flowfish/docs/07-roadmap.md

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