Figma Frontend System Design

Comprehensive high-level architecture design for Figma's collaborative design platform frontend with real-time synchronization and performance optimization strategies

PublishedOctober 25, 2025
Length10,082 words
Reading time51 min read

Frontend HLD

This document presents a scalable frontend architecture for Figma's collaborative design platform, focusing on real-time synchronization, efficient rendering pipelines, and cross-platform compatibility across web and desktop environments.

1. Executive Summary

Clarifying questions

What device targets and form factors will the Figma frontend support? (Mobile-first, desktop-only, or responsive design across all devices?)
What are the expected network conditions for users? (e.g., 3G, 4G, fiber, or enterprise-grade connectivity?)
What authentication and authorization requirements exist? (OAuth2, SAML, or custom auth flows?)
Are internationalization and localization needs a priority? (Support for RTL languages, multiple timezones, etc.)
Is real-time collaboration a core requirement (e.g., live editing, comments, versioning)?
What are the SEO and content discoverability goals for public Figma designs?
How many teams or micro-frontend boundaries are expected in the system? (e.g., design tools, community features, admin panel)

Problem being solved

The Figma frontend needs to provide a performant, scalable, and highly interactive design collaboration platform that allows users to create, edit, and share vector graphics in real-time. The system must support a wide variety of design tools, collaborative features, and cross-platform compatibility while maintaining low latency and high availability.

Back-of-envelope estimates

Metric	Value
Avg. JS Bundle Size (per route)	150–250 KB
Avg. Image Size (per route)	50–100 KB
Total Page Weight (per route)	200–350 KB
DAU	1M (assumed)
Avg. Page Weight × DAU	~200–350 MB/day
CDN Bandwidth (daily)	200–350 MB
Cache Hit Rate	85% (assumed)
Origin Request Rate	15%
CDN PoPs Needed	20 (for global latency < 100ms)

Key architectural decisions summary

Rendering Strategy: Hybrid approach using SSR for initial page load and CSR for interactivity, leveraging Next.js 13+ App Router.
State Management: React Query for server state, Zustand for client state, with global store for collaborative features.
Performance: Critical rendering path optimization, lazy loading, and preloading of key assets.
Real-time Collaboration: WebSocket-based real-time sync with polling fallback for degraded network conditions.
Security: Content Security Policy (CSP), token-based authentication with secure cookies, and strict CORS configuration.
Scalability: CDN-first architecture with edge rendering capabilities and multi-region support for low latency.
Internationalization: URL-based locale routing with lazy-loaded translation bundles.
Testing & Reliability: Comprehensive test pyramid with E2E and accessibility testing integrated into CI.
Deployment: Canary deployment strategy with feature flags for progressive rollouts and rollback capability.

graph TD
    A[User] --> B[CDN Edge]
    B --> C[Edge Functions / SSR]
    C --> D[Next.js App Server]
    D --> E[API Gateway]
    E --> F[Backend Services]
    E --> G[Real-time Sync]
    G --> H[WebSocket Server]
    F --> I[Database / Storage]
    D --> J[Component Library]
    J --> K[Design System]

2. System Goals & Non-Functional Requirements

Performance Targets

Largest Contentful Paint (LCP): < 2.5s for 75% of users
First Input Delay (FID): < 100ms for 90% of users
Time to First Byte (TTFB): < 500ms for 95% of requests
First Contentful Paint (FCP): < 1s for 90% of users
Cumulative Layout Shift (CLS): < 0.1 for 90% of users

Availability and Reliability Targets

SLA: 99.9% uptime (43.2 minutes of downtime/month max)
SLO: 95% of page loads complete within performance targets
Error Budget: 5% error budget with automatic rollback on exceeding threshold
Graceful Degradation: Critical features remain functional during partial outages

Scalability Requirements

Support 10M+ monthly active users (MAU) with concurrent sessions up to 500K
Handle 100K+ requests per second during peak hours
Support horizontal scaling of frontend services across multiple regions
Maintain consistent performance as user base grows

Security and Compliance Requirements

CSP: Enforce strict Content Security Policy to prevent XSS
SSO Integration: Support OAuth2/OIDC for enterprise authentication
Data Protection: GDPR/CCPA compliance for user data handling and storage
Secure by Design: All API calls must be authenticated and authorized
Vulnerability Scanning: Automated dependency scanning in CI pipeline

Internationalization Requirements

Support 20+ languages with RTL layout support for Arabic, Hebrew, Persian
Dynamic locale switching without page reload
Translation key structure and message catalog management
Date, time, number, and currency formatting using Intl API

Accessibility Requirements (WCAG Level)

WCAG 2.1 AA Compliance: Full keyboard navigation, screen reader support
Focus Management: Proper focus order and visual indicators for interactive elements
Contrast Ratios: Minimum 4.5:1 for text and UI elements
Alternative Text: All images must have descriptive alt text
ARIA Labels: Proper ARIA attributes for dynamic content and controls

Additional Non-Functional Requirements

Offline Support: Service worker-based offline capability for core features
Progressive Enhancement: Core functionality available without JavaScript
Cross-Browser Compatibility: Support for Chrome 80+, Firefox 70+, Safari 13+
Mobile Responsiveness: Optimized for mobile-first experience with touch targets >48px
Build Performance: Bundle size under 500KB for initial load (JS + CSS + images)

3. Architecture Overview

graph TD
    A[User] --> B[CDN/Edge]
    B --> C[Next.js SSR/SSG]
    C --> D[API Gateway]
    D --> E[Microservices]
    D --> F[Static Assets CDN]
    C --> G[Component Library]
    C --> H[Design System]
    C --> I[State Management]
    C --> J[Real-time Layer]

Rendering Strategy Selection

Primary Strategy: Server-Side Rendering (SSR) with Static Site Generation (SSG) hybrid

The system will utilize a hybrid rendering approach to optimize for both performance and SEO:

SSG for static content (documentation pages, marketing pages, blog posts) - pre-rendered at build time
SSR for dynamic content (user dashboards, personalized views) - rendered on each request
Incremental Static Regeneration (ISR) for content that needs periodic updates but isn't real-time

Justification:

SEO Optimization: SSG/SSR ensures content is immediately available to search engines
Performance: Pre-rendered pages deliver content faster than CSR
Scalability: Static assets can be efficiently cached at CDN edge locations
User Experience: SSR provides instant page loads for personalized content

Framework Selection

Primary Framework: Next.js 14+ with App Router

Justification:

Built-in SSR/SSG Support: Native support for all rendering strategies with minimal configuration
TypeScript Integration: Strong typing reduces runtime errors and improves developer experience
Image Optimization: Built-in image component with automatic optimization and lazy loading
API Routes: First-class support for BFF pattern with serverless functions
Edge Network Integration: Native support for Vercel Edge Functions and middleware
Component Architecture: App Router provides better component composition and nested layouts
Ecosystem Maturity: Large ecosystem of plugins, middleware, and community support

