# Flowfish - Roadmap and Phase Planning

## 🎯 Overview

Development of the Flowfish platform is planned in three main phases. Each phase is designed to deliver value incrementally.

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## 📅 Phase Summary

| Phase | Duration | Milestones | Deliverable |
|-------|----------|------------|-------------|
| **Phase 1: MVP** | 0–3 months | M1, M2, M3 | Production-ready core platform |
| **Phase 2: Advanced** | 4–6 months | M4, M5 | Enterprise features |
| **Phase 3: AI/ML** | 7–9 months | M6, M7 | Advanced analytics |

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## 🚀 Phase 1: MVP (Minimum Viable Product)

**Target Duration**: 0–3 months  
**Status**: Planning  
**Goal**: Complete core platform infrastructure and core features

### Milestone 1: Foundation (Month 1)

**Sprint 1–2: Infrastructure Setup**

**Backend**:
- ✅ FastAPI project setup
- ✅ PostgreSQL schema implementation
- ✅ Database migrations (Alembic)
- ✅ Authentication (JWT)
- ✅ RBAC implementation
- ✅ API documentation (OpenAPI)

**Frontend**:
- ✅ React + TypeScript + Ant Design setup
- ✅ Layout components (Header, Sidebar, Content)
- ✅ Authentication flow (Login, OAuth)
- ✅ Route structure
- ✅ State management (Redux Toolkit)

**DevOps**:
- ✅ Docker containers (backend, frontend)
- ✅ Docker Compose for local development
- ✅ CI/CD pipeline (GitHub Actions)
- ✅ Kubernetes base manifests

**Deliverables**:
- ✅ Working login page
- ✅ Basic dashboard skeleton
- ✅ API health check endpoint
- ✅ Database schema deployed

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**Sprint 3–4: Cluster Management & Inspektor Gadget**

**Backend**:
- ✅ Kubernetes API client integration
- ✅ Cluster CRUD operations
- ✅ Namespace discovery
- ✅ Workload discovery (Pod, Deployment, Service, StatefulSet)
- ✅ Inspektor Gadget DaemonSet integration
- ✅ eBPF data collection pipeline

**Frontend**:
- ✅ Cluster management page
- ✅ Cluster selector component
- ✅ Namespace list view
- ✅ Workload explorer

**Testing**:
- ✅ Unit tests (backend)
- ✅ Integration tests (API)
- ✅ E2E tests (frontend)

**Deliverables**:
- ✅ Add/edit/delete clusters
- ✅ View discovered workloads
- ✅ Inspektor Gadget collecting data

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### Milestone 2: Core Features (Month 2)

**Sprint 5–6: Analysis Wizard & Communication Discovery**

**Backend**:
- ✅ Analysis wizard API (4-step workflow)
- ✅ Gadget module configuration
- ✅ Analysis execution engine
- ✅ Communication discovery logic
- ✅ ClickHouse integration
- ✅ Data enricher (K8s metadata)

**Frontend**:
- ✅ Analysis wizard (4 steps)
- ✅ Analysis list page
- ✅ Analysis detail page
- ✅ Communication list view

**Neo4j**:
- ✅ Graph schema creation
- ✅ Vertex/Edge insertion logic
- ✅ Basic graph queries

**Deliverables**:
- ✅ Create analysis via wizard
- ✅ Start/stop analysis
- ✅ View discovered communications
- ✅ Data flowing to databases

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**Sprint 7–8: Dependency Map Visualization**

**Backend**:
- ✅ Graph service (Neo4j queries)
- ✅ Graph data transformation (Node/Edge format)
- ✅ Filtering logic (namespace, workload type, risk)
- ✅ Real-time updates (WebSocket)

**Frontend**:
- ✅ Live Map page (Cytoscape.js integration)
- ✅ Graph rendering (nodes, edges, styling)
- ✅ Layout algorithms (hierarchical, force-directed)
- ✅ Interaction (click, hover, zoom)
- ✅ Detail panel (node/edge info)
- ✅ Filters (namespace, type, risk)

**Deliverables**:
- ✅ Interactive dependency map
- ✅ Real-time updates visible on graph
- ✅ Filtering and search working
- ✅ Export graph as PNG/JSON

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### Milestone 3: Polish & Testing (Month 3)

**Sprint 9–10: Dashboard & Refinement**

**Backend**:
- ✅ Dashboard metrics API
- ✅ Aggregation queries (ClickHouse)
- ✅ Performance optimization
- ✅ Caching (Redis)

