# Software Architecture Processes Backlog

This document contains researched software architecture processes that can be adapted to the Babysitter SDK orchestration framework. Each process should be implemented in its own directory under `processes/[name]/`.

## Implementation Guidelines

### Directory Structure
```
processes/
├── [process-name]/
│   ├── README.md              # Overview and usage
│   ├── [process-name].js      # Main process workflow with embedded agentic or skill based tasks, breakpoints, etc.
│   └── examples/              # Example inputs/outputs
│       ├── examples.json
│       └── ...
```

### File Patterns
- **Main Process**: `processes/[name]/[name].js` or `processes/[name].js` (for single-file)
- **JSDoc Required**: `@process`, `@description`, `@inputs`, `@outputs`
- **Export Pattern**: `export async function process(inputs, ctx) { ... }`
- **Task Definitions**: Use `defineTask` from `@a5c-ai/babysitter-sdk`
- **Breakpoints**: Use `ctx.breakpoint()` for human approval gates
- **Parallel Execution**: Use `ctx.parallel.all()` for independent tasks

---

## Priority Matrix

### 🔥 High Priority (Implement First)
**Architecture design and documentation processes:**
1. **C4 Model Architecture Documentation** - Multi-level architecture visualization
2. **Architecture Decision Records (ADRs)** - Lightweight decision documentation
3. **System Design Review Process** - Structured architecture evaluation
4. **API Design and Specification** - REST/GraphQL API design workflow
5. **Microservices Decomposition** - Domain-driven service boundary identification

### ⭐ Medium Priority (Strategic Processes)
6. **Migration Strategy Planning** - Legacy system modernization roadmap
7. **Technology Stack Evaluation** - Framework/platform selection framework
8. **Refactoring Plan Creation** - Technical debt remediation planning
9. **Performance Optimization Process** - Systematic performance improvement
10. **Quality Attributes Workshop** - Non-functional requirements elicitation

### 📋 Advanced Priority (Specialized Processes)
11. **Event Storming Session** - Domain modeling and bounded context discovery
12. **Architecture Trade-off Analysis (ATAM)** - Quality attribute trade-off analysis
13. **Domain-Driven Design Strategic Modeling** - Context mapping and boundaries
14. **Resilience Pattern Implementation** - Circuit breaker, bulkhead, retry patterns
15. **Cloud Architecture Design** - Cloud-native architecture patterns

### 🔧 Operational Priority (Runtime Processes)
16. **Observability Implementation** - Logging, monitoring, tracing setup
17. **Infrastructure as Code Review** - IaC architecture validation
18. **Security Architecture Review** - Threat modeling and security patterns
19. **Data Architecture Design** - Data modeling, storage, and flow patterns
20. **DevOps Architecture Alignment** - CI/CD pipeline and deployment architecture

---

## 1. C4 Model Architecture Documentation

**Category**: Architecture Design
**Priority**: 🔥 High
**Implementation Status**: Not Started
**Focus Area**: Architecture Visualization

### Overview
The C4 Model provides a hierarchical approach to software architecture documentation through four levels of abstraction: Context, Container, Component, and Code. This process guides architects through creating comprehensive, audience-appropriate architecture diagrams.

### Key Principles
- **Hierarchical abstraction**: Start high-level, zoom in as needed
- **Audience-driven**: Different diagrams for different stakeholders
- **Technology explicit**: Show concrete technology choices
- **Consistent notation**: Standardized boxes and lines
- **Living documentation**: Keep diagrams synchronized with code

### Implementation Plan

**Directory**: `processes/c4-model-documentation/`

**Files to Create**:
1. **`c4-model-documentation.js`** - Main orchestration process
   - Context diagram creation
   - Container diagram generation
   - Component diagram detailing
   - Supplementary diagram creation

### Process Steps

1. **Context Diagram (Level 1)**
   - Identify system boundaries
   - Map users and external systems
   - Define system purpose and scope
   - Document high-level interactions
   - Output: System context diagram

2. **Container Diagram (Level 2)**
   - Identify applications and data stores
   - Map technology choices (frameworks, databases)
   - Define inter-container communication
   - Document deployment containers
   - Output: Container architecture diagram

3. **Component Diagram (Level 3)**
   - Break down containers into components
   - Define component responsibilities
   - Map component dependencies
   - Document interfaces and APIs
   - Output: Component diagrams per container

4. **Code Diagram (Level 4)** (Optional)
   - Generate class diagrams for complex components
   - Document design patterns usage
   - Map implementation details
   - Output: Class/code-level diagrams

5. **Supplementary Diagrams**
   - Create deployment diagrams
   - Document dynamic behavior
   - Map system landscape (multi-system)
   - Output: Deployment and dynamic diagrams

### Inputs
- System requirements
- Technology stack list
- User personas
- External system dependencies
- Deployment architecture

### Outputs
- C4 Context diagram
- C4 Container diagram
- C4 Component diagrams
- Deployment diagrams
- Architecture narrative document

### Breakpoints
- After Context diagram for stakeholder review
- After Container diagram for technology approval
- After Component diagrams for development team review

### SDK Integration Points
- `ctx.breakpoint()` for diagram review gates
- `ctx.parallel.all()` for multiple component diagrams
- `defineTask` for each diagram level
- Diagram versioning in output artifacts

---

## 2. Architecture Decision Records (ADRs)

**Category**: Architecture Documentation
**Priority**: 🔥 High
**Implementation Status**: Not Started
**Focus Area**: Decision Documentation

### Overview
Architecture Decision Records (ADRs) capture significant architectural decisions along with their context and consequences. This process provides a structured workflow for creating, reviewing, and maintaining ADRs throughout the system lifecycle.