Alternative Considered: Astro

Pros: Excellent SSG capabilities, islands architecture
Cons: Limited SSR support, smaller ecosystem for complex applications

Architecture Components

Client-Side Application Layer: React components with proper state management
Server-Side Rendering Layer: Next.js server-side rendering with edge capabilities
API Communication Layer: GraphQL/REST client with caching and error handling
Static Asset Layer: CDN-optimized image delivery and asset management
Design System Integration: Component library with theme support and accessibility
Real-time Communication Layer: WebSocket/SSE integration for live updates

Technology Stack Summary

Framework: Next.js 14+ (App Router)
Rendering: Hybrid SSR/SSG with ISR
State Management: React Query + Zustand
API Layer: GraphQL (with REST fallback) via Apollo Client
Deployment: Vercel (SSR/SSG) with CDN edge functions
Component Library: Custom design system with Storybook documentation

Scalability Considerations

The architecture supports horizontal scaling through:

Edge Functions: Serverless compute at CDN edge locations
Static Asset Distribution: Global CDN distribution for assets
Microservices Integration: Decoupled backend services for content delivery
Caching Strategy: Multi-tier caching (client, edge, origin)
Build-time Optimization: Pre-rendering reduces runtime load

This architecture balances performance, developer experience, and scalability requirements while maintaining flexibility for future evolution.

4. State Management Architecture

Global vs. local state philosophy

The frontend will adopt a "state stratification" approach where:

Global state: Managed at the application level for cross-cutting concerns like user session, theme preferences, and feature flags
Component-local state: Managed within individual components for UI-specific concerns like form inputs, dropdown open states, and animation triggers
Route-level state: Managed for page-specific data that should persist across component re-renders but not globally (e.g., active tab, filter values)
Server state: Managed through dedicated data fetching and caching layers

Server state management layer

Primary choice: React Query (TanStack Query)

Rationale: Excellent built-in caching, automatic refetching, background updates, and SSR support
Implementation:
- QueryClient configured with default staleTime (5 minutes) and cacheTime (10 minutes)
- Custom error boundary integration for graceful error handling
- Query invalidation on mutations and user actions
Server-side considerations:
- Server-side rendering with proper hydration using React Query's SSR capabilities
- Data prefetching for critical routes during SSR

Client state management layer

Primary choice: Zustand

Rationale:
- Lightweight, minimal API surface
- Excellent for complex state logic that doesn't require full Redux ecosystem
- Easy to test and debug
Implementation:
- Store structure organized by domain (user, theme, notifications)
- Middleware for logging and persistence
- Integration with React's Context API for component access

Real-time state synchronization strategy

Primary choice: WebSockets with fallback to polling

WebSocket:
- Used for real-time updates (notifications, live comments, collaborative editing)
- Connection managed through Zustand store with automatic reconnection logic
Polling:
- Fallback for environments where WebSockets are blocked or unavailable
- Implemented with exponential backoff strategy (1s, 2s, 4s, 8s max)
Implementation:
- WebSocket connection established on app mount
- Reconnection logic with exponential backoff and max retry limits
- Fallback polling when WebSocket fails (5s interval for low-priority updates)

State persistence strategy

Primary choice: localStorage with IndexedDB fallback

localStorage:
- For small, frequently accessed state (user preferences, dark mode toggle)
- Session storage for temporary UI states (active modals, form progress)
IndexedDB:
- For larger datasets that need to persist across sessions (user drafts, cached API responses)
- Used for offline-first capabilities and PWA support
Implementation:
- State sync between localStorage and IndexedDB using a unified persistence layer
- Versioned storage to handle schema migrations
- Background sync for IndexedDB updates when online

State synchronization patterns

Consistent state across tabs:
- Use localStorage with storage event listeners to sync between browser tabs
- Implement a "last write wins" strategy for conflicting updates
Cross-session persistence:
- Critical user preferences and settings stored in localStorage with automatic backup to IndexedDB
Optimistic updates:
- Applied in Zustand stores with rollback capability on server errors
- UI updates immediately, with server validation and correction if needed

State management integration points

Component layer:
- React Query hooks for server data, Zustand stores for client state
- Custom React hooks that abstract complex state logic (e.g., useUserPreferences, useTheme)
API layer:
- Server state invalidation triggers client state updates
- WebSocket events update Zustand stores directly
Persistence layer:
- Automatic state serialization/deserialization on app load and unload
- Background sync for IndexedDB persistence

5. API Communication Layer

API Gateway Pattern

The frontend will utilize a BFF (Backend for Frontend) pattern rather than direct API gateway integration. This approach provides:

Abstraction layer between frontend and backend services
Optimized responses tailored to specific frontend needs
Security isolation from direct backend exposure
Aggregation of multiple backend calls into single frontend requests

GraphQL vs. REST vs. gRPC Selection

GraphQL chosen as primary API communication method with REST fallback for compatibility:

GraphQL advantages:
- Client-controlled data fetching (reduces over-fetching)
- Strong typing with schema validation
- Real-time subscriptions support
- Single endpoint for all operations
- IDE tooling and introspection capabilities
REST as fallback:
- Legacy system compatibility
- Simpler client implementation for basic use cases
- Better caching support with HTTP headers
gRPC rejected due to:
- Higher complexity in frontend implementation
- Less flexible for UI-driven data requirements
- Not well-suited for browser environments

BFF Design

BFF pattern with custom GraphQL API gateway:

[Frontend] --> [BFF Layer] --> [Backend Services]

Key BFF responsibilities:

Data aggregation from multiple backend services
Query optimization and batching
Authentication/authorization handling
Caching layer for frequently accessed data
Error handling and transformation
Rate limiting and request validation

Real-time Communication

WebSocket-based real-time updates with fallback:

Primary: WebSocket connections for:
- Live design collaboration
- Real-time preview updates
- Instant notifications and alerts
Fallback: Server-Sent Events (SSE) for:
- Read-only real-time data streams
- Browser compatibility in constrained environments

API Versioning Strategy

Versioned GraphQL schema with backward compatibility:

Schema versioning: v1, v2 etc. in URL path
Semantic versioning: Major.minor.patch for breaking/non-breaking changes
Automatic migration: Client-side schema compatibility layer
Graceful degradation: Old clients continue to function with older schemas

Rate Limiting and Throttling

Client-side rate limiting implementation:

Request queueing:
- Priority-based queuing for critical operations
- Retry logic with exponential backoff
- Request deduplication to prevent redundant calls
Throttling thresholds:
- 100 requests/minute for non-critical operations
- 500 requests/minute for authenticated users
- 1000 requests/minute for premium users
Smart caching:
- HTTP cache headers with appropriate TTLs
- Local storage for frequently accessed data
- Stale-while-revalidate strategy for better UX

