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# SDD + GitOps Documentation Framework
## Overview
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.
This framework ensures that every piece of documentation serves a specific purpose, reaches the right audience, and is measurable through clear KPIs and SLOs.
This document defines the documentation framework for the NATSBridge project. It establishes a structured approach to creating, maintaining, and evolving technical documentation in alignment with GitOps principles—ensuring that documentation is versioned, auditable, and continuously validated alongside the codebase.
---
## The Documentation Matrix
## The SDD Framework: Seven Pillars of Documentation
| Document | Purpose & Rationale (The "Why") | Audience | Format / Content | Measurement (KPI/SLO) | Example (SaaS Context) |
|----------|---------------------------------|----------|------------------|----------------------|------------------------|
| **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." |
| **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. |
| **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). |
| **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. |
| **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. |
| **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. |
| **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." |
| **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. |
| Document | Purpose (Rationale) | Primary Audience | Format / Content | Example (SaaS Context) | Measurement (KPI) |
|----------|---------------------|-----------------|------------------|------------------------|-------------------|
| **Requirements** | Capture the **business intent** — why we're building this and what success looks like. Defines boundaries and user-visible outcomes. | Stakeholders, Product Owners, Lead Developers | User stories, PRDs, acceptance criteria, non-functional constraints. | "System must process tabular data from Julia to SvelteKit UI with <200ms latency for 5-member teams." | 95% of requests complete <200ms (synthetic monitoring). |
| **Specification** | The **technical contract** — precise rules for inputs, outputs, and data shape. Ensures consistency across dev and test. | Developers, QA Engineers, CI/CD pipelines | OpenAPI, Protobuf, AsyncAPI. Endpoint definitions, schemas, error codes. | `contract.yaml` defining a NATS subject that accepts Arrow streams with snake_case headers. | 100% of messages validated against spec (CI block rate). |
| **Architecture** | The **blueprint** — how components fit together, interact, and scale. Guides system structure and trade-offs. | Architects, Senior Developers, DevOps | C4 diagrams, Mermaid.js, component/network/storage models. | Diagram showing 6-node cluster routing traffic via Caddy → Node.js API → Julia pods. | 100% of major decisions logged with trade-off analysis. |
| **Walkthrough** | The **story of flow** — shows how pieces connect end-to-end and why steps are sequenced. Builds intuition for new devs. | New Developers, Team Members | TOUR.md, Loom videos, sequence diagrams. Step-by-step traces with rationale. | "UI sends JSON → Node.js wraps Claim-Check → Julia pulls Arrow data (prevents NATS overflow)." | New developers ship feature in <2 days (PR timeline). |
| **Implementation** | The **real code** — business logic, helpers, tests, configs. Where design becomes executable. | Developers, Code Reviewers | Source code, README.md, unit tests, setup scripts. | Julia function for matrix calculation + SvelteKit component rendering table. | >80% unit test coverage, <5% drift from spec. |
| **Validation** | The **enforcer** — ensures implementation matches the spec. Blocks drift and human error. | Automation servers, QA, Lead Developers | CI jobs, contract tests, linting, integration checks. | CI job rejects PR with camelCase field not allowed by YAML spec. | <1% of PRs bypass validation gates. |
| **Runbook** | The **operational manual** — how the system lives in production, scales, and recovers. Guides on-call engineers. | DevOps, SREs, On-call Developers | K8s manifests, Helm charts, Markdown guides. Deployment, scaling, backup/restore, troubleshooting. | GitOps manifest ensuring 6 Julia replicas restart if memory >80%. | MTTR <15 minutes for P1 incidents. |
---
## Detailed Breakdown of Each Document Type
## Detailed Document Descriptions
### 1. Requirements
**Purpose**: Establish the Business North Star
**Purpose**: Capture the *business intent* — why we're building this and what success looks like. Defines boundaries and user-visible outcomes.
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?"