### Key Principles
- **Lightweight documentation**: Quick to write (15-30 minutes)
- **One decision per ADR**: Single architectural decision focus
- **Immutable records**: ADRs are never deleted, only superseded
- **Context preservation**: Capture why decision was needed
- **Consequences explicit**: Document both positive and negative impacts
- **Sequential numbering**: Track decision chronology

### Implementation Plan

**Directory**: `processes/adr-management/`

**Files to Create**:
1. **`adr-management.js`** - Main ADR lifecycle process
   - ADR creation workflow
   - ADR review and approval
   - ADR status updates
   - ADR linking and superseding

### Process Steps

1. **Identify Decision Need**
   - Recognize significant architectural decision
   - Assess if ADR is warranted (vs. code comment)
   - Gather stakeholders
   - Define decision scope
   - Output: Decision proposal

2. **Research Alternatives**
   - List viable options (minimum 2)
   - Research pros/cons for each
   - Prototype or spike if needed
   - Gather team input
   - Output: Options analysis

3. **Draft ADR**
   - Use standard template (Nygard format)
   - Write Context section (forces at play)
   - Write Decision section (chosen approach)
   - Write Consequences section (all impacts)
   - Assign sequential number
   - Output: Draft ADR document

4. **Review and Approval**
   - Share with architecture review board
   - Conduct review meeting
   - Incorporate feedback
   - Get formal approval
   - Output: Approved ADR

5. **Publish ADR**
   - Commit to version control
   - Update ADR index
   - Communicate to team
   - Link related ADRs
   - Output: Published ADR with status "Accepted"

6. **Maintain ADRs**
   - Update status when superseded
   - Link new ADRs to related ones
   - Archive deprecated decisions
   - Review periodically
   - Output: Updated ADR repository

### Inputs
- Architectural decision trigger
- Technical context
- Business requirements
- Constraints and trade-offs
- Stakeholder list

### Outputs
- Numbered ADR document (Markdown)
- ADR index/catalog
- Decision log
- Architecture history
- Related ADR links

### Breakpoints
- After draft for team review
- After review meeting for formal approval
- When superseding existing ADR for impact assessment

### SDK Integration Points
- `ctx.breakpoint()` for review gates
- `defineTask` for each ADR lifecycle stage
- Template generation
- Git commit integration
- ADR number sequencing

---

## 3. System Design Review Process

**Category**: Architecture Evaluation
**Priority**: 🔥 High
**Implementation Status**: Not Started
**Focus Area**: Architecture Quality Assurance

### Overview
A structured process for evaluating software architectures against quality attributes, identifying risks, and ensuring alignment with business goals. Based on methods like ATAM (Architecture Tradeoff Analysis Method) but adapted for agile environments.

### Key Principles
- **Quality attribute focus**: Evaluate against specific system qualities
- **Scenario-based evaluation**: Use concrete scenarios to test architecture
- **Risk identification**: Surface architectural risks early
- **Stakeholder involvement**: Include business and technical stakeholders
- **Trade-off explicit**: Make architectural trade-offs visible
- **Actionable outcomes**: Produce concrete improvement recommendations

### Implementation Plan

**Directory**: `processes/system-design-review/`

**Files to Create**:
1. **`system-design-review.js`** - Main review orchestration
   - Pre-review preparation
   - Architecture presentation
   - Quality attribute scenarios
   - Risk assessment
   - Recommendations

### Process Steps

1. **Prepare for Review**
   - Schedule review meeting (2-4 hours)
   - Gather architecture documentation
   - Identify stakeholders
   - Define quality attributes to evaluate
   - Prepare presentation materials
   - Output: Review agenda and materials

2. **Present Architecture**
   - Present business context and drivers
   - Walk through architecture (C4 diagrams)
   - Explain key decisions (reference ADRs)
   - Describe technology choices
   - Time: 30-45 minutes
   - Output: Shared understanding of architecture

3. **Define Quality Attribute Scenarios**
   - Elicit scenarios for key quality attributes
   - Prioritize scenarios by importance
   - Document scenario details (stimulus, response, measure)
   - Example: "System handles 10K concurrent users with <200ms latency"
   - Output: Prioritized scenario list

4. **Evaluate Architecture Against Scenarios**
   - For each high-priority scenario:
     - Analyze how architecture supports it
     - Identify architectural approaches used
     - Document risks and sensitivities
     - Assess trade-offs made
   - Output: Scenario evaluation results

5. **Identify Risks and Non-Risks**
   - **Risks**: Architectural decisions with uncertain outcomes
   - **Sensitivity Points**: Decisions critical to quality attributes
   - **Trade-offs**: Decisions affecting multiple attributes
   - **Non-Risks**: Decisions with low risk
   - Output: Risk catalog

6. **Generate Recommendations**
   - Prioritize risks by severity and likelihood
   - Propose risk mitigation strategies
   - Suggest architectural improvements
   - Define follow-up actions
   - Assign owners and timelines
   - Output: Action plan with recommendations

7. **Document and Communicate**
   - Create review report
   - Document decisions and rationale
   - Share with stakeholders
   - Track action items
   - Output: Review report and action tracker

### Inputs
- Architecture documentation (C4 diagrams, ADRs)
- Business requirements and drivers
- Quality attribute priorities
- Stakeholder availability
- Existing system metrics (if brownfield)

### Outputs
- Review meeting minutes
- Quality attribute scenarios
- Risk catalog (risks, sensitivities, trade-offs)
- Prioritized recommendations
- Action plan with owners and dates
- Architecture review report

### Breakpoints
- After scenario definition for validation
- After risk identification for prioritization
- After recommendations for approval

### SDK Integration Points
- `ctx.breakpoint()` for review gates
- `ctx.parallel.all()` for parallel scenario evaluation
- `defineTask` for each review phase
- Scenario template generation
- Risk tracking integration

---

## 4. API Design and Specification

**Category**: Interface Design
**Priority**: 🔥 High
**Implementation Status**: Not Started
**Focus Area**: API Architecture

### Overview
A comprehensive process for designing RESTful or GraphQL APIs that are intuitive, consistent, well-documented, and evolvable. Covers resource modeling, endpoint design, versioning, documentation, and validation.