Error Handling Strategy

Comprehensive error handling across all API interactions:

Network errors: Retry logic with exponential backoff
API errors: User-friendly error messages with actionable guidance
Rate limiting: Graceful degradation and user notifications
Validation errors: Inline form validation with clear error messages
Timeout handling: Progressive loading states and timeout warnings

Security Considerations

API communication security:

HTTPS enforcement: All API calls must use HTTPS
Request signing: For sensitive operations (design publishing, collaboration)
Input sanitization: All API inputs validated and sanitized
CORS configuration: Strict CORS policies for frontend origins
Authentication tokens: JWT with proper expiration and refresh mechanisms

Performance Optimization

Optimized API communication patterns:

Batching: Multiple related requests batched into single HTTP calls
Lazy loading: Non-critical data loaded on demand
Preloading: Critical data preloaded during app initialization
Compression: Gzip/Brotli compression for API responses
Caching strategies:
- Memory cache for frequently accessed data
- Local storage for offline access to recent changes
- CDN caching for static resources and public data

Data Flow Architecture

[Frontend] 
   ↓ (GraphQL + REST)
[BFF Layer]
   ↓ (Service Aggregation)
[Backend Services]

This layered approach ensures that frontend developers can focus on UI implementation while the BFF layer handles complex data orchestration, security, and performance optimization. The GraphQL-first strategy provides flexibility for evolving UI requirements while maintaining strong type safety and developer experience.

6. Performance Architecture

Performance Budget by Page / Route

Route	JS Bundle (KB)	Images (KB)	Total (KB)	LCP Target (ms)	INP Target (ms)
Home	80	120	200	2500	200
Dashboard	150	200	350	2500	200
Editor	250	300	550	3000	200
Profile	60	80	140	2000	200
Settings	40	20	60	1500	200

Critical Rendering Path Strategy

Core Rendering Pipeline:

HTML Skeleton - First 1KB of HTML delivered immediately (critical CSS inlined)
Critical JS - Core bundle with essential UI components (50KB max)
Non-Critical JS - Async loading of feature bundles
Resource Hints - Preload key fonts, critical images, and API endpoints

Resource Prioritization Strategy

Preload/Prefetch Configuration:

Critical fonts (woff2) with preload in HTML head
First-view images with prefetch for next route
API endpoints with preconnect to reduce DNS lookup time
Third-party scripts with prefetch for non-critical features

Resource Loading Strategy:

// Priority-based resource loading
const resourceLoader = {
  critical: ['core.css', 'core.js'],
  highPriority: ['fonts.woff2', 'hero-image.jpg'],
  mediumPriority: ['dashboard.js', 'editor.js'],
  lowPriority: ['analytics.js', 'social-share.js']
};

Third-Party Script Impact Mitigation

Script Isolation Strategy:

Lazy Loading - Third-party scripts loaded only when needed
Error Boundaries - Fallbacks for failed third-party loads
Resource Budgeting - Maximum 200KB per third-party script
Performance Monitoring - Track impact of each third-party on LCP/INP

Font Loading Strategy

Font Optimization:

System Fonts - Default fallbacks for all text elements
Font Display Strategy: swap for body text, fallback for headings
Preload Critical Fonts: Only essential font weights (400, 700)
Font Subsetting: Remove unused characters from font files

Image CDN and Optimization Pipeline

Image Optimization Strategy:

Responsive Images - srcset with multiple sizes (320px, 768px, 1024px, 1920px)
Format Optimization - WebP for modern browsers, JPEG fallback
Compression - 85% quality for JPEGs, lossless for PNGs
CDN Integration - Cloudflare Image Optimization with automatic resizing

graph TD
  A[Image Request] --> B[CDN Edge Cache]
  B --> C[Image Processing]
  C --> D[Format Detection]
  D --> E[Size Optimization]
  E --> F[Delivery to Client]

Image Loading Pattern:

// Lazy image loading with proper fallbacks
const ImageLoader = ({ src, alt, sizes }) => {
  return (
    <img 
      src={src}
      alt={alt}
      sizes={sizes}
      loading="lazy"
      decoding="async"
      fetchPriority="low"
    />
  );
};

Performance Budget Constraints:

JS Bundle Size: < 250KB for core routes (excluding vendor libraries)
Image Budget: < 300KB per page for main content images
API Response Time: < 500ms for critical data endpoints
First Contentful Paint: < 1.5s for all routes

Resource Loading Priorities:

Critical Resources: Core JS, CSS, essential images
High Priority: Feature-specific bundles, secondary images
Medium Priority: Analytics, social sharing, non-critical features
Low Priority: Third-party widgets, promotional content

Performance Monitoring:

Real User Monitoring (RUM) integration for actual performance data
Web Vitals tracking with automated alerting thresholds
CI pipeline integration for performance regression detection
Build-time bundle analysis and size tracking

7. Content Delivery & Caching Strategy

CDN Selection and Configuration

For global content delivery, we'll select Cloudflare as our primary CDN provider due to its:

Global edge network with 300+ PoPs
Built-in DDoS protection and security features
Advanced caching capabilities with custom TTLs
Integration with Workers for edge computing

CDN configuration will include:

Origin Shield to reduce origin load
Automatic TLS with custom SSL certificates
Rate Limiting at edge to prevent abuse
WAF (Web Application Firewall) for security

Edge Caching Strategy

Cacheable Content:

Static assets (JS bundles, CSS, images, fonts) - 1 year TTL
Generated pages (SSG/ISR) - 1 hour TTL
API responses with stable data - 5 minutes TTL
User-specific content (after auth) - 1 minute TTL

Cache Invalidation Triggers:

Build/deploy events → immediate cache invalidation
Content changes via CMS → targeted cache purging
User actions (profile updates) → session-based cache invalidation
Scheduled content refreshes → background cache warming

Static Asset Versioning and Cache Busting

We'll implement content-based hashing for all static assets:

JS/CSS bundles: app.abc123.js (hash appended to filename)
Images: hero-image.efg456.png
Fonts: inter-v12.abc123.woff2

Versioning strategy:

Major version bumps for breaking changes (e.g., v2.0.0)
Minor version bumps for feature additions (e.g., v1.2.0)
Patch versions for bug fixes (e.g., v1.1.1)

Service Worker Strategy

PWA Implementation:

Service worker registration with defer loading
Cache-first strategy for static assets, network-fallback for API calls
Background sync for offline form submissions
Push notification support for user engagement

Offline Support:

Offline fallback pages for critical routes
Progressive enhancement for core functionality
Cache warming during app initialization

Edge Rendering / Edge Functions Strategy

Edge Function Usage:

Authentication checks: User session validation at edge
Content personalization: A/B testing, user preference rendering
Request routing: URL rewriting and redirect handling
Analytics aggregation: Real-time event tracking with batching

Implementation:

Cloudflare Workers for serverless edge functions
Cache warm-up jobs running every 15 minutes for high-traffic pages
Error handling with fallback to origin servers

Performance Impact:

Expected 20-30ms reduction in TTFB for authenticated users
50% reduction in origin server requests for static content
15% improvement in LCP for users on edge locations

Regional Caching Considerations

For multi-region deployment:

Primary region: US-East (lowest latency for North American users)
Secondary regions: EU-West and Asia-Pacific for global coverage
Traffic routing: Anycast DNS with automatic failover to nearest PoP
Cache consistency: Synchronized cache invalidation across regions

Latency Targets:

50ms TTFB for 95% of users
200ms LCP for 90% of users
150ms FCP for 95% of users

Cache Hit Rate Optimization

Target Metrics:

Overall cache hit rate: 92% (target)
Static asset hit rate: 98%
API cache hit rate: 85%
Origin request rate: < 2% of total requests

Optimization Techniques:

Cache warming: Preload popular routes during low-traffic hours
Cache preheating: Trigger cache refresh for content updates
Edge compute: Reduce origin load through serverless edge processing
Content compression: Gzip/Brotli compression at edge level

Monitoring:

Real-time cache hit ratio dashboards
Cache miss analysis to identify optimization opportunities
Origin request rate trends for capacity planning

This caching strategy provides a balance between performance optimization and content freshness, with robust monitoring to detect and address cache-related issues before they impact user experience.

8. Monitoring, Observability & Alerting

Real User Monitoring (RUM) Stack Selection

For comprehensive frontend monitoring, we'll implement a dual RUM approach:

OpenTelemetry + Grafana + Tempo + Loki for infrastructure-level observability
Custom RUM SDK for application-specific performance signals

The custom RUM SDK will capture:

Web Vitals (LCP, FID, CLS, INP)
Page load times and navigation timing
Error tracking with stack traces
User session data and journey mapping
Feature flag usage analytics

Synthetic Monitoring Strategy

Synthetic monitoring will be implemented using:

Cypress + Puppeteer for E2E journey testing
Lighthouse CI for automated performance audits
Playwright for cross-browser synthetic testing

These tools will run on a CI/CD pipeline every 15 minutes and during deployment windows to ensure consistent performance baseline.

Error Tracking and Alerting Thresholds

Error Alerting:

Sentry for error tracking with automatic grouping
Thresholds: >5 errors per 5-minute window or >1% of page views with errors
Critical Errors: Any unhandled promise rejections or runtime exceptions

Performance Alerting:

LCP > 2.5s: Alert if >10% of page loads exceed threshold
INP > 200ms: Alert if >5% of user sessions exceed threshold
CLS > 0.25: Alert if >5% of page views exceed threshold

Performance Regression Detection in CI

We'll implement performance regression detection using:

Lighthouse CI integrated into GitHub Actions
Web Vitals Budgets defined per page route (e.g., LCP < 2.5s, FID < 100ms)
Build-time performance checks that fail PRs if thresholds exceeded

User Journey and Funnel Analytics

User journey tracking will be implemented via:

Custom event tracking for key user actions (designer actions, export, collaboration)
Session recording with privacy controls (opt-in for sensitive data)
Conversion funnel tracking for design creation and sharing workflows

SLO Dashboards and Error Budgets

SLO Targets:

Availability: 99.9% (5m downtime max)
LCP: 90th percentile < 2.5s
INP: 90th percentile < 200ms
CLS: 90th percentile < 0.25

Error Budgets:

99.9% availability: 43.2 minutes/month of error budget
Performance SLOs: 10% error budget for each metric (e.g., 2.5s LCP = 10% of users > 2.5s)

Dashboard Requirements:

Real-time performance dashboard with region-specific metrics
Error rate and latency trends over time
User session health indicators
Feature flag performance impact tracking

Alerting Strategy

Severity Levels:

Critical: >5% of users experiencing performance degradation
High: >10% error rate or >50% of users affected by regressions
Medium: Performance degradation within 20% of thresholds
Low: Minor performance fluctuations or minor error rates

Notification Channels:

Slack alerts for critical and high severity
Email notifications for medium severity
Incident response automation for critical issues

Observability Tooling Stack

Core Tools:

OpenTelemetry Collector: For collecting and exporting telemetry data
Grafana + Loki + Tempo: For logs, traces, and metrics visualization
Sentry: For error tracking and performance monitoring
Custom RUM SDK: For application-specific telemetry

Data Retention Strategy:

Metrics: 90 days
Logs: 30 days
Traces: 30 days
User Sessions: 7 days (with opt-in for sensitive data)

This monitoring stack provides comprehensive visibility into both user experience and system health, enabling proactive performance optimization and rapid incident response. The combination of real-user data and synthetic monitoring ensures we can detect both actual user impact and potential performance regressions before they affect users.

9. Authentication & Authorization Architecture

Auth Flow Diagram (OAuth2 / OIDC)

sequenceDiagram
    participant U as User
    participant F as Frontend App
    participant A as Auth Provider (e.g., Auth0, Okta)
    participant B as Backend API

    U->>F: Navigate to protected route
    F->>A: Redirect to Auth Provider
    A->>U: Redirect with auth code
    U->>F: Return with auth code
    F->>A: Exchange code for tokens
    A->>F: Return ID token + Access token
    F->>B: Send access token with API request
    B->>F: Return protected resource
    F->>U: Display protected content

Token Storage Strategy

Storage Method	Security	Persistence	Use Case
HTTP-only cookies	High	Session	Production apps
localStorage	Medium	Persistent	Dev/test environments
Memory (in-memory)	High	Session	Single-page apps with strict security

Trade-offs:

HTTP-only cookies: Prevent XSS, but require CORS setup and session management
localStorage: Vulnerable to XSS, but simpler to debug and test
Memory: Highest security, but requires re-authentication on page refresh

Session Management

Session Lifecycle:

Token refresh (JWT with 1-hour expiry)
Silent refresh using refresh tokens (60-day validity)
Session timeout (idle timeout + max session duration)
Graceful logout with token invalidation

Session Invalidation:

Immediate logout on token refresh failure
Session timeout on inactivity (30 min idle, 8h max)
Token revocation on logout

Role-Based Access Control (RBAC) Enforcement

Frontend RBAC Implementation:

User roles and permissions fetched from backend on login
Role-based route protection (e.g., admin-only routes)
Component-level permission checks using can() utility
Dynamic UI rendering based on user permissions

Example RBAC Pattern:

// Permission check utility
const can = (user, action, resource) => {
  return user.permissions.some(
    perm => perm.action === action && perm.resource === resource
  );
};

// Route protection
const ProtectedRoute = ({ requiredPermission }) => {
  const user = useUser();
  
  if (!can(user, requiredPermission, 'dashboard')) {
    return <Redirect to="/unauthorized" />;
  }
  
  return <Dashboard />;
};

