DevOps AI Toolkit

# PRD: Extend Solution Support Beyond Applications **Created**: 2025-07-28 **Status**: Complete **Owner**: Viktor Farcic **Last Updated**: 2025-08-05 **Completed**: 2025-08-05 ## Executive Summary Update dot-ai's presentation and examples to clearly communicate its existing capability to recommend and deploy infrastructure resources, operators, networking, storage, and other Kubernetes resources beyond application deployments. **Key Insight**: Code analysis revealed the system is already architecturally generic and can handle any Kubernetes resource type. The limitation is in application-focused messaging and examples, not core functionality. ## Documentation Changes ### Files Created/Updated - **`src/tools/recommend.ts`** - Updated - Remove application-focused bias in tool descriptions - **`prompts/*.md`** - Updated - Add infrastructure examples and broader terminology - **`docs/mcp-guide.md`** - Updated - Add infrastructure deployment examples to existing MCP tools - **`README.md`** - Updated - Clarify infrastructure deployment capability in existing features - **Testing validation** - New - Verify system works with infrastructure use cases ### Content Location Map - **Tool Descriptions**: See `src/tools/recommend.ts` (Updated tool descriptions) - **Prompt Examples**: See `prompts/` directory (Enhanced with infrastructure examples) - **MCP Documentation**: See `docs/mcp-guide.md` (Infrastructure examples added to existing tools) - **Capability Overview**: See `README.md` (Updated to clarify existing infrastructure support) - **Validation Examples**: See test cases demonstrating infrastructure deployments ### User Journey Validation - [ ] **Primary workflow** documented end-to-end: Describe infrastructure need → Get recommendations → Deploy resources - [ ] **Secondary workflows** have complete coverage: Networking, storage, operator deployment - [ ] **Cross-references** between app deployment and infrastructure deployment docs work correctly - [ ] **Examples and commands** are testable via automated validation ## Implementation Requirements - [x] **Tool Description Updates**: Remove application-focused bias from MCP tool descriptions ✅ **COMPLETE** - [x] **Prompt Enhancement**: Add infrastructure examples to existing AI prompts ✅ **COMPLETE** - [~] **Documentation Clarity**: Update existing docs to highlight infrastructure deployment capability ⚠️ **MOVED TO PRD #45** - [~] **Validation Testing**: Verify system works with infrastructure use cases (databases, operators, networking) ⚠️ **MOVED TO PRD #45** ### Success Criteria - [x] **Resource coverage**: Support for major Kubernetes resource types beyond applications ✅ **COMPLETE - Architecture already generic** - [~] **Recommendation quality**: Accurate infrastructure recommendations based on cluster capabilities ⚠️ **REQUIRES PRDs #43/#44** - [~] **Deployment success**: Successful deployment of infrastructure resources with proper configuration ⚠️ **MOVED TO PRD #45** ## Implementation Progress ### Phase 1: Core Technical Updates [Status: ✅ COMPLETE] **Target**: Enable infrastructure deployment capabilities at the technical level **Technical Changes (COMPLETE):** - [x] **`src/tools/recommend.ts`**: Update MCP tool descriptions to remove application bias ✅ - [x] **`prompts/intent-validation.md`**: Add infrastructure examples alongside application examples ✅ - [x] **`prompts/resource-selection.md`**: Enhance with database, networking, operator examples ✅ **Moved to PRD #45 (Infrastructure Documentation):** - [~] **`docs/mcp-guide.md`**: Document infrastructure deployment examples using existing tools → **PRD #45** - [~] **`README.md`**: Clarify that infrastructure deployment is already supported → **PRD #45** **Validation Tasks (Moved to PRD #45):** - [~] Test PostgreSQL database deployment recommendation → **PRD #45** - [~] Test Redis cache deployment recommendation → **PRD #45** - [~] Test Ingress controller deployment recommendation → **PRD #45** - [~] Test monitoring operator deployment recommendation → **PRD #45** - [~] Document successful infrastructure deployment examples → **PRD #45** ## Work Log ### 2025-08-05: Strategic Completion - Documentation Work Moved to PRD #45 **Decision**: Complete PRD #19 with core technical improvements and move remaining documentation work to PRD #45. **Rationale**: During implementation, discovered that recommendation engine needs enhancement (PRDs #43/#44) before documentation can be accurate. Rather than document suboptimal experiences, moved user-facing work to PRD #45 which depends on enhanced recommendation engine. **Outcome**: - ✅ **Core technical work complete**: Tool descriptions and AI prompts enhanced for infrastructure - 📋 **Documentation work strategically moved**: PRD #45 will provide complete user experience once recommendations are optimized - 🎯 **Clear dependency path**: PRD #43 → PRD #44 → PRD #45 for complete infrastructure deployment experience **Owner**: Viktor Farcic **Status**: Strategic completion - foundational work done, user experience work properly sequenced ### 2025-08-04: Major Strategic Decision - Architectural Simplification **Decision**: After code analysis, determined the system is already architecturally generic and can handle infrastructure deployments. The issue is presentation/examples, not core functionality. **Impact**: Simplified implementation from building new systems to updating existing prompts and descriptions. **Evidence**: Core engine works with any Kubernetes resource type, discovery finds all resources, AI matching uses actual schemas. ### 2025-07-28: PRD Refactoring to Documentation-First Format **Completed Work**: Refactored PRD #19 to follow new documentation-first guidelines with comprehensive infrastructure deployment features. ## Decision Log ### Decision #1: Architectural Simplification (2025-08-04) **Decision**: Leverage existing generic architecture instead of building new core functionality **Rationale**: Code analysis revealed that dot-ai is already architecturally generic: - Core engine uses `kubectl explain` for ANY resource type - Discovery finds ALL cluster resources (standard + CRDs) - AI matching works against actual resource schemas, not predefined categories - Examples already include infrastructure: "database cluster", "monitoring stack", "load balancer" **Impact**: - **Scope**: Reduced from building new systems to updating existing presentation - **Timeline**: Significantly faster implementation - **Risk**: Lower risk since no architectural changes needed - **Implementation**: Simple prompt/description updates vs. complex 3-phase development **Owner**: Viktor Farcic **Status**: Approved --- ## Appendix ### Resource Types Already Supported (Architecture Analysis) **The system can already recommend and deploy these resource types:** - **Networking**: Ingress, Service, NetworkPolicy, EndpointSlice - **Storage**: PersistentVolumeClaim, StorageClass, Volume configurations - **Security**: RBAC roles, ServiceAccount, PodSecurityPolicy - **Configuration**: ConfigMap, Secret management patterns - **Operators**: Helm charts, Custom operators, CRD deployments - **Databases**: PostgreSQL operators, MongoDB, Redis, MySQL - **Monitoring**: Prometheus, Grafana, AlertManager operators - **Any Custom Resources**: Automatically discovered via `kubectl api-resources` **What's needed**: Update prompts and examples to communicate this existing capability clearly to users.