**Frontend**:
- ✅ Overview Dashboard (metrics cards, charts)
- ✅ Application Inventory page
- ✅ Risk scoring visualization
- ✅ UI polish (responsive, dark mode)

**Documentation**:
- ✅ User guide
- ✅ API documentation
- ✅ Deployment guide
- ✅ Troubleshooting guide

**Deliverables**:
- ✅ Production-ready platform
- ✅ Comprehensive documentation
- ✅ Performance benchmarks met

**Phase 1 Success Criteria**:
- ✅ 1000+ pods handled
- ✅ Real-time graph updates <5s
- ✅ API response time p95 <500ms
- ✅ 4 user roles working
- ✅ OAuth SSO working
- ✅ Deployment on Kubernetes successful

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## 🌟 Phase 2: Advanced Features

**Target Duration**: 4–6 months  
**Status**: Planned  
**Goal**: Enterprise features and advanced analytics

### Milestone 4: Historical Analysis (Month 4)

**Sprint 11–12: Time Travel & Baseline**

**Backend**:
- ✅ Historical graph snapshots
- ✅ Time-range queries
- ✅ Baseline creation logic
- ✅ Baseline storage (PostgreSQL)
- ✅ Comparison engine

**Frontend**:
- ✅ Historical Map page
- ✅ Time slider component
- ✅ Playback mode
- ✅ Snapshot comparison view
- ✅ Baseline management page

**Deliverables**:
- ✅ View past dependency maps
- ✅ Compare snapshots
- ✅ Create traffic baselines

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**Sprint 13–14: Change Detection**

**Backend**:
- ✅ Change detection algorithm
- ✅ New/lost connection tracking
- ✅ Traffic spike detection
- ✅ Change event storage

**Frontend**:
- ✅ Change Detection page
- ✅ Change timeline visualization
- ✅ Change details panel
- ✅ Change filtering

**Deliverables**:
- ✅ Automatic change detection
- ✅ Change notifications
- ✅ Change review workflow

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### Milestone 5: AI & Multi-Cluster (Months 5–6)

**Sprint 15–16: LLM Integration & Anomaly Detection**

**Backend**:
- ✅ LLM service (OpenAI/Anthropic/Azure)
- ✅ Prompt engineering
- ✅ Anomaly scoring algorithm
- ✅ Anomaly storage
- ✅ Scheduled anomaly checks

**Frontend**:
- ✅ LLM configuration page
- ✅ Anomaly Detection page
- ✅ Anomaly detail view
- ✅ Anomaly workflow (assign, resolve)

**Deliverables**:
- ✅ AI-powered anomaly detection
- ✅ LLM analysis reports
- ✅ Anomaly alerting

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**Sprint 17–18: Import/Export & Multi-Cluster**

**Backend**:
- ✅ CSV export logic
- ✅ Graph JSON export
- ✅ Import parser (CSV, JSON)
- ✅ Import validation
- ✅ Multi-cluster management
- ✅ Cross-cluster queries

**Frontend**:
- ✅ Import/Export page
- ✅ Job progress tracking
- ✅ Multi-cluster selector
- ✅ Cross-cluster view

**Deliverables**:
- ✅ Data export (CSV, JSON)
- ✅ Data import with validation
- ✅ Multi-cluster dashboard
- ✅ Cross-cluster dependency view

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**Sprint 19–20: Webhooks & SIEM Integration**

**Backend**:
- ✅ Webhook engine
- ✅ Event filtering
- ✅ Delivery retry logic
- ✅ SIEM connectors (Splunk, Elastic, Sentinel)

**Frontend**:
- ✅ Webhook configuration page
- ✅ Webhook test tool
- ✅ Delivery logs

**Deliverables**:
- ✅ Webhook notifications working
- ✅ SIEM integration tested
- ✅ Alert templates

**Phase 2 Success Criteria**:
- ✅ Historical data retained 30+ days
- ✅ Change detection 95% accuracy
- ✅ LLM response <10 seconds
- ✅ Multi-cluster 5+ clusters
- ✅ Import/export 10MB+ files

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## 🔮 Phase 3: AI/ML & Enterprise

**Target Duration**: 7–9 months  
**Status**: Conceptual  
**Goal**: AI/ML and enterprise features

### Milestone 6: Policy & Change Simulation (Months 7–8)

**Sprint 21–22: What-If Analysis Engine**

**Backend**:
- ⏳ Policy parser (YAML)
- ⏳ Simulation engine
- ⏳ Impact calculator
- ⏳ Recommendation engine
- ⏳ Change simulation engine
- ⏳ Dependency impact analyzer
- ⏳ Risk scoring algorithm