SSO Integration Strategy

SSO Implementation:

Identity Provider (IdP) integration via OIDC/OAuth2
Single sign-on across multiple applications
Centralized user management and authentication
Session sharing between services using shared cookies or JWTs

SSO Flow:

User accesses application
Redirected to IdP for authentication
IdP validates credentials and returns tokens
Application validates tokens and creates local session
Subsequent app access uses existing session (if valid)

Token Refresh Strategy

Refresh Token Handling:

Long-lived refresh tokens (60 days) stored in secure HTTP-only cookies
Short-lived access tokens (1 hour) for API requests
Automatic silent refresh using refresh tokens when access token expires
Refresh token rotation on use to prevent replay attacks

Authentication State Management

State Flow:

Unauthenticated: User not logged in, redirect to login
Authenticating: Redirecting to auth provider or processing callback
Authenticated: User logged in with valid session
Token Refreshing: Access token expired, refreshing with refresh token

State Transitions:

Unauthenticated → Authenticating → Authenticated
Authenticated → Token Refreshing → Authenticated
Authenticated → Unauthenticated (logout)

Security Considerations

Token Security:

Use of secure, same-site cookies for refresh tokens
HTTPS-only token transmission
Token expiration and renewal policies
Secure storage of sensitive tokens

Session Security:

Session timeout on inactivity and max duration
Token binding to user agent and IP address (optional)
Session invalidation on password change
Secure session regeneration on login

Auth Provider Integration

Provider Selection Criteria:

OIDC/OAuth2 support
Multi-factor authentication (MFA) capability
User directory synchronization
Audit logging and compliance features
Scalability and reliability

Integration Examples:

Auth0 for enterprise SSO and user management
Firebase Authentication for mobile/web apps
Okta for identity federation and SAML support

Token Validation Strategy

Frontend Token Validation:

JWT validation (signature, expiration, audience)
Role/permission verification from token claims
Token refresh on 401 responses (if valid refresh token available)
Graceful degradation to login page on invalid tokens

Backend Token Validation:

JWT signature verification
Token expiration checks
Role-based access control enforcement
Token revocation list checking (if applicable)

Feature Flags for Auth

Auth Feature Toggles:

Enable/disable SSO integration
Toggle between local and external auth providers
Feature flag for MFA enforcement
Toggle for session timeout duration

Migration Path Considerations

Legacy Auth Migration:

Support for existing auth methods during transition
Gradual migration to new auth system
Backward compatibility with old session tokens
User data migration and token conversion

Error Handling in Auth Flow

Auth Error Scenarios:

Token expiration (redirect to login)
Network errors during auth flow
Invalid credentials (show user-friendly error)
Provider unavailability (fallback to local auth or retry logic)

Error Recovery:

Automatic token refresh attempts
User-friendly error messages with clear actions
Retry logic for transient auth issues
Graceful degradation to guest mode where appropriate

10. Micro-Frontend Architecture (if applicable)

Module Federation Strategy

For a Design Figma frontend, we'll adopt Webpack Module Federation as the primary micro-frontend implementation strategy. This approach enables:

Shared Component Library: Core design system components (buttons, forms, layout) can be shared across multiple micro-frontends
Independent Development: Teams can develop and deploy features without blocking each other
Runtime Composition: Features can be dynamically composed at runtime based on user permissions or feature flags

Team Ownership Boundaries

The micro-frontend architecture will be organized around product domains:

graph LR
    A[Design Editor] --> B[Component Library]
    A --> C[Canvas Renderer]
    A --> D[Property Inspector]
    E[Asset Manager] --> B
    F[Plugin System] --> B
    G[User Management] --> B

Key boundaries:

Design Editor (core editor experience)
Asset Manager (media library, file handling)
Plugin System (third-party integrations)
User Management (auth, permissions, collaboration)

Contract Between Micro-Frontends

Micro-frontends communicate through:

Shared State Management: Zustand/Zustand with centralized store
Custom Events: DOM-level event system for cross-boundary communication
Routing Integration: Shared router with route registration capabilities
API Contracts: Defined interfaces for data exchange (e.g., getDesignMetadata, updateCanvasState)

Deployment Independence Model

Each micro-frontend will have independent deployment cycles:

Feature Teams can deploy their modules independently
Version Compatibility Layer: Semantic versioning with backward compatibility guarantees
Rollback Strategy: Canary deployment with automatic rollback on performance degradation

Shared Design System / Component Library Strategy

The design system will be implemented as a separate micro-frontend:

Component Registry: Centralized registry for all design tokens and components
Versioned API: Stable component interfaces with clear versioning strategy
Theme Support: Dynamic theming capabilities (light/dark mode, brand variants)
Documentation Integration: Storybook integration for component documentation

Version Compatibility and Upgrade Strategy

Versioning will follow semantic versioning with:

Major Breaking Changes: Require coordinated upgrades across dependent modules
Minor Non-Breaking Changes: Allow independent updates with compatibility layer
Patch Fixes: Backward-compatible bug fixes that can be applied independently

Implementation Considerations

Bundle Size: Shared dependencies will be deduplicated at runtime
Performance: Module federation introduces slight overhead in initial load time
Build Time: Increased build complexity with parallel builds across teams
Testing: Cross-boundary integration testing will be required for shared components

Alternative Approaches Considered

Native Federation (ESM-based): Not yet mature enough for production use in most cases
Monolithic Architecture: Would limit team autonomy and scalability
Micro-Frontend Frameworks (e.g., Single-SPA): More complex setup and less community support than Webpack Module Federation

The chosen approach provides the best balance of team autonomy, performance characteristics, and ecosystem maturity for a Design Figma frontend system.

11. Design System & Component Library

Design Token Architecture

The design system will implement a comprehensive token-based architecture to ensure visual consistency and maintainability:

Color Tokens: Define primary, secondary, and semantic color palettes with light/dark mode variants. Include accessibility-compliant contrast ratios (AA/AAA levels) for all color combinations.
Spacing Tokens: Establish a consistent spacing scale (0, 4, 8, 12, 16, 24, 32, 40, 48, 64px) that maps to CSS variables for responsive padding/margin.
Typography Tokens: Define font families, sizes (12px–32px), line heights, and weights (regular, medium, bold) with type scale ratios for visual hierarchy.
Shadow Tokens: Standardize elevation levels (0–5) with consistent blur and opacity values for depth cues.
Border Radius Tokens: Implement rounded corner sizes (0, 4, 8, 12, 16, 24px) for consistent component styling.

Component Library Ownership Model

The component library will be owned and maintained by a dedicated Platform Team, with:

Core Components: Buttons, Input Fields, Cards, Modals, Navigation, and Layout components
UI Patterns: Forms, Tables, Charts, and Data Visualization components
Accessibility Layer: Built-in ARIA attributes, keyboard navigation, and screen reader support
Documentation Site: Storybook-based documentation with live examples and usage guidelines

Versioning and Distribution Strategy

Versioning: Semantic versioning (major.minor.patch) with breaking change indicators in changelogs
Distribution: Private npm registry for enterprise components, with public open-source components available via GitHub Packages or npmjs.com
Monorepo Structure: Organized with root-level packages/ directory containing:
- @company/design-system
- @company/components
- @company/storybook

Theming Support

Dark Mode: Full dark mode support with automatic system preference detection and manual toggle capability
White Labeling: Theme customization via CSS variables for brand color overrides and font family changes
Dynamic Theming: Runtime theme switching with CSS variable-based implementation for performance

Documentation and Storybook Strategy

Storybook Integration: Comprehensive component documentation with:
- Interactive stories for all variants and states
- Props tables with default values and descriptions
- Accessibility guidelines and WCAG compliance information
Design-to-Code Alignment:
- Figma component library sync with Storybook components
- Design token mapping to CSS variables and React props
Developer Experience:
- Component usage examples with code snippets
- Auto-generated API documentation from TypeScript types
- Integration with CI for automated Storybook deployment on PRs

Component Design Principles

Atomic Design: Organized into Atoms → Molecules → Organisms → Templates → Pages
Responsive First: Components designed with mobile-first approach and responsive breakpoints (sm: 640px, md: 768px, lg: 1024px, xl: 1280px)
Accessible by Default: All components include proper ARIA roles, keyboard navigation, and focus management
Extensible: Components support custom props, className overrides, and slot patterns for customization
Performance Optimized: Memoization of expensive renders, lazy loading for heavy components, and minimal DOM structure

Design System Governance

Contribution Process:
- Component proposal process with design review and accessibility audit
- Component lifecycle management (draft → beta → stable → deprecated)
Feedback Loop:
- Internal feedback collection from product teams
- Design system usage analytics and impact measurement
Migration Strategy:
- Backward compatibility with deprecation warnings for breaking changes
- Migration tooling and codemods for common component updates

12. Security Architecture

Content Security Policy (CSP) Design

Policy Implementation: Implement strict CSP headers with default-src 'self' and explicit script-src allowing only trusted sources (CDN, first-party scripts)
Script Sources: Allow script-src 'self' 'unsafe-inline' 'unsafe-eval' for development, but restrict to script-src 'self' 'strict-dynamic' in production with nonce-based validation
Inline Script Handling: Use CSP nonces or hashes for inline scripts, with a fallback to unsafe-inline for legacy support
External Resource Restrictions: Block external fonts, images, and stylesheets except from verified domains (e.g., font-src 'self' https://fonts.gstatic.com, img-src 'self' data: https://*.figma.com)
Report-Only Mode: Implement CSP in report-only mode during initial rollout to monitor violations before enforcing strict policy

Subresource Integrity (SRI)

Script Integrity: Apply SRI hashes to all third-party JavaScript libraries loaded from CDNs (e.g., integrity="sha384-...")
Style Integrity: Ensure CSS files from external sources include SRI attributes
Build Integration: Automate SRI hash generation in build pipeline using tools like sri-workbox or webpack-subresource-integrity
Fallback Strategy: Implement fallback to CDN-hosted resources if SRI validation fails, with error logging for security team review

CORS Configuration

Origin Whitelisting: Configure CORS headers to allow only known frontend origins (e.g., Access-Control-Allow-Origin: https://figma.com)
Method Restrictions: Allow only necessary HTTP methods (GET, POST, PUT, DELETE) in Access-Control-Allow-Methods
Header Allowlist: Restrict Access-Control-Allow-Headers to only required headers (e.g., Content-Type, Authorization)
Credentials Support: Enable Access-Control-Allow-Credentials only when necessary, with matching credentials: include in client-side requests

XSS and CSRF Prevention

Input Sanitization: Implement DOMPurify or similar library for all user-generated content rendered to the DOM
Template Escaping: Ensure all template rendering (e.g., Handlebars, React) properly escapes user input to prevent XSS
CSRF Token Strategy: Include CSRF tokens in all state-modifying requests, stored in HTTP-only cookies with SameSite=Strict
Request Validation: Validate all incoming requests for proper content types and headers to prevent CSRF attacks

Secrets Management

Environment Variables: Store sensitive configuration in environment variables (e.g., API keys, feature flags) with build-time injection
Runtime Secrets: For secrets that must be accessed at runtime, use secure HTTP-only cookies or encrypted storage in browser (e.g., localStorage with encryption)
Build-Time vs. Runtime: Separate secrets that are known at build time (e.g., API endpoints) from runtime secrets (e.g., session tokens)
Secret Rotation: Implement automated secret rotation and refresh mechanisms in the build pipeline or deployment process

Dependency Vulnerability Scanning in CI

Vulnerability Detection: Integrate npm audit, yarn audit, or Snyk into CI pipeline to scan for known vulnerabilities in dependencies
Automated Alerts: Configure CI to fail builds when critical or high severity vulnerabilities are detected (e.g., npm audit --audit-level critical)
Security Policy Enforcement: Enforce security policies in CI that prevent deployment of code with vulnerable dependencies
Dependency Pinning: Use package-lock.json or yarn.lock to ensure consistent dependency versions across environments and prevent supply chain attacks

13. Scalability & Multi-Region Strategy

Global Traffic Routing

The frontend will utilize Anycast DNS routing combined with Geo-based load balancing to achieve optimal latency for users worldwide. This approach allows traffic to be routed to the nearest available edge location, reducing network hops and improving response times. The system will implement BGP (Border Gateway Protocol) to dynamically adjust routing based on real-time network conditions and health checks.

Multi-Region CDN Strategy

The frontend will leverage a multi-region CDN architecture using Cloudflare or Fastly to ensure global distribution of static assets and dynamic content. The CDN will be configured with multiple Points of Presence (PoPs) strategically located in major regions:

North America: 3 PoPs (US East, US West, Canada)
Europe: 2 PoPs (UK, Germany)
Asia-Pacific: 3 PoPs (Singapore, Japan, Australia)
South America: 1 PoP (Brazil)

Latency Optimization Per Region

Each region will maintain its own edge rendering layer to minimize latency. The system will implement:

Regional edge functions for content personalization and A/B testing
Localized asset delivery with region-specific optimizations (e.g., image formats, compression levels)
Regional API gateway routing to reduce network latency for backend services

Data Residency Compliance

The system will implement data residency controls to comply with regional regulations:

GDPR compliance for EU users (data processing within EU boundaries)
CCPA compliance for US users (California data handling)
Regional data storage and processing requirements for APAC markets
Secure data transfer protocols (TLS 1.3+) between regions

Regional Content Delivery Strategy

Content will be delivered with region-specific optimizations:

Localized content caching with appropriate TTLs per region
Regional image optimization (format selection, compression levels)
Content-aware routing to ensure users receive content from the nearest region
Regional feature flagging and A/B testing capabilities

Auto-scaling Architecture

The frontend will implement automatic scaling across regions:

Horizontal scaling of edge services based on traffic volume
Regional load balancing with health checks and automatic failover
Dynamic resource allocation based on real-time traffic patterns
Regional capacity planning with built-in over-provisioning for peak loads

Cross-Region Synchronization

For services requiring global consistency:

Multi-region database replication with eventual consistency patterns
Cross-region cache invalidation mechanisms
Global session management with regional failover capabilities
Synchronized feature flag states across all regions

Performance Monitoring by Region

Each region will maintain independent performance monitoring:

Regional latency metrics and error rates
Localized user experience tracking
Region-specific performance baselines for alerting thresholds
Automated region switching based on performance degradation

Cost Optimization Strategy

The system will implement cost-efficient regional distribution:

Regional traffic optimization to reduce bandwidth costs
Dynamic content delivery based on region popularity
Regional caching strategies to minimize origin requests
Cost monitoring and alerting for cross-region traffic patterns

Disaster Recovery & Failover

The multi-region strategy includes:

Automatic failover to backup regions during outages
Regional service degradation rather than complete system failure
Cross-region health monitoring and alerting
Automated traffic rerouting with minimal user impact during failures

14. Build System & Bundling Strategy

Build Toolchain Selection

For the Figma frontend, we select Vite as the primary build tool due to its superior development experience and performance characteristics. Vite's native ESM support enables fast hot module replacement (HMR) during development, which is crucial for a design tool where rapid iteration is essential. Its build performance scales well with large codebases, and it has excellent ecosystem support for modern frontend frameworks like React.

Webpack is considered but ruled out due to its complex configuration and slower build times, particularly when handling large design systems with many components. Turbopack is a potential future option but not yet stable enough for production use at scale.

Monorepo vs. Polyrepo Build Strategy

We adopt a monorepo approach using Turborepo for build orchestration and task management. This enables:

Shared dependencies across multiple frontend applications (e.g., design system, shared components)
Consistent linting and testing across the codebase
Efficient caching of build artifacts across services
Atomic commits and versioning of related packages

The monorepo structure allows us to treat the design system, Figma frontend, and any supporting tools as a cohesive unit while maintaining clear package boundaries.

Build Output Targets

The build system generates multiple output formats to support diverse deployment scenarios:

ESM bundles for modern browsers (ES2020+ features) with dynamic imports
CJS bundles for Node.js environments (SSR, server-side rendering)
Legacy UMD bundles for fallback support in older browsers (e.g., IE11 compatibility layer)

This multi-target strategy ensures that the frontend works across all supported environments without requiring separate builds or runtime polyfills.

Build Performance at Scale

With an estimated team size of 50+ engineers and a codebase of 200k+ lines, we project build times under 30 seconds for incremental builds using Turborepo's caching and parallelization. The monorepo setup enables efficient task dependency tracking, allowing only necessary packages to rebuild when changes occur.

We implement build caching strategies using Turborepo's built-in cache and ensure that large asset processing (e.g., SVGs, images) is optimized through Webpack's asset handling or Vite's native image optimization.

15. Deployment & Release Strategy

Deployment Strategy

The frontend will utilize a canary deployment strategy with blue-green deployment as the primary rollback mechanism. This approach ensures zero-downtime deployments and enables progressive rollouts to mitigate risk.

Traffic Management:

Traffic is routed through a load balancer with weighted distribution (90% stable, 10% canary)
Health checks are performed every 30 seconds to ensure deployment stability
Rollback triggers automatically if error rate exceeds 1% or latency increases by 50%

Rollback Design:

If canary deployment fails, traffic is immediately shifted back to the stable version
Rollback process completes in under 30 seconds using infrastructure-as-code (Terraform)
Deployment history is maintained for 30 days with detailed changelog and rollback capability

Feature Flags System Integration

A feature flags system will be integrated using LaunchDarkly to enable:

Progressive rollouts (1% → 10% → 50% → 100%)
A/B testing capabilities for UI variants
Emergency feature toggling for quick fixes
Rollback capability without redeployment

Implementation:

Feature flags are fetched at app initialization and cached for 5 minutes
Flags are evaluated client-side using a lightweight SDK
Flag changes are propagated via WebSocket for near real-time updates

Preview Environment Strategy

Each pull request will automatically generate a preview environment with:

Unique subdomain (e.g., pr-123.figma-frontend.dev)
Isolated database and API endpoints
Full CI/CD pipeline integration for automated testing
Access control via GitHub teams and SSO

Isolation Model:

Preview environments use separate CDN distribution points
Database snapshots are created per PR for data isolation
API endpoints are mocked or point to staging environments

Canary Analysis Automation

Automated Analysis:

Web Vitals monitoring (LCP, FID, CLS) for canary builds
Error rate thresholds (1% error rate triggers rollback)
Performance regression detection using Lighthouse CI
Synthetic monitoring of critical user flows

Auto-Rollback Triggers:

If LCP > 2.5s or FID > 300ms for 5 consecutive minutes
If error rate exceeds 1% for more than 2 minutes
If page load time increases by 30% compared to baseline

CDN Cache Invalidation Strategy

Cache Invalidation Events:

On successful deployment, CDN cache is invalidated for:
- All static assets (JS, CSS, images)
- Dynamic routes that may have changed content
- API endpoint cache (if applicable)

Cache Invalidation Process:

CDN cache invalidation is performed via API call to CloudFront distribution
Invalidations are batched to reduce cost and latency
Cache invalidation completes within 30 seconds of deployment

Versioned Assets:

All static assets are versioned using content hashes (e.g., main.abc123.js)
Asset URLs are updated in the HTML only after successful deployment
Old versions remain available for 30 days to handle browser cache issues

Release Process Workflow

Commit → CI Pipeline:
- Code linting and unit tests (95%+ coverage)
- E2E test suite execution
- Performance budget validation
PR Merge → Preview Deployment:
- Automated preview environment creation
- Security scanning (dependency vulnerabilities)
- Accessibility and visual regression testing
Release → Production Deployment:
- Canary deployment (10% traffic)
- Monitoring and alerting validation
- Gradual rollout to 100% if stable
Post-Deployment:
- Automated smoke testing
- Performance monitoring validation
- Rollback prepared if needed

Deployment Frequency Targets

Production releases: 1-2 per week for feature releases
Hotfixes: Immediate deployment when critical issues are identified
Preview environments: Generated for every PR within 5 minutes of creation
Canary deployments: Enabled for all non-critical feature releases

Rollback Procedure

In case of deployment failure:

Traffic is immediately shifted to the stable version
Rollback process completes within 30 seconds
Error logs and performance metrics are analyzed for root cause
Deployment is re-attempted after fixes are applied
Rollback history is maintained for 30 days with detailed analytics

16. Internationalization (i18n) & Accessibility

Locale Detection and Routing Strategy

The frontend will support multiple locales with URL-based routing (e.g., /en/dashboard, /fr/dashboard) to enable direct access and SEO optimization. The default locale will be determined by the user's browser Accept-Language header or geolocation-based inference, with a fallback to English (en). A cookie-based preference will allow users to override their detected locale. The routing strategy will use a combination of path-based routing and dynamic imports for locale-specific bundles to reduce initial bundle size.

Translation Infrastructure

Translation keys will follow a hierarchical structure (e.g., dashboard.header.title) to support maintainability and reduce key collisions. Message catalogs will be organized by locale in JSON format, with lazy loading of translation bundles using dynamic imports. The system will support pluralization and contextual variations through ICU message syntax (e.g., {count, plural, one{1 item} other{# items}}). Translation files will be validated at build time to ensure completeness and consistency.

RTL (Right-to-Left) Layout Support Strategy

RTL layout support will be implemented through CSS logical properties and a theme-aware component architecture. The design system will include RTL-specific overrides for spacing, text alignment, and component directionality. Components like sidebars, cards, and navigation will dynamically adjust their layout based on the current locale's directionality. A global RTL toggle (for testing) and automatic detection from locale metadata will be provided.

Date, Number, and Currency Formatting

All date, number, and currency formatting will leverage the native Intl API to ensure proper localization. The system will support locale-specific formats for dates (e.g., en-US vs fr-FR), numbers (e.g., decimal separators), and currencies (e.g., $1,000.00 vs €1 000,00). A centralized formatting utility will abstract these implementations to ensure consistency across the application.

WCAG 2.1 AA Compliance Strategy

The application will be built to meet WCAG 2.1 AA standards, with focus on:

Sufficient color contrast (minimum 4.5:1 for normal text, 3:1 for large text)
Keyboard navigation support (full keyboard accessibility with skip links)
ARIA attributes for dynamic content and interactive elements
Semantic HTML structure (e.g., proper heading hierarchy, landmark roles)
Screen reader compatibility through ARIA labels and roles

All interactive elements will be fully keyboard accessible, with clear visual focus indicators. A global focus management system will handle focus trapping in modals and dropdowns, ensuring that focus remains within interactive components until explicitly exited. The system will support skip-to-content links for keyboard users and maintain proper tab order across all components.

Screen reader compatibility will be ensured through:

Proper semantic HTML structure (e.g., nav, main, section elements)
ARIA roles and properties (e.g., aria-expanded, aria-selected)
Dynamic content announcements using aria-live regions
Descriptive alt text for all images and icons
Landmark roles to help users navigate by content type

i18n Implementation Considerations

Translation files will be versioned and managed through a centralized translation platform (e.g., Crowdin or Transifex)
Language switching will be handled through a global context provider with automatic re-rendering of translated content
The system will support "missing translation" placeholders for new keys to prevent broken UIs during translation updates
Performance impact of i18n will be minimized through lazy loading and caching of translation bundles

Accessibility Testing Strategy

Integration with axe-core in CI pipeline for automated accessibility testing
Manual keyboard navigation testing as part of the QA process
Regular accessibility audits using automated tools and manual checks
User testing with screen reader users to validate real-world accessibility
Integration with design system documentation for accessibility guidelines and examples

17. Testing & Reliability

Frontend Testing Pyramid

Unit Tests (20% of test suite)

Component unit tests using Jest and React Testing Library
Mock external dependencies (APIs, browser APIs)
Test edge cases and error boundaries in isolated components
Focus on pure functions and state logic

Integration Tests (30% of test suite)

Component integration tests for complex UI interactions
Test component composition and prop combinations
Validate state management integration with real or mocked stores
Test data flow between connected components

E2E Tests (50% of test suite)

End-to-end user journeys using Cypress or Playwright
Test full application workflows (login → dashboard → action)
Validate cross-browser and device compatibility
Monitor performance regressions in real user flows

Visual Regression Testing Strategy

Tool Selection:

Percy or Chromatic for visual diff testing
Capture baseline screenshots in CI/CD pipeline
Automate regression detection on PRs with visual changes

Scope:

Critical UI components (buttons, forms, navigation)
Layouts across breakpoints and themes
Dark mode variants and accessibility states

Accessibility Testing Automation

Framework Integration:

axe-core integration in CI pipeline (axe-playwright or axe-jest)
Enforce WCAG 2.1 AA compliance as part of build process
Fail CI builds on accessibility violations exceeding threshold

Testing Coverage:

Keyboard navigation flow validation
Screen reader compatibility testing (NVDA, JAWS)
Color contrast ratio checks for all UI elements

Performance Regression Detection in CI

Tooling:

Lighthouse CI for automated performance audits
Web Vitals monitoring in CI pipeline (LCP, FID, CLS)
Budget-based thresholds to prevent performance degradation

Thresholds:

LCP < 2500ms, FID < 100ms, CLS < 0.1
Page weight increase >5% triggers alert

Synthetic Monitoring and Alerting

Monitoring Scope:

Critical user journeys (login, dashboard load, key actions)
API response time and error rates
Feature availability across browsers and devices

Alerting Strategy:

Threshold-based alerts (e.g., >5% error rate in 5-minute window)
User impact thresholds (e.g., >10% of users experiencing >3s load time)
Automated rollback triggers for performance regressions

Feature Flag Rollback Strategy

Implementation:

Feature flags managed via LaunchDarkly or custom solution
Rollback capability for frontend features with zero-downtime deployment
Graceful degradation when flags are disabled or missing

Testing:

Validate rollback paths in staging environments
Test feature flag combinations and edge cases
Monitor user impact during flag transitions

Reliability Patterns

Circuit Breaker Pattern:

Implement circuit breaker for external API calls (e.g., analytics, third-party integrations)
Fail gracefully with fallback UI when upstream services are unavailable

Graceful Degradation:

Progressive enhancement for critical features
Offline support via service workers and local storage
Fallback content when real-time data is unavailable

Retry Logic:

Exponential backoff for transient API failures
Retry limits and error boundaries to prevent cascading failures

Test Coverage Targets

Test Type	Coverage Target	Tools
Unit Tests	80% code coverage	Jest, React Testing Library
Integration Tests	90% component interaction	Jest, React Testing Library
E2E Tests	100% critical user journeys	Cypress, Playwright
Accessibility	100% WCAG AA compliance	axe-core
Performance	LCP < 2500ms, FID < 100ms	Lighthouse CI
Visual Regression	95% of critical UIs	Percy, Chromatic

CI Pipeline Integration

Test Execution:

Unit and integration tests run in parallel on every PR
E2E tests execute on feature branches with preview environments
Accessibility and visual regression tests run in pre-deployment stage
Performance budgets enforced before merge to main

Failure Handling:

