ENGINEERING ROADMAP - SPRINT PLANNING

TECHNICAL ARCHITECTURE EVOLUTION

NOW (Current Sprint - Next 3 months):

1. Auth Refactor (Estimated: 8-10 weeks) - CRITICAL FOUNDATION

Technical Scope:

• Refactor authentication layer to support modern OAuth 2.0/OIDC standards
• Extract auth logic from monolith into dedicated service
• Implement JWT token management with refresh token rotation
• Add support for multi-tenancy and SSO preparation
• Database schema updates for session management and security policies

Dependencies: Blocks GraphQL migration and any SSO features
Team: Backend team (3 engineers full-time)
Risk Level: HIGH - touches all authentication flows, requires extensive security testing
Rollout Strategy: Feature flags per endpoint, gradual migration with parallel auth systems during transition
Testing Requirements: Security audit, penetration testing, backwards compatibility validation

Technical Debt Context:

• Current auth system has grown organically over 2+ years
• Eliminating 6 known security vulnerabilities in legacy auth code
• Will reduce auth-related bugs by ~70% based on similar migrations

2. GraphQL Migration (Estimated: 10-12 weeks) - ARCHITECTURAL SHIFT

Technical Scope:

• Migrate REST API endpoints to GraphQL for improved query efficiency
• Implement Apollo Server or equivalent GraphQL runtime
• Design schema with mobile-first principles (minimize over-fetching)
• Add DataLoader for N+1 query prevention
• Implement subscriptions for real-time features
• Maintain REST API backward compatibility layer for existing clients

Dependencies: Requires completed auth refactor (uses new auth service)
Team: Backend team (4 engineers) + 1 frontend engineer for client integration
Risk Level: HIGH - fundamental API paradigm shift, extensive client updates required
Rollout Strategy: Dual-run both APIs in parallel for 8 weeks, gradual client migration per endpoint

Performance Impact:

• Expected 40-60% reduction in API payload sizes
• Reduces client-side API calls by ~50% (batch queries)
• Mobile app battery consumption should improve significantly

Migration Path:

• Week 1-3: GraphQL server setup, auth integration, core schema design
• Week 4-6: Migrate critical read endpoints, performance testing
• Week 7-9: Migrate write operations, add subscriptions
• Week 10-12: Client migration, load testing, documentation

SEQUENCING & CRITICAL PATH:

Week 1-4:   Auth Refactor Phase 1 (extract auth service, JWT implementation)
Week 5-8:   Auth Refactor Phase 2 (multi-tenancy, SSO prep, security hardening)
Week 9-10:  Auth Refactor Phase 3 (cleanup, migration completion, security audit)
Week 11-13: GraphQL Phase 1 (server setup, auth integration, schema design)
Week 14-17: GraphQL Phase 2 (endpoint migration, testing)
Week 18-22: GraphQL Phase 3 (client migration, performance optimization)

Critical path: Auth Refactor MUST complete before GraphQL work begins.
Any delay in auth refactor directly delays entire GraphQL timeline.

Parallel Work Opportunities:

• Weeks 1-10: Documentation updates can happen in parallel (0.5 engineer)
• Week 5+: Begin GraphQL schema design discussions (architecture review, no implementation)

NEXT (Following Sprint - 3-6 months):

1. Mobile App Launch (iOS + Android) (Estimated: 12-16 weeks)

• iOS: Swift/SwiftUI native application
• Android: Kotlin + Jetpack Compose
• Shared backend GraphQL API (completed in NOW phase)
• Offline-first architecture with optimistic updates
• Push notifications via Firebase Cloud Messaging

Dependencies:

• HARD BLOCKER: Requires completed GraphQL API from NOW phase
• SOFT DEPENDENCY: Benefits from auth refactor for smooth SSO experience

Team: Mobile team (2 iOS engineers, 2 Android engineers) + 1 backend engineer for API support
Risk Level: MEDIUM - new platform expertise, learning curve on team

2. Analytics Dashboard (Estimated: 8-10 weeks)

• Data warehouse integration (Snowflake, BigQuery, or Redshift)
• ETL pipeline for historical data ingestion
• Real-time event streaming (Kafka or AWS Kinesis)
• Custom visualization library or Recharts/D3.js integration

Dependencies: Minimal dependency on NOW phase (can use existing REST API)
Team: Full-stack team (2 backend, 2 frontend engineers) + data engineer (0.5 FTE)
Risk Level: MEDIUM - data pipeline complexity, performance at scale

LATER (6+ months):

1. AI Features (Estimated: TBD - depends on scope)

Potential Technical Scope:

• ML model integration for predictive analytics
• LLM integration for natural language queries
• AI-powered recommendations or insights
• Model hosting infrastructure (AWS SageMaker, GCP Vertex AI, or self-hosted)

Dependencies:

• Requires analytics infrastructure from NEXT phase
• May require data science team expansion
• Needs product definition before accurate estimation

Risk Level: HIGH - unclear requirements, ML infrastructure complexity

RISK ASSESSMENT:

HIGH-RISK ITEMS:

1. Auth Refactor (Risk Score: 8/10)

Risks:

• Security regression during migration (HIGH impact)
• Breaking existing integrations or client sessions (MEDIUM impact)
• Underestimating complexity of legacy auth code (MEDIUM impact)
• Performance degradation if new service introduces latency (LOW impact)

Mitigation:

• Security audit required before production rollout
• Maintain parallel auth systems during transition period
• Comprehensive integration test suite (aim for 95%+ coverage)
• Load testing with 2x production traffic before cutover
• Rollback plan: Feature flags allow instant revert per endpoint

2. GraphQL Migration (Risk Score: 7/10)

Risks:

• Breaking changes for existing API clients (HIGH impact)
• N+1 query problems if DataLoader not implemented correctly (MEDIUM impact)
• Schema design mistakes require breaking changes (MEDIUM impact)

Mitigation:

• Maintain REST compatibility layer for minimum 6 months
• Extensive load testing before migration (target: 10x current peak load)
• Schema versioning strategy from day one
• Query complexity limiting and depth limiting from start

ROLLBACK PLANS:

Auth Refactor Rollback:

• Feature flags per authentication method (email/password, OAuth, API keys)
• Can revert to legacy auth system per user cohort
• Parallel systems run for 4 weeks minimum before decommissioning legacy
• Rollback window: Can revert instantly for 6 weeks post-migration

GraphQL Rollback:

• REST API remains available indefinitely (no forced migration)
• Clients can toggle between REST and GraphQL via config flag
• GraphQL can be disabled per-endpoint if performance issues arise
• Rollback window: Can revert any client to REST at any time

OPEN QUESTIONS FOR SPRINT PLANNING:

Technical Questions:

1. Do we have access to a security expert for auth refactor review, or need to hire consultant?
2. What’s our target API response time SLA for GraphQL? (Recommend p95 < 200ms)
3. For mobile: React Native vs native? Need decision by Week 15 to stay on schedule.
4. Data warehouse choice for analytics: Snowflake, BigQuery, or Redshift?

Resource Questions:
5. Can we sustain 3-4 backend engineers on this work for 22 weeks without interruptions?
6. Should we hire additional backend capacity NOW to derisk timeline?
7. Do we have mobile engineers on staff or need to hire before NEXT phase?

Scope Questions:
8. Is there optional scope in GraphQL migration we can defer to reduce risk?
9. For AI features: What’s the actual scope? Need detailed spec before estimating.
10. Should we descope Android and launch iOS-only first to reduce NEXT phase risk?