**Frontend**:
- ⏳ Policy Simulator page
- ⏳ Policy editor (Monaco)
- ⏳ Simulation results view
- ⏳ Impact visualization
- ⏳ **Change Simulation page**
- ⏳ **CAP workflow interface**
- ⏳ **Approval dashboard**

**Deliverables**:
- ⏳ Network policy simulation
- ⏳ Impact analysis
- ⏳ What-if scenarios
- ⏳ **Change impact assessment**
- ⏳ **CAP workflow integration**

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**Sprint 23–24: CAP Integration & Change Management**

**Backend**:
- ⏳ Change Request API
- ⏳ Approval workflow engine
- ⏳ ServiceNow integration
- ⏳ Jira integration
- ⏳ Pre/post-change validation
- ⏳ Automated rollback triggers
- ⏳ Change history tracking

**Frontend**:
- ⏳ Change Request creation wizard
- ⏳ Impact analysis dashboard
- ⏳ Approval workflow UI
- ⏳ Change history viewer
- ⏳ Analytics dashboard

**Integrations**:
- ⏳ ServiceNow connector
- ⏳ Jira connector
- ⏳ PagerDuty integration
- ⏳ Slack/Teams notifications

**Deliverables**:
- ⏳ **Full CAP workflow**
- ⏳ **Change approval automation**
- ⏳ **Impact assessment reports**
- ⏳ **Integration with enterprise tools**
- ⏳ **Automated rollback capability**

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**Sprint 25–26: Universal Ingestion & Governance**

**Backend**:
- ⏳ Prometheus metrics collector
- ⏳ Service mesh telemetry integration (Istio, Linkerd)
- ⏳ APM trace correlation (Jaeger, Zipkin)
- ⏳ Log correlation engine
- ⏳ CI/CD event collectors (GitLab, Jenkins, ArgoCD)
- ⏳ Provenance tracking system
- ⏳ Admission controller webhook
- ⏳ Policy-as-code engine
- ⏳ CI/CD plugins (GitHub Actions, GitLab CI, Jenkins)

**Frontend**:
- ⏳ Data source configuration page
- ⏳ Provenance viewer
- ⏳ Policy management UI
- ⏳ CI/CD integration dashboard

**Deliverables**:
- ⏳ Multi-source data ingestion working
- ⏳ Dependency provenance tracking
- ⏳ Admission controller deployed
- ⏳ CI/CD plugins for 3+ platforms

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**Sprint 27–28: DR Assessment & Predictive Analytics**

**Backend**:
- ⏳ DR posture scanner
- ⏳ RPO/RTO calculator
- ⏳ Backup status checker (Velero, Stash)
- ⏳ Replication lag monitor
- ⏳ ML model training pipeline
- ⏳ Traffic forecasting model
- ⏳ Capacity planning algorithm

**Frontend**:
- ⏳ DR Posture Dashboard
- ⏳ Stateful workload inventory
- ⏳ Backup compliance view

**Deliverables**:
- ⏳ DR posture assessment for 100+ workloads
- ⏳ RPO/RTO compliance reporting
- ⏳ Traffic predictions
- ⏳ Capacity recommendations

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### Milestone 7: AI & Enterprise Features (Month 9)

**Sprint 29–30: Natural Language & Explainable AI**

**Backend**:
- ⏳ Natural language query parser
- ⏳ Intent recognition (90%+ accuracy)
- ⏳ Query-to-SQL/GQL translator
- ⏳ Evidence collection engine
- ⏳ Confidence scoring algorithm
- ⏳ Provenance linker
- ⏳ Interactive debugging assistant

**Frontend**:
- ⏳ Natural language search bar
- ⏳ Conversational UI
- ⏳ Evidence viewer
- ⏳ AI explanation panel
- ⏳ Interactive troubleshooting wizard

**Deliverables**:
- ⏳ Natural language queries working
- ⏳ 90%+ intent recognition accuracy
- ⏳ Grounded AI responses with evidence
- ⏳ AI-assisted troubleshooting

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**Sprint 31–32: Advanced Features & Polish**

**Backend**:
- ⏳ Custom dashboard builder API
- ⏳ Report generation (PDF)
- ⏳ Compliance scanning
- ⏳ Auto-remediation engine

**Frontend**:
- ⏳ Custom dashboard builder (drag & drop)
- ⏳ Report scheduler
- ⏳ Compliance dashboard
- ⏳ Remediation playbooks