**Why It Matters**:
- Aligns engineering efforts with business goals
- Provides a north star for feature development
- Establishes acceptance criteria before implementation begins
- Creates a contract between product and engineering
**Key Characteristics**:
- **Business-Focused**: Written in business terms, not technical jargon
- **Boundary-Setting**: Explicitly defines what we will NOT build
- **Outcome-Oriented**: Focuses on user outcomes, not features
**Content Guidelines**:
- User stories with clear acceptance criteria (As a X, I want Y so that Z)
- Product Requirements Documents (PRDs) with success metrics
- Non-functional requirements (performance, security, scalability)
- Boundary definitions (what's in scope vs. out of scope)
**Best Practices**:
- Include user stories that describe the user's perspective
- Document business constraints (regulatory, legal, compliance)
- Define competitive context and market positioning
- Establish clear success metrics from day one
**Common Pitfalls to Avoid**:
- Vague descriptions like "improve user experience"
- Changing requirements without updating the document
- Not defining what's out of scope
- Link each requirement to a measurable KPI
- Keep requirements testable and verifiable
- Maintain backward compatibility with existing requirements
- Review and update requirements as business context changes
---
### 2. Spec (Specification)
### 2. Specification
**Purpose**: Create the Technical Contract
**Purpose**: The *technical contract* — precise rules for inputs, outputs, and data shape. Ensures consistency across dev and test.
The Spec serves as the Single Source of Truth for all data interfaces. It's a machine-readable definition that ensures consistency across services.
**Why It Matters**:
- Prevents implementation drift between components
- Enables contract testing in CI/CD pipelines
- Provides a single source of truth for data structures
- Facilitates integration between teams
**Key Characteristics**:
- **Machine-Readable**: Can be parsed by tools for validation and code generation
- **Strictly Typed**: Enforces data types and validation rules
- **Comprehensive**: Covers all endpoints, request/response formats, and error codes
**Content Guidelines**:
- API endpoint definitions (methods, paths, parameters)
- Request/response schemas (JSON, XML, Protobuf, AsyncAPI)
- Error codes and their meanings
- Data validation rules and constraints
- Rate limiting and quota definitions
**Best Practices**:
- Use OpenAPI/Swagger for REST APIs or Protobuf for gRPC
- Enforce consistent naming conventions (e.g., snake_case)
- Define validation rules for all data fields
- Document all possible error responses
**Common Pitfalls to Avoid**:
- Letting the spec diverge from the implementation
- Incomplete error handling documentation
- Not versioning the API spec
- Use formal specification languages (OpenAPI 3.0+, AsyncAPI)
- Version specifications alongside code
- Generate client SDKs from specifications
- Block CI on specification violations
- Document edge cases and error scenarios
---
### 3. Architecture
**Purpose**: Visualize the System Structure
**Purpose**: The *blueprint* — how components fit together, interact, and scale. Guides system structure and trade-offs.
The Architecture document provides a visual map of how components fit together. It helps identify bottlenecks and understand data flow.
**Why It Matters**:
- Provides a mental model for system design
- Guides technical decision-making and trade-off analysis
- Facilitates onboarding of new architects and senior developers
- Documents scaling and performance considerations
**Key Characteristics**:
- **Visual**: Uses diagrams to represent complex relationships
- **Comprehensive**: Covers system context, data flow, and infrastructure
- **Living Document**: Updated as the system evolves
**Content Guidelines**:
- C4 diagrams (Context, Container, Component levels)
- Mermaid.js flowcharts for sequence diagrams
- Component interaction diagrams
- Network topology and data flow
- Storage and caching strategies
- Scaling and resilience patterns
**Best Practices**:
- Use Mermaid.js for diagrams-as-code (versionable in Git)
- Include multiple views: System Context, C4 model, ERDs, network topology
- Document trade-offs and architectural decisions
- Show data flow through the system
**Common Pitfalls to Avoid**:
- Over-engineering diagrams with unnecessary detail
- Not updating diagrams when the architecture changes
- Using static images instead of diagrams-as-code
- Use diagrams that are easy to update (Mermaid.js over static images)
- Document trade-off decisions with Rationale Documents
- Include scaling considerations for each component
- Document failure modes and recovery strategies
- Keep architecture diagrams versioned with code
---
### 4. Walkthrough
**Purpose**: Build Mental Models
**Purpose**: The *story of flow* — shows how pieces connect end-to-end and why steps are sequenced. Builds intuition for new devs.
The Walkthrough document explains the "why" behind the "how." It helps developers understand the rationale behind design decisions.
**Why It Matters**:
- Reduces onboarding time for new developers
- Provides context that code comments alone cannot convey
- Explains the "why" behind architectural decisions
- Helps identify gaps in the system design
**Key Characteristics**:
- **Narrative-Driven**: Tells a story about how the system works
- **Context-Rich**: Explains trade-offs and decisions
- **End-to-End**: Traces flows from user input to system output
**Content Guidelines**:
- Step-by-step flow descriptions with rationale
- Sequence diagrams showing request/response patterns
- "Tour of the codebase" guides
- Video walkthroughs (Loom, internal recordings)
- Debugging and tracing examples
**Best Practices**:
- Document step-by-step traces of core features
- Explain architectural trade-offs and why you chose them
- Include "The Big Picture" context
- Use real examples and data flows
**Common Pitfalls to Avoid**:
- Only documenting the happy path
- Assuming developers will figure out the "why"
- Not explaining the rationale behind decisions
- Walk through real user journeys, not just technical flows
- Include "what could go wrong" scenarios
- Link walkthroughs to relevant code locations
- Keep walkthroughs updated with architecture changes
- Make walkthroughs interactive where possible
---
### 5. Implementation
**Purpose**: The Functional Reality
**Purpose**: The *real code* — business logic, helpers, tests, configs. Where design becomes executable.
The Implementation is the actual code that does the work. In SDD, the "boring" parts are auto-generated from the Spec to ensure consistency.
**Why It Matters**:
- This is the actual artifact that runs in production
- Code is the ultimate source of truth (when it matches spec)
- Tests validate correctness and prevent regressions
- Configuration files define runtime behavior
**Key Characteristics**:
- **Machine-Generated**: Types and routes auto-generated from Spec
- **Human-Written**: Business logic and helper functions
- **Tested**: Includes unit and integration tests
**Content Guidelines**:
- Business logic implementation
- Helper functions and utilities
- Unit and integration tests
- Configuration files (YAML, JSON, environment)
- Setup and development scripts
- Code organization and module structure
**Best Practices**:
- Auto-generate boring parts (types, routes) from the Spec
- Keep business logic separate from boilerplate
- Maintain comprehensive test coverage
- Document the local development setup
**Common Pitfalls to Avoid**:
- Hand-writing types that should be auto-generated
- Inconsistent code style
- Insufficient test coverage
- Follow consistent code style and conventions
- Write tests before or alongside implementation (TDD/BDD)
- Document complex logic with inline comments
- Keep configuration externalized and versioned
- Use type annotations where applicable
---
### 6. Validation
**Purpose**: Enforce the Contract
**Purpose**: The *enforcer* — ensures implementation matches the spec. Blocks drift and human error.
The Validation layer provides automated gates that ensure the Implementation matches the Spec. It prevents human error from reaching production.
**Why It Matters**:
- Prevents breaking changes from reaching production
- Catches specification violations early in the CI pipeline
- Maintains data integrity and API consistency
- Reduces manual QA effort through automation
**Key Characteristics**:
- **Automated**: Runs on every commit/Pull Request
- **Comprehensive**: Covers contract tests, integration tests, and security scans
- **Blocking**: Prevents merges that violate the contract
**Content Guidelines**:
- CI/CD pipeline configurations
- Contract testing scripts
- Linting rules and configurations
- Integration test suites
- Schema validation jobs
- Security scanning and audit jobs
**Best Practices**:
- Use contract testing tools (Dredd, Prism) to validate API contracts
- Run integration tests on every commit
- Include security scans in the CI pipeline
- Fail builds on contract violations
**Common Pitfalls to Avoid**:
- Not running tests on every commit
- Allowing manual overrides of validation gates
- Not updating tests when the Spec changes
- Fail CI on specification violations
- Run validation jobs on every commit and PR
- Use automated code review tools
- Maintain validation job health dashboard
- Document validation failure remediation steps
---
### 7. Maintenance
### 7. Runbook
**Purpose**: Ensure Long-Term Health
**Purpose**: The *operational manual* — how the system lives in production, scales, and recovers. Guides on-call engineers.
The Maintenance document defines how to upgrade dependencies, manage technical debt, and rotate secrets. It's the guide for "future-proofing" the software.
**Why It Matters**:
- Reduces Mean Time To Recovery (MTTR) for incidents
- Provides step-by-step guidance for common issues
- Documents scaling and deployment procedures
- Ensures operational knowledge is not siloed
**Key Characteristics**:
- **Procedural**: Step-by-step instructions for common tasks
- **Scheduled**: Includes regular maintenance windows
- **Documented**: Tracks technical debt and migration history
**Content Guidelines**:
- Deployment procedures (manual and automated)
- Scaling instructions (horizontal/vertical)
- Backup and restore procedures
- Troubleshooting guides for common issues
- Runbook entries for specific error codes
- Contact information and escalation paths
**Best Practices**:
- Document dependency update schedules
- Create secret rotation procedures
- Track technical debt in a "Graveyard"
- Document migration history and rollback procedures
**Common Pitfalls to Avoid**:
- Ad-hoc upgrades without documentation
- Ignoring technical debt until it becomes critical
- Not testing upgrades in staging first
---
### 8. Runbook
**Purpose**: Operational Life-Support
The Runbook provides instructions for when the system is alive (or dying). In GitOps, this is the "Desired State" of the infrastructure.
**Key Characteristics**:
- **Action-Oriented**: Step-by-step instructions for common operations
- **Automated**: Infrastructure as code defines the desired state
- **Crisis-Ready**: Includes "3:00 AM" troubleshooting guides
**Best Practices**:
- Document deployment procedures
- Define scaling triggers and procedures
- Include backup and restore procedures
- Create troubleshooting guides for common issues
**Common Pitfalls to Avoid**:
- Not documenting procedures for common issues
- Not testing runbook procedures
- Not versioning runbooks with the infrastructure
- Write runbooks for every P1/P2 incident
- Include exact commands and configuration snippets
- Test runbooks periodically (chaos engineering)
- Link runbook entries to relevant documentation
- Keep runbooks updated when system changes
---
## How to Use This Approach Effectively
### Phase 1: Foundation (Week 1-2)
### 1. Start with Requirements
1. **Create Requirements Document**
- Define the Business North Star
- Establish success metrics
- Define out-of-scope items
Before writing any code or documentation, establish clear requirements. Ask:
- What business problem are we solving?
- How will we measure success?
- What are the non-negotiable constraints?
2. **Write the Spec**
- Define all data interfaces
- Establish naming conventions
- Document validation rules
**Action**: Create a `docs/requirements/` directory and start with `PRD.md` and `KPIs.md`.
3. **Design Architecture**
- Create system diagrams
- Document data flow
- Identify potential bottlenecks
### 2. Define the Specification First
### Phase 2: Development (Week 3+)
Once requirements are stable, define the technical specification. This becomes the contract for implementation.
4. **Write Walkthrough**
- Document end-to-end flows
- Explain architectural trade-offs
- Create mental models for developers
**Action**: Create `docs/specification/` with `contract.yaml` (or appropriate format) and `error-codes.md`.
5. **Implement Code**
- Auto-generate boring parts from Spec
- Write business logic
- Implement tests
### 3. Design the Architecture
### Phase 3: Quality Assurance
With requirements and specification in place, design the architecture. Document trade-off decisions explicitly.
6. **Set Up Validation**
- Configure CI/CD pipeline
- Set up contract testing
- Configure security scans
**Action**: Create `docs/architecture/` with Mermaid diagrams and `trade-offs.md`.
7. **Create Runbook**
- Document deployment procedures
- Define scaling triggers
- Create troubleshooting guides
### 4. Create Walkthroughs Early
### Phase 4: Maintenance
As soon as the architecture is defined, create walkthroughs. This helps identify gaps and provides onboarding material.
8. **Document Maintenance**
- Create dependency update schedule
- Document secret rotation
- Track technical debt
**Action**: Create `docs/walkthrough/` with `TOUR.md` and sequence diagrams.
### 5. Implement with Validation in Mind
Write implementation code that adheres to the specification. Build validation into the CI pipeline from day one.
**Action**: Ensure test files are co-located with implementation and run on every commit.
### 6. Automate Validation
Build automated validation that runs in CI/CD. This ensures spec compliance and prevents drift.
**Action**: Configure CI jobs to validate against specification and block PRs on violations.
### 7. Document Operations from Day One
Create runbook entries as soon as deployment procedures are established. Update them when incidents occur.
**Action**: Create `docs/runbook/` with entries for deployment, scaling, and common issues.
---
## Key Principles for Success
## GitOps Integration
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
This documentation framework aligns with GitOps principles:
| GitOps Principle | Documentation Alignment |
|-----------------|------------------------|
| **Versioned** | All documentation lives in git, with history and audit trail |
| ** declarative** | Specifications and architecture are declarative contracts |
| **Automated** | Validation jobs automate spec compliance checks |
| **Self-Service** | Walkthroughs and runbooks enable self-service onboarding and operations |
| **Observability** | KPIs and metrics are defined for each documentation artifact |
**Git Structure**:
```
docs/
├── requirements/ # PRDs, user stories, KPIs
├── specification/ # OpenAPI, Protobuf, AsyncAPI specs
├── architecture/ # C4 diagrams, Mermaid, trade-off docs
├── walkthrough/ # TOUR.md, sequence diagrams
├── implementation/ # Source code (in src/)
├── validation/ # CI configs, test suites
└── runbook/ # Deployment, scaling, troubleshooting
```
---
## Metrics and Continuous Improvement
Each documentation artifact has associated KPIs. Track these to ensure quality:
| Document | KPI | Target |
|----------|-----|--------|
| Requirements | Requirement coverage | 100% of features have associated requirements |
| Specification | Spec compliance rate | 100% of messages validate against spec |
| Architecture | Decision documentation | 100% of major decisions logged with trade-offs |
| Walkthrough | New dev time-to-first-PR | <2 days from onboarding to first contribution |
| Implementation | Test coverage | >80% unit test coverage |
| Validation | Bypass rate | <1% of PRs bypass validation gates |
| Runbook | MTTR | <15 minutes for P1 incidents |
**Review Cadence**:
- Weekly: Review KPI dashboards and documentation gaps
- Monthly: Update documentation based on incident learnings
- Quarterly: Full framework review and improvement
---
## Template Examples
### Requirements Template
```markdown
# PRD: Feature Name
## Business Goal
[What problem are we solving?]
## Success Metrics
- [Metric 1]: Target [value]
- [Metric 2]: Target [value]
## User Stories
- As a [role], I want [feature] so that [benefit]
- Acceptance Criteria: [details]
## Non-Functional Requirements
- Performance: [details]
- Security: [details]
- Scalability: [details]
## Out of Scope
- [What's explicitly excluded]
```
### Specification Template
```yaml
# contract.yaml
openapi: 3.0.0
info:
title: NATSBridge API
version: 1.0.0
paths:
/api/v1/endpoint:
post:
requestBody:
content:
application/json:
schema:
$ref: '#/components/schemas/Request'
responses:
'200':
description: Success
content:
application/json:
schema:
$ref: '#/components/schemas/Response'
```
### Architecture Template
```mermaid
%%{init: {'theme': 'base', 'themeVariables': {'primaryColor': '#3b82f6'}}}%%
flowchart TD
A[Client] --> B[Caddy]
B --> C[Node.js API]
C --> D[Julia Worker]
D --> E[NATS Cluster]
E --> F[Storage]
style A fill:#f9f9f9,stroke:#333
style E fill:#e0e7ff,stroke:#3b82f6
```
### Runbook Template
```markdown
# Runbook: Service Restart
**Severity**: P2
**Estimated Time**: 5 minutes
## Symptoms
- Service is unresponsive
- Health checks are failing
## Steps
1. SSH to the host
2. Run: `kubectl rollout restart deployment/natsbridge`
3. Monitor: `kubectl get pods -l app=natsbridge -w`
## Rollback
- Run: `kubectl rollout undo deployment/natsbridge`
## Post-Incident
- [ ] Review logs for root cause
- [ ] Update runbook if needed
```
---
## Conclusion
The SDD + GitOps Documentation Framework provides a comprehensive, structured approach to software development documentation. By following this framework, teams can ensure that:
This SDD + GitOps Documentation Framework ensures that documentation is:
- **Structured**: Seven distinct artifacts with clear purposes
- **Automated**: Validation and CI/CD integration
- **Versioned**: All documentation in git with history
- **Measurable**: KPIs for quality and effectiveness
- **Actionable**: Practical templates and examples
- 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.
Use this framework as a living document—update it as your team's needs evolve.