flow of user actions
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- **Trade-off explanations**: Why you chose option A over B
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- **The Big Picture**: How components fit together conceptually
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**Key Characteristics**:
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- **Narrative-Driven**: Tells a story about how the system works
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- **Context-Rich**: Explains trade-offs and decisions
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- **End-to-End**: Traces flows from user input to system output
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**Best Practices**:
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- Write in a TOUR.md file or record Loom videos
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- Focus on intuition, not just mechanics
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- Include "Rationale" sections for each major decision
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- Document step-by-step traces of core features
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- Explain architectural trade-offs and why you chose them
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- Include "The Big Picture" context
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- Use real examples and data flows
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**Common Pitfalls to Avoid**:
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- Only documenting the happy path
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- Assuming developers will figure out the "why"
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- Not explaining the rationale behind decisions
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---
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### 5. Implementation
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**Purpose**: The functional reality - the actual code.
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**Purpose**: The Functional Reality
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**Why It Matters**: This is what runs in production. In SDD, the spec-driven approach ensures boring parts are generated automatically, so developers focus on business logic.
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The Implementation is the actual code that does the work. In SDD, the "boring" parts are auto-generated from the Spec to ensure consistency.
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**Key Elements**:
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- **Business Logic**: The unique value you provide
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- **Unit Tests**: Covering edge cases and error paths
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- **README.md**: Local environment setup instructions
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**Key Characteristics**:
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- **Machine-Generated**: Types and routes auto-generated from Spec
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- **Human-Written**: Business logic and helper functions
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- **Tested**: Includes unit and integration tests
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**Best Practices**:
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- Generate boilerplate (types, routes) from the Spec
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- Maintain 90%+ test coverage
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- Keep README.md up-to-date for local development
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- Auto-generate boring parts (types, routes) from the Spec
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- Keep business logic separate from boilerplate
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- Maintain comprehensive test coverage
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- Document the local development setup
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**Common Pitfalls to Avoid**:
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- Hand-writing types that should be auto-generated
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- Inconsistent code style
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- Insufficient test coverage
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---
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### 6. Validation
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**Purpose**: Automated quality gates.
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**Purpose**: Enforce the Contract
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**Why It Matters**: Human error happens. Validation layers catch mistakes before they reach production, preventing contract violations and security issues.
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The Validation layer provides automated gates that ensure the Implementation matches the Spec. It prevents human error from reaching production.
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**Key Elements**:
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- **Contract Tests**: Verify implementation matches spec (Dredd, Prism)
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- **Integration Tests**: Test service-to-service interactions
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- **Security Scans**: SAST/SBOM analysis on every PR
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**Key Characteristics**:
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- **Automated**: Runs on every commit/Pull Request
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- **Comprehensive**: Covers contract tests, integration tests, and security scans
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- **Blocking**: Prevents merges that violate the contract
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**Best Practices**:
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- Run validation on every pull request
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- Block merges on contract violations
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- Track build success rate as a KPI
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- Use contract testing tools (Dredd, Prism) to validate API contracts
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- Run integration tests on every commit
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- Include security scans in the CI pipeline
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- Fail builds on contract violations
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**Common Pitfalls to Avoid**:
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- Not running tests on every commit
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- Allowing manual overrides of validation gates
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- Not updating tests when the Spec changes
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---
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### 7. Maintenance
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**Purpose**: Guide for long-term health and evolution.
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**Purpose**: Ensure Long-Term Health
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**Why It Matters**: Software decays. Without a maintenance plan, dependency upgrades become risky, secrets accumulate, and technical debt piles up.
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The Maintenance document defines how to upgrade dependencies, manage technical debt, and rotate secrets. It's the guide for "future-proofing" the software.
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**Key Elements**:
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- **Dependency Update Schedule**: When and how to upgrade packages
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- **Secret Rotation Steps**: How to rotate credentials securely
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- **DB Migration Logs**: History of schema changes
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- **Tech Debt "Graveyard"**: Documented technical debt with remediation plans
|
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**Key Characteristics**:
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- **Procedural**: Step-by-step instructions for common tasks
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- **Scheduled**: Includes regular maintenance windows
|
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- **Documented**: Tracks technical debt and migration history
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|
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**Best Practices**:
|
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- Document the "how" for common maintenance tasks
|
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- Track package age and security vulnerabilities
|
||||
- Schedule regular tech debt reviews
|
||||
- Document dependency update schedules
|
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- Create secret rotation procedures
|
||||
- Track technical debt in a "Graveyard"
|
||||
- Document migration history and rollback procedures
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|
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**Common Pitfalls to Avoid**:
|
||||
- Ad-hoc upgrades without documentation
|
||||
- Ignoring technical debt until it becomes critical
|
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- Not testing upgrades in staging first
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|
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---
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### 8. Runbook
|
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|
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**Purpose**: Operational life-support for production systems.
|
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**Purpose**: Operational Life-Support
|
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|
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**Why It Matters**: When production is down, teams need clear instructions. In GitOps, the runbook is the "desired state" that the system constantly works toward.
|
||||
The Runbook provides instructions for when the system is alive (or dying). In GitOps, this is the "Desired State" of the infrastructure.
|
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|
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**Key Elements**:
|
||||
- **Deployment Steps**: How to deploy new versions
|
||||
- **Scaling Triggers**: When and how to scale up/down
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||||
- **Backup/Restore Procedures**: Disaster recovery steps
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- **"3:00 AM" Troubleshooting**: Quick fixes for common failures
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**Key Characteristics**:
|
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- **Action-Oriented**: Step-by-step instructions for common operations
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- **Automated**: Infrastructure as code defines the desired state
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- **Crisis-Ready**: Includes "3:00 AM" troubleshooting guides
|
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**Best Practices**:
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- Store in K8s manifests (Flux/Argo) for GitOps
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- Automate as much as possible
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- Test runbook procedures regularly
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- Document deployment procedures
|
||||
- Define scaling triggers and procedures
|
||||
- Include backup and restore procedures
|
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- Create troubleshooting guides for common issues
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|
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**Common Pitfalls to Avoid**:
|
||||
- Not documenting procedures for common issues
|
||||
- Not testing runbook procedures
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||||
- Not versioning runbooks with the infrastructure
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---
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||||
## How to Use This Framework
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||||
## How to Use This Approach Effectively
|
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|
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1. **Start with Requirements** - Define the business problem and success criteria
|
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2. **Create the Spec** - Translate requirements into machine-readable contracts
|
||||
3. **Design Architecture** - Visualize how the system will work
|
||||
4. **Write Walkthrough** - Document the logic and trade-offs
|
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5. **Implement** - Build the actual code
|
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6. **Set up Validation** - Add automated tests and gates
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7. **Document Maintenance** - Plan for long-term health
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8. **Create Runbook** - Define operational procedures
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### Phase 1: Foundation (Week 1-2)
|
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|
||||
This framework ensures that every document serves a clear purpose and that your project remains maintainable, scalable, and aligned with business goals.
|
||||
1. **Create Requirements Document**
|
||||
- Define the Business North Star
|
||||
- Establish success metrics
|
||||
- Define out-of-scope items
|
||||
|
||||
2. **Write the Spec**
|
||||
- Define all data interfaces
|
||||
- Establish naming conventions
|
||||
- Document validation rules
|
||||
|
||||
3. **Design Architecture**
|
||||
- Create system diagrams
|
||||
- Document data flow
|
||||
- Identify potential bottlenecks
|
||||
|
||||
### Phase 2: Development (Week 3+)
|
||||
|
||||
4. **Write Walkthrough**
|
||||
- Document end-to-end flows
|
||||
- Explain architectural trade-offs
|
||||
- Create mental models for developers
|
||||
|
||||
5. **Implement Code**
|
||||
- Auto-generate boring parts from Spec
|
||||
- Write business logic
|
||||
- Implement tests
|
||||
|
||||
### Phase 3: Quality Assurance
|
||||
|
||||
6. **Set Up Validation**
|
||||
- Configure CI/CD pipeline
|
||||
- Set up contract testing
|
||||
- Configure security scans
|
||||
|
||||
7. **Create Runbook**
|
||||
- Document deployment procedures
|
||||
- Define scaling triggers
|
||||
- Create troubleshooting guides
|
||||
|
||||
### Phase 4: Maintenance
|
||||
|
||||
8. **Document Maintenance**
|
||||
- Create dependency update schedule
|
||||
- Document secret rotation
|
||||
- Track technical debt
|
||||
|
||||
---
|
||||
|
||||
## Key Principles for Success
|
||||
|
||||
1. **Separation of Concerns**: Keep business concerns separate from technical concerns
|
||||
2. **Machine-Readable Contracts**: Use OpenAPI/Protobuf for specs to enable automation
|
||||
3. **Automation**: Automate boring parts and validation to reduce human error
|
||||
4. **Measurability**: Every document should have measurable outcomes
|
||||
5. **Version Control**: Keep all documentation in Git for history and collaboration
|
||||
6. **Living Documents**: Update documentation as the system evolves
|
||||
7. **Audience-Focused**: Write for the intended audience's needs and knowledge level
|
||||
|
||||
---
|
||||
|
||||
## Conclusion
|
||||
|
||||
The SDD + GitOps Documentation Framework provides a comprehensive, structured approach to software development documentation. By following this framework, teams can ensure that:
|
||||
|
||||
- Business goals are clearly defined and measurable
|
||||
- Technical contracts are machine-readable and enforced
|
||||
- System architecture is visualized and understood
|
||||
- Developers have clear mental models of the system
|
||||
- Code quality is maintained through automation
|
||||
- Operations are reliable and repeatable
|
||||
|
||||
This framework is not just about documentation—it's about creating a shared understanding across the entire team and ensuring that every decision is aligned with business goals.
|
||||
Reference in New Issue
Block a user