**Deliverables**:
- ⏳ Custom dashboards
- ⏳ Automated reports
- ⏳ Compliance reports (PCI-DSS, HIPAA, SOC 2)
- ⏳ Auto-remediation playbooks

**Phase 3 Success Criteria**:
- ⏳ What-if simulation <30s
- ⏳ **Change simulation <20s**
- ⏳ Prediction accuracy >80%
- ⏳ **Change approval automation working**
- ⏳ **CAP integration with ServiceNow/Jira**
- ⏳ Custom dashboard builder working
- ⏳ Compliance reports generated

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## 📊 Sprint Structure

### Typical 2-Week Sprint

**Week 1**:
- Day 1–2: Sprint planning, task breakdown
- Day 3–5: Development (backend + frontend parallel)
- Day 6–8: Integration & testing
- Day 9–10: Code review, refinement

**Week 2**:
- Day 1–3: Bug fixes, polish
- Day 4–5: Documentation
- Day 6–7: QA testing
- Day 8: Demo & retrospective
- Day 9–10: Sprint planning (next sprint)

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## 👥 Team Structure

### Recommended Team (Phase 1)

| Role | Count | Responsibility |
|------|-------|------------------|
| **Product Owner** | 1 | Backlog, prioritization |
| **Scrum Master** | 1 | Sprint facilitation |
| **Backend Developer** | 2 | Python, FastAPI, databases |
| **Frontend Developer** | 2 | React, TypeScript, UI/UX |
| **DevOps Engineer** | 1 | K8s, CI/CD, infrastructure |
| **QA Engineer** | 1 | Testing, automation |
| **UI/UX Designer** | 0.5 (part-time) | UI design, wireframes |

**Total**: 7.5 FTE

### Expansion in Phase 2

- +1 Backend Developer (LLM, ML)
- +1 Data Engineer (ClickHouse optimization)
- +1 Security Engineer (Penetration testing)

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## 🎯 Key Performance Indicators (KPIs)

### Development KPIs

| KPI | Target |
|-----|--------|
| Sprint Velocity | 40–50 story points/sprint |
| Code Coverage | >80% |
| Bug Escape Rate | <5% |
| API Response Time | p95 < 500ms |
| Frontend Load Time | <3 seconds |

### Product KPIs (Post-Launch)

| KPI | Target (6 months) |
|-----|------------------|
| Active Users | 100+ |
| Clusters Managed | 50+ |
| Daily API Calls | 1M+ |
| Anomalies Detected | 1000+ |
| Customer Satisfaction | NPS > 50 |

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## 🚧 Risks & Mitigation

### Technical Risks

| Risk | Impact | Probability | Mitigation |
|------|--------|-------------|------------|
| Inspektor Gadget performance issues | High | Medium | Early POC, load testing |
| Neo4j scalability limits | High | Low | Benchmark, alternative (Neo4j) |
| LLM API cost explosion | Medium | Medium | Rate limiting, caching |
| Kubernetes version compatibility | Medium | High | Support 3 latest versions |

### Project Risks

| Risk | Impact | Probability | Mitigation |
|------|--------|-------------|------------|
| Scope creep | High | High | Strict backlog prioritization |
| Team turnover | High | Medium | Knowledge sharing, documentation |
| Dependency delays | Medium | Medium | Buffer time in planning |
| Budget overrun | High | Low | Bi-weekly budget review |

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## 📅 Release Schedule

### Alpha Release (End of Phase 1 - Month 3)
- Internal testing
- Limited feature set
- Kubernetes clusters only

### Beta Release (End of Phase 2 - Month 6)
- Select customer testing
- Full feature set (Phase 1 + 2)
- OpenShift support added

### GA (General Availability) Release (End of Phase 3 - Month 9)
- Public release
- All features complete
- Production-ready
- Enterprise support

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## 🔄 Continuous Improvement

### Post-GA (Month 10+)

**Maintenance & Support**:
- Bug fixes (P0/P1: 24h, P2: 1 week, P3/P4: next sprint)
- Security patches (immediate)
- Dependency updates (monthly)

**Feature Enhancements**:
- Community feedback incorporation
- New gadget modules
- New LLM providers
- Performance improvements

**Innovation**:
- AI/ML model improvements
- New visualization types
- Advanced analytics
- Integration with more tools

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**Version**: 1.0.0  
**Last Updated**: January 2025  
**Status**: Detailed Roadmap