### Key Principles
- **Resource-oriented design**: Model domain entities as resources
- **Consistent conventions**: Follow REST/HTTP standards
- **Design-first approach**: Specify before implementing
- **Version from day one**: Plan for API evolution
- **Comprehensive documentation**: OpenAPI/GraphQL schema
- **Security by default**: Authentication, authorization, rate limiting

### Implementation Plan

**Directory**: `processes/api-design/`

**Files to Create**:
1. **`api-design.js`** - Main API design orchestration
   - Resource modeling
   - Endpoint design
   - Schema definition
   - Documentation generation
   - Validation and testing

### Process Steps

1. **Identify Resources and Relationships**
   - Analyze domain model
   - Identify core entities
   - Map entity relationships
   - Define resource hierarchy
   - Output: Resource model diagram

2. **Design Resource Representations**
   - Define JSON schema for each resource
   - Choose fields to expose
   - Handle relationships (embedded vs. linked)
   - Define filtering, sorting, pagination
   - Output: Resource schemas

3. **Design API Endpoints** (REST)
   - Map resources to URLs
   - Define HTTP methods (GET, POST, PUT, PATCH, DELETE)
   - Design URL structure and parameters
   - Plan query parameters
   - Output: Endpoint inventory

4. **Design GraphQL Schema** (if GraphQL)
   - Define types and fields
   - Design queries and mutations
   - Plan subscriptions (if real-time)
   - Handle relationships with resolvers
   - Output: GraphQL schema (SDL)

5. **Define API Contract**
   - Create OpenAPI 3.0 specification (REST)
   - Or GraphQL schema with documentation
   - Document request/response examples
   - Define error responses
   - Specify authentication/authorization
   - Output: API specification document

6. **Plan Versioning Strategy**
   - Choose versioning approach (URL, header, content negotiation)
   - Define deprecation policy
   - Plan backwards compatibility
   - Document breaking vs. non-breaking changes
   - Output: Versioning guidelines

7. **Design Cross-Cutting Concerns**
   - Authentication (OAuth 2.0, JWT, API keys)
   - Authorization (RBAC, ABAC)
   - Rate limiting and throttling
   - Caching headers
   - CORS policies
   - Output: Security and operational policies

8. **Generate Documentation**
   - Generate interactive API docs (Swagger UI, GraphQL Playground)
   - Write getting started guide
   - Provide code examples (cURL, SDKs)
   - Document common use cases
   - Output: Developer portal content

9. **Validate Design**
   - Review with API consumers (frontend, partners)
   - Validate against use cases
   - Create mock server for testing
   - Gather feedback
   - Iterate on design
   - Output: Validated API specification

10. **Plan Implementation**
    - Break down into implementation tasks
    - Define integration tests
    - Plan deployment strategy
    - Output: Implementation backlog

### Inputs
- Domain model or entity relationship diagram
- Use cases and user stories
- Non-functional requirements (performance, security)
- API consumer needs
- Existing APIs (if any)

### Outputs
- API specification (OpenAPI 3.0 or GraphQL SDL)
- Resource model diagram
- Endpoint inventory
- Authentication/authorization design
- Versioning strategy document
- Interactive API documentation
- Mock server for testing
- Implementation task list

### Breakpoints
- After resource modeling for domain validation
- After endpoint design for consumer review
- After specification draft for stakeholder approval
- After mock server creation for integration testing

### SDK Integration Points
- `ctx.breakpoint()` for review gates
- `ctx.parallel.all()` for parallel endpoint design
- `defineTask` for each design phase
- OpenAPI/GraphQL schema generation
- Mock server deployment
- Validation rule checking

---

## 5. Microservices Decomposition

**Category**: Architecture Design
**Priority**: 🔥 High
**Implementation Status**: Not Started
**Focus Area**: Service Boundaries

### Overview
A systematic process for decomposing monolithic applications into microservices or designing microservices from scratch. Uses domain-driven design principles to identify bounded contexts and define service boundaries.

### Key Principles
- **Domain-driven boundaries**: Services aligned with business capabilities
- **Bounded contexts**: Clear domain boundaries from DDD
- **Single responsibility**: Each service owns one business capability
- **Autonomous services**: Independent deployment and scaling
- **Data ownership**: Each service owns its data
- **Loose coupling**: Minimal inter-service dependencies

### Implementation Plan

**Directory**: `processes/microservices-decomposition/`

**Files to Create**:
1. **`microservices-decomposition.js`** - Main decomposition process
   - Domain analysis
   - Bounded context identification
   - Service boundary definition
   - Integration pattern design
   - Migration planning

### Process Steps

1. **Understand the Domain**
   - Conduct domain expert interviews
   - Map business capabilities
   - Identify core vs. supporting domains
   - Create ubiquitous language glossary
   - Output: Domain knowledge document

2. **Identify Bounded Contexts**
   - Run Event Storming workshop (if applicable)
   - Identify domain aggregates
   - Find natural boundaries (where terminology changes)
   - Define context boundaries
   - Create context map
   - Output: Bounded context diagram

3. **Define Service Candidates**
   - Map bounded contexts to potential services
   - Identify service responsibilities
   - Define service APIs
   - Assess service size (not too big, not too small)
   - Output: Service candidate list

4. **Analyze Service Dependencies**
   - Map data dependencies
   - Identify synchronous vs. asynchronous needs
   - Find circular dependencies (red flag)
   - Plan for shared data (duplication vs. service)
   - Output: Service dependency graph

5. **Design Service Communication**
   - Choose sync vs. async patterns per interaction
   - Design REST/gRPC APIs for synchronous
   - Design event schemas for asynchronous
   - Select message broker (RabbitMQ, Kafka, etc.)
   - Define service mesh requirements
   - Output: Integration architecture

6. **Plan Data Management**
   - Database per service pattern
   - Define data ownership per service
   - Handle distributed transactions (Saga pattern)
   - Plan for eventual consistency
   - Design data synchronization
   - Output: Data architecture diagram

7. **Address Cross-Cutting Concerns**
   - API Gateway design
   - Authentication/authorization (centralized vs. distributed)
   - Distributed tracing and logging
   - Configuration management
   - Service discovery
   - Output: Cross-cutting concerns design

8. **Assess and Mitigate Risks**
   - Identify distributed system challenges
   - Plan for network failures
   - Design circuit breakers and bulkheads
   - Test fallback strategies
   - Output: Risk mitigation plan

9. **Create Migration Strategy** (if from monolith)
   - Prioritize services to extract
   - Choose strangler pattern or big bang
   - Define migration phases
   - Plan data migration
   - Create rollback strategy
   - Output: Migration roadmap

10. **Validate with Architecture Review**
    - Present to stakeholders
    - Conduct design review
    - Gather feedback
    - Iterate on design
    - Output: Approved microservices architecture

### Inputs
- Current system architecture (if brownfield)
- Business requirements and capabilities
- Domain expert availability
- Team structure and size
- Technology constraints
- Scalability and performance requirements

### Outputs
- Bounded context map
- Microservices architecture diagram
- Service responsibility matrix
- Service API specifications
- Integration patterns document
- Data management strategy
- Migration roadmap (if applicable)
- ADRs for key decisions
- Implementation backlog

### Breakpoints
- After bounded context identification for domain validation
- After service candidate definition for team review
- After integration design for architecture approval
- After migration strategy for stakeholder sign-off

### SDK Integration Points
- `ctx.breakpoint()` for review gates
- `ctx.parallel.all()` for parallel service design
- `defineTask` for each decomposition phase
- Event Storming integration (if applicable)
- Diagram generation
- ADR creation triggers

---

## 6. Migration Strategy Planning

**Category**: Architecture Evolution
**Priority**: ⭐ Medium
**Implementation Status**: Not Started
**Focus Area**: Legacy Modernization

### Overview
A comprehensive process for planning and executing migrations from legacy systems to modern architectures. Covers assessment, risk analysis, strategy selection, phased planning, and execution monitoring.

### Key Principles
- **Incremental migration**: Minimize big-bang risks
- **Strangler Fig pattern**: Gradually replace legacy system
- **Risk-driven prioritization**: Tackle highest-risk areas strategically
- **Business continuity**: Maintain operations during migration
- **Rollback planning**: Always have a way back
- **Data migration first**: Solve data challenges early

### Implementation Plan

**Directory**: `processes/migration-strategy/`

**Files to Create**:
1. **`migration-strategy.js`** - Main migration planning process

### Process Steps

1. **Assess Current State**
   - Document existing architecture
   - Identify pain points and technical debt
   - Map dependencies and integrations
   - Analyze data architecture
   - Measure current performance/reliability
   - Output: Current state assessment report

2. **Define Target State**
   - Design future architecture
   - Select target technologies
   - Define success criteria
   - Establish quality attributes
   - Output: Target architecture design

3. **Choose Migration Strategy**
   - **Rehost** (lift-and-shift): Minimal changes
   - **Replatform**: Minor optimizations
   - **Refactor/Re-architect**: Significant restructuring
   - **Rebuild**: Start from scratch
   - **Replace**: Buy instead of build
   - **Retire**: Eliminate functionality
   - Output: Strategy selection per component

4. **Plan Migration Phases**
   - Prioritize components by risk/value
   - Define migration waves
   - Establish dependencies between phases
   - Set phase timelines and resources
   - Plan for parallel operation (old + new)
   - Output: Migration roadmap

5. **Design Data Migration**
   - Analyze data schemas (old vs. new)
   - Plan data transformation rules
   - Choose migration approach (big-bang vs. incremental)
   - Design data synchronization (dual-write, CDC)
   - Plan data validation and reconciliation
   - Output: Data migration plan

6. **Plan Testing Strategy**
   - Define test scenarios
   - Plan load and performance testing
   - Design rollback testing
   - Plan user acceptance testing
   - Establish success metrics
   - Output: Testing plan

7. **Create Rollback Strategy**
   - Define rollback triggers
   - Plan rollback procedures per phase
   - Test rollback mechanisms
   - Document emergency contacts
   - Output: Rollback playbook

8. **Execute and Monitor**
   - Run pilot/proof of concept
   - Execute migration phases
   - Monitor performance and errors
   - Gather user feedback
   - Adjust plan as needed
   - Output: Migration status reports

### Inputs
- Legacy system documentation
- Business requirements
- Budget and timeline constraints
- Team capabilities
- Risk tolerance
- Compliance requirements

### Outputs
- Current state assessment
- Target architecture design
- Migration strategy document
- Phased migration roadmap
- Data migration plan
- Testing strategy
- Rollback procedures
- Risk mitigation plan
- Cost estimates
- Implementation schedule

### Breakpoints
- After assessment for baseline validation
- After target state design for approval
- After strategy selection for stakeholder buy-in
- Before each migration phase for readiness check

### SDK Integration Points
- `ctx.breakpoint()` for phase gates
- `defineTask` for migration phases
- Monitoring integration
- Rollback automation
- Status reporting

---

## 7. Technology Stack Evaluation

**Category**: Architecture Decision
**Priority**: ⭐ Medium
**Implementation Status**: Not Started
**Focus Area**: Technology Selection

### Overview
A structured process for evaluating and selecting technologies (frameworks, libraries, platforms, databases) for a project. Includes proof of concepts, scoring matrices, and risk assessment.

### Key Principles
- **Requirements-driven**: Evaluate against specific needs
- **Hands-on validation**: Build POCs for top candidates
- **Multi-dimensional scoring**: Consider multiple criteria
- **Long-term viability**: Assess community, support, roadmap
- **TCO analysis**: Include licensing, training, operational costs
- **Team capability**: Consider learning curve and expertise

### Implementation Plan

**Directory**: `processes/tech-stack-evaluation/`

**Process Steps**

1. **Define Requirements**
   - Functional requirements
   - Non-functional requirements (performance, scalability, security)
   - Team constraints (skills, preferences)
   - Budget and timeline
   - Integration needs
   - Output: Requirements document

2. **Identify Candidates**
   - Research options (frameworks, platforms, tools)
   - Create long list (8-10 options)
   - Preliminary filtering (basic requirements)
   - Shortlist top candidates (3-4)
   - Output: Candidate shortlist

3. **Define Evaluation Criteria**
   - Technical fit (features, performance, scalability)
   - Maturity and stability
   - Community and ecosystem
   - Documentation quality
   - Learning curve
   - Licensing and cost
   - Vendor support
   - Long-term viability
   - Output: Weighted scoring matrix

4. **Research Each Candidate**
   - Read documentation
   - Review case studies
   - Check GitHub activity (stars, issues, contributors)
   - Read community discussions
   - Assess security vulnerabilities
   - Output: Research notes per candidate

5. **Build Proof of Concepts**
   - Define POC scope (same for all candidates)
   - Implement POC for each candidate
   - Measure performance
   - Assess developer experience
   - Document challenges and surprises
   - Output: POC code and results

6. **Score and Compare**
   - Score each candidate against criteria
   - Calculate weighted scores
   - Identify strengths and weaknesses
   - Perform sensitivity analysis
   - Output: Comparison matrix

7. **Assess Risks**
   - Identify adoption risks
   - Migration risks (if replacing existing)
   - Vendor lock-in risks
   - Community sustainability risks
   - Output: Risk register

8. **Make Recommendation**
   - Recommend top choice
   - Justify decision
   - Document alternatives considered
   - Create ADR
   - Output: Technology selection report and ADR

### Inputs
- Project requirements
- Constraints (budget, timeline, skills)
- Existing technology landscape
- Evaluation criteria preferences

### Outputs
- Candidate shortlist
- POC implementations
- Scoring matrix with results
- Risk assessment
- Technology recommendation
- ADR documenting decision
- Onboarding plan for chosen tech

### Breakpoints
- After shortlist for validation
- After POC completion for hands-on review
- After scoring for decision validation

---

## 8. Refactoring Plan Creation

**Category**: Technical Debt Management
**Priority**: ⭐ Medium
**Implementation Status**: Not Started
**Focus Area**: Code Quality Improvement

### Overview
A systematic process for identifying technical debt, prioritizing refactoring efforts, and creating actionable plans to improve code quality without breaking functionality.

### Key Principles
- **Test first**: Ensure comprehensive tests before refactoring
- **Small steps**: Incremental refactoring reduces risk
- **Continuous integration**: Commit frequently
- **Boy Scout Rule**: Leave code better than you found it
- **Balance with features**: Refactor in context of new work
- **Measure improvement**: Track code quality metrics

### Implementation Plan

**Directory**: `processes/refactoring-plan/`

**Process Steps**

1. **Identify Technical Debt**
   - Run static analysis tools (SonarQube, CodeClimate)
   - Review code complexity metrics
   - Collect team feedback (pain points)
   - Analyze bug patterns
   - Identify architectural smells
   - Output: Technical debt inventory

2. **Categorize and Prioritize**
   - Rate by severity (high/medium/low)
   - Assess business impact
   - Estimate refactoring effort
   - Calculate pain-to-gain ratio
   - Prioritize by ROI
   - Output: Prioritized debt backlog

3. **Define Refactoring Goals**
   - Reduce cyclomatic complexity
   - Improve test coverage
   - Eliminate duplication
   - Improve modularity
   - Enhance readability
   - Output: Measurable goals

4. **Create Test Safety Net**
   - Assess current test coverage
   - Add missing unit tests
   - Add integration tests
   - Add regression tests
   - Set coverage targets
   - Output: Test suite with baseline coverage

5. **Design Refactoring Approach**
   - Choose refactoring patterns (Extract Method, Move Class, etc.)
   - Plan incremental steps
   - Identify breaking points for commits
   - Consider feature flags for large changes
   - Output: Refactoring strategy

6. **Estimate and Schedule**
   - Estimate effort per item
   - Allocate capacity (% of sprint)
   - Balance with feature work
   - Create timeline
   - Output: Refactoring schedule

7. **Execute Refactorings**
   - Follow red-green-refactor cycle
   - Commit frequently
   - Run tests continuously
   - Conduct code reviews
   - Track progress
   - Output: Improved codebase

8. **Measure Improvement**
   - Re-run static analysis
   - Compare before/after metrics
   - Assess team velocity impact
   - Gather team feedback
   - Output: Improvement report

### Inputs
- Codebase
- Static analysis reports
- Bug history
- Team feedback
- Code quality metrics

### Outputs
- Technical debt inventory
- Prioritized refactoring backlog
- Refactoring plan with estimates
- Test coverage improvements
- Refactored code
- Before/after metrics
- Lessons learned

### Breakpoints
- After prioritization for approval
- After test coverage improvements for validation
- After each major refactoring for review

---

## 9. Performance Optimization Process

**Category**: Quality Attributes
**Priority**: ⭐ Medium
**Implementation Status**: Not Started
**Focus Area**: System Performance

### Overview
A data-driven process for identifying performance bottlenecks, designing optimizations, implementing improvements, and validating results. Covers application, database, and infrastructure performance.

### Key Principles
- **Measure first**: Profile before optimizing
- **Data-driven decisions**: Use metrics, not assumptions
- **Target bottlenecks**: Optimize the slowest parts
- **Iterative approach**: Optimize, measure, repeat
- **Performance budgets**: Set and enforce targets
- **Real-world testing**: Test under production-like conditions

### Implementation Plan

**Directory**: `processes/performance-optimization/`

**Process Steps**

1. **Establish Performance Baselines**
   - Define performance metrics (latency, throughput, resource usage)
   - Measure current performance
   - Identify performance goals (SLAs, targets)
   - Document baseline results
   - Output: Performance baseline report

2. **Profile and Identify Bottlenecks**
   - Run application profiling (CPU, memory, I/O)
   - Analyze database query performance
   - Monitor network latency
   - Identify slow endpoints/functions
   - Use APM tools (New Relic, Datadog, etc.)
   - Output: Bottleneck analysis

3. **Prioritize Optimizations**
   - Rank bottlenecks by impact
   - Estimate optimization effort
   - Calculate ROI (performance gain vs. effort)
   - Prioritize high-impact, low-effort items
   - Output: Optimization backlog

4. **Design Optimization Strategies**
   - **Application-level**: Algorithm optimization, caching, lazy loading
   - **Database-level**: Indexing, query optimization, denormalization
   - **Infrastructure-level**: Scaling, CDN, load balancing
   - **Architecture-level**: Async processing, microservices, caching layers
   - Output: Optimization design

5. **Implement Optimizations**
   - Implement changes incrementally
   - Test in staging environment
   - Use feature flags for controlled rollout
   - Monitor for regressions
   - Output: Optimized code/configuration

6. **Validate Improvements**
   - Run performance tests
   - Compare to baseline
   - Measure performance gain
   - Check for side effects
   - Output: Performance validation report

7. **Load Test and Stress Test**
   - Simulate peak load
   - Test system limits
   - Identify new bottlenecks
   - Validate auto-scaling
   - Output: Load test results

8. **Document and Monitor**
   - Document optimizations made
   - Update performance budget
   - Set up continuous monitoring
   - Create performance alerts
   - Output: Performance documentation and dashboards

### Inputs
- Performance requirements/SLAs
- Current system metrics
- Application and infrastructure access
- Load testing tools

### Outputs
- Performance baseline report
- Bottleneck analysis
- Optimization backlog
- Implemented optimizations
- Performance validation results
- Load test results
- Performance monitoring dashboards
- Optimization documentation

### Breakpoints
- After profiling for bottleneck validation
- After optimization design for review
- After each optimization for validation

---

## 10. Quality Attributes Workshop

**Category**: Requirements Elicitation
**Priority**: ⭐ Medium
**Implementation Status**: Not Started
**Focus Area**: Non-Functional Requirements

### Overview
A facilitated workshop for identifying, prioritizing, and specifying quality attributes (non-functional requirements) for a system. Ensures architecture addresses stakeholder concerns beyond functional requirements.

### Key Principles
- **Scenario-based**: Use concrete scenarios to define quality attributes
- **Stakeholder-driven**: Include business and technical stakeholders
- **Prioritization**: Not all quality attributes are equal
- **Measurable**: Define specific, testable criteria
- **Trade-off aware**: Acknowledge conflicting attributes
- **Early in lifecycle**: Define before major architecture decisions

### Implementation Plan

**Directory**: `processes/quality-attributes-workshop/`

**Process Steps**

1. **Prepare for Workshop**
   - Identify stakeholders (business, technical, operations)
   - Schedule workshop (2-4 hours)
   - Prepare quality attribute reference (ISO 25010, FURPS+)
   - Gather business context
   - Output: Workshop agenda and invitations

2. **Present System Context**
   - Describe system purpose and scope
   - Explain business drivers
   - Identify key use cases
   - Present constraints (budget, timeline, technology)
   - Output: Shared understanding

3. **Brainstorm Quality Attributes**
   - Introduce quality attributes framework (scalability, security, usability, etc.)
   - Facilitate brainstorming session
   - Collect stakeholder concerns
   - Group into categories
   - Output: Initial quality attribute list

4. **Define Quality Attribute Scenarios**
   - For each attribute, create scenarios with:
     - **Stimulus**: Event triggering the scenario
     - **Response**: How system should respond
     - **Measure**: Quantifiable success criteria
   - Example: "Under peak load (10K users), system responds in <200ms for 95% of requests"
   - Output: Quality attribute scenarios

5. **Prioritize Scenarios**
   - Vote on importance (MoSCoW method: Must have, Should have, Could have, Won't have)
   - Identify conflicts and trade-offs
   - Discuss implications
   - Reach consensus on top priorities
   - Output: Prioritized scenario list

6. **Refine and Document**
   - Detail top-priority scenarios
   - Define acceptance criteria
   - Identify measurement approach
   - Document assumptions and constraints
   - Output: Quality attribute requirements document

7. **Map to Architecture**
   - Identify architectural patterns that support each attribute
   - Document trade-offs
   - Plan validation approach (how to test)
   - Output: Architecture implications

8. **Review and Validate**
   - Review with stakeholders
   - Get sign-off on priorities
   - Integrate into requirements backlog
   - Plan for architecture design
   - Output: Approved quality attributes

### Inputs
- Business requirements
- Stakeholder availability
- System scope description
- Known constraints

### Outputs
- Quality attribute list
- Prioritized quality attribute scenarios
- Measurement criteria
- Trade-off analysis
- Architecture implications
- Quality attribute requirements document

### Breakpoints
- After scenario definition for validation
- After prioritization for consensus check

---

## 11. Event Storming Session

**Category**: Domain Modeling
**Priority**: 📋 Advanced
**Implementation Status**: Not Started
**Focus Area**: Domain Discovery

### Overview
A collaborative workshop technique for discovering domain events, commands, aggregates, and bounded contexts. Rapid way to build shared understanding of complex business domains.

### Key Principles
- **Event-first**: Focus on domain events (things that happened)
- **Collaborative**: Include domain experts and developers
- **Visual**: Use sticky notes on large wall
- **Time-based flow**: Arrange events chronologically
- **Inclusive**: Everyone participates equally
- **Fast-paced**: Keep energy high, defer details

### Implementation Plan

**Directory**: `processes/event-storming/`

**Process Steps**

1. **Prepare Space and Materials**
   - Book large room with wall space
   - Gather supplies (sticky notes, markers)
   - Invite participants (domain experts, developers, stakeholders)
   - Define scope (what domain or process to model)
   - Output: Workshop setup

2. **Chaotic Exploration (Events)**
   - Participants write domain events (past tense)
   - Place on wall in approximate chronological order
   - No discussion yet, just capture
   - Duration: 15-30 minutes
   - Output: Wall of events

3. **Enforce Timeline**
   - Group walks through events left to right
   - Identify duplicates and gaps
   - Refine event ordering
   - Ask clarifying questions
   - Output: Refined event timeline

4. **Add Commands and Users**
   - Identify commands that trigger events
   - Add user/actor who triggers command
   - Use different colored sticky notes
   - Output: Commands and actors added

5. **Identify Aggregates**
   - Group events around aggregates (consistency boundaries)
   - Name aggregates
   - Identify aggregate boundaries
   - Output: Aggregate groupings

6. **Surface External Systems and Policies**
   - Identify external system integrations
   - Document business rules/policies
   - Add automation (policy-driven events)
   - Output: Complete domain model

7. **Identify Bounded Contexts**
   - Look for terminology changes
   - Find natural boundaries
   - Define context boundaries
   - Name bounded contexts
   - Output: Bounded context map

8. **Document and Digitize**
   - Take photos of the wall
   - Create digital diagram (Miro, LucidChart)
   - Document key insights
   - Share with team
   - Output: Digital event storm diagram

### Inputs
- Domain experts availability
- Business process knowledge
- Workshop space and materials

### Outputs
- Domain event timeline
- Commands and actors
- Aggregate boundaries
- Bounded context map
- External system integrations
- Business rules documentation
- Event storm photos and digital diagram

### Breakpoints
- After chaotic exploration for energy check
- After timeline enforcement for validation

---

## 12. Architecture Trade-off Analysis (ATAM)

**Category**: Architecture Evaluation
**Priority**: 📋 Advanced
**Implementation Status**: Not Started
**Focus Area**: Quality Attribute Analysis

### Overview
The Architecture Tradeoff Analysis Method (ATAM) is a structured technique for evaluating software architectures against quality attribute requirements, identifying risks, and analyzing trade-offs.

### Key Principles
- **Quality attribute focus**: Evaluate how architecture achieves quality goals
- **Scenario-driven**: Use concrete scenarios to test architecture
- **Trade-off explicit**: Make architectural trade-offs visible
- **Risk-based**: Identify architectural risks early
- **Stakeholder participation**: Include business and technical stakeholders
- **Iterative**: Can be repeated as architecture evolves

### Implementation Plan

**Directory**: `processes/atam-analysis/`

**Process Steps**

1. **Present ATAM Method**
2. **Present Business Drivers**
3. **Present Architecture**
4. **Identify Architectural Approaches**
5. **Generate Quality Attribute Utility Tree**
6. **Analyze Architectural Approaches**
7. **Brainstorm and Prioritize Scenarios**
8. **Analyze Architectural Approaches (Revisited)**
9. **Present Results**

### Outputs
- Quality attribute utility tree
- Architectural approaches catalog
- Scenario analysis results
- Risk themes
- Sensitivity points
- Trade-off points
- ATAM report

---

## 13. Domain-Driven Design Strategic Modeling

**Category**: Domain Modeling
**Priority**: 📋 Advanced
**Implementation Status**: Not Started
**Focus Area**: Bounded Contexts and Context Mapping

### Overview
Strategic DDD focuses on identifying bounded contexts, defining their relationships, and creating a context map to guide system architecture and team organization.

### Process Steps**

1. **Understand the Domain**
2. **Identify Subdomains**
3. **Define Bounded Contexts**
4. **Create Context Map**
5. **Define Context Relationships**
6. **Align with Team Structure**

### Outputs
- Subdomain categorization (core, supporting, generic)
- Bounded context definitions
- Context map diagram
- Ubiquitous language glossary per context
- Team ownership mapping

---

## 14. Resilience Pattern Implementation

**Category**: Reliability Engineering
**Priority**: 📋 Advanced
**Implementation Status**: Not Started
**Focus Area**: Fault Tolerance

### Overview
A process for implementing resilience patterns (Circuit Breaker, Bulkhead, Retry, Timeout) to improve system reliability and graceful degradation.

### Process Steps

1. **Identify Failure Points**
2. **Select Resilience Patterns**
3. **Design Circuit Breakers**
4. **Implement Bulkheads**
5. **Configure Retry Logic**
6. **Set Timeouts**
7. **Test Failure Scenarios**
8. **Monitor and Tune**

### Outputs
- Failure mode analysis
- Resilience pattern design
- Implementation code/configuration
- Chaos engineering tests
- Monitoring dashboards

---

## 15. Cloud Architecture Design

**Category**: Infrastructure Architecture
**Priority**: 📋 Advanced
**Implementation Status**: Not Started
**Focus Area**: Cloud-Native Patterns

### Overview
A process for designing cloud-native architectures leveraging cloud provider services (AWS, Azure, GCP) including compute, storage, networking, and managed services.

### Process Steps

1. **Define Cloud Strategy**
2. **Select Cloud Provider**
3. **Design Compute Architecture**
4. **Design Data Architecture**
5. **Design Network Architecture**
6. **Plan Security and Compliance**
7. **Design for High Availability**
8. **Optimize Costs**
9. **Create Infrastructure as Code**

### Outputs
- Cloud architecture diagram
- Service selection matrix
- Cost estimates
- Security design
- Infrastructure as Code (Terraform, CloudFormation)
- Disaster recovery plan

---

## 16. Observability Implementation

**Category**: Operational Excellence
**Priority**: 🔧 Operational
**Implementation Status**: Not Started
**Focus Area**: Monitoring, Logging, Tracing

### Overview
A comprehensive process for implementing observability in systems through structured logging, metrics collection, distributed tracing, and dashboard creation.

### Process Steps

1. **Define Observability Requirements**
2. **Implement Structured Logging**
3. **Define Metrics and SLIs**
4. **Implement Distributed Tracing**
5. **Create Dashboards**
6. **Set Up Alerts**
7. **Test Observability**

### Outputs
- Logging standards
- Metrics catalog
- Tracing implementation
- Monitoring dashboards
- Alert definitions
- Runbooks

---

## 17. Infrastructure as Code Review

**Category**: Infrastructure
**Priority**: 🔧 Operational
**Implementation Status**: Not Started
**Focus Area**: IaC Quality

### Overview
A review process for Infrastructure as Code ensuring best practices, security, cost optimization, and maintainability.

### Process Steps

1. **Review IaC Structure**
2. **Check Security Compliance**
3. **Validate Resource Configuration**
4. **Assess Cost Implications**
5. **Review State Management**
6. **Check Documentation**
7. **Test IaC Changes**

### Outputs
- IaC review checklist
- Security findings
- Cost optimization recommendations
- Approved IaC changes

---

## 18. Security Architecture Review

**Category**: Security
**Priority**: 🔧 Operational
**Implementation Status**: Not Started
**Focus Area**: Threat Modeling

### Overview
A security-focused architecture review including threat modeling, security pattern validation, and vulnerability assessment.

### Process Steps

1. **Create Threat Model**
2. **Identify Attack Surfaces**
3. **Review Security Patterns**
4. **Assess Authentication/Authorization**
5. **Review Data Protection**
6. **Check Compliance Requirements**
7. **Perform Security Testing**

### Outputs
- Threat model diagram
- Security risk register
- Security requirements
- Remediation plan

---

## 19. Data Architecture Design

**Category**: Data Management
**Priority**: 🔧 Operational
**Implementation Status**: Not Started
**Focus Area**: Data Modeling and Flow

### Overview
A process for designing data architecture including data models, storage patterns, data flow, and data governance.

### Process Steps

1. **Analyze Data Requirements**
2. **Design Data Models**
3. **Select Storage Technologies**
4. **Design Data Flow**
5. **Plan Data Governance**
6. **Design Data Security**
7. **Plan Data Migration**

### Outputs
- Data model diagrams (logical, physical)
- Storage architecture
- Data flow diagrams
- Data governance policies
- Data dictionary

---

## 20. DevOps Architecture Alignment

**Category**: DevOps
**Priority**: 🔧 Operational
**Implementation Status**: Not Started
**Focus Area**: CI/CD and Deployment

### Overview
A process for aligning software architecture with DevOps practices ensuring continuous integration, deployment, and delivery.

### Process Steps

1. **Review Current CI/CD**
2. **Design Deployment Architecture**
3. **Plan Release Strategy**
4. **Implement Feature Flags**
5. **Design Rollback Mechanisms**
6. **Plan Zero-Downtime Deployment**
7. **Monitor Deployments**

### Outputs
- CI/CD pipeline architecture
- Deployment strategy document
- Release checklist
- Rollback procedures
- Deployment automation

---

## Summary

This backlog contains **20 software architecture processes** organized into four priority tiers:

**🔥 High Priority (5 processes)**: Core architecture design and documentation
**⭐ Medium Priority (5 processes)**: Strategic architecture processes
**📋 Advanced Priority (5 processes)**: Specialized architecture techniques
**🔧 Operational Priority (5 processes)**: Runtime and operational processes

These processes cover the key focus areas requested:
- ✅ Architecture design (C4 model)
- ✅ ADRs (Architecture Decision Records)
- ✅ System design reviews
- ✅ Refactoring plans
- ✅ Migration strategies
- ✅ API design
- ✅ Microservices decomposition
- ✅ Performance optimization
- ✅ Tech stack evaluation

Each process is designed to integrate with the Babysitter SDK orchestration framework using `defineTask`, `ctx.breakpoint()`, and `ctx.parallel.all()` patterns.

## Next Steps

1. **Implement High Priority processes first** (C4, ADRs, Design Review, API Design, Microservices)
2. **Create process templates** for consistent implementation
3. **Build reusable task libraries** for common architecture activities
4. **Integrate with existing tools** (diagram generation, ADR tools, static analysis)
5. **Gather feedback** from architecture practitioners
6. **Iterate and improve** based on real-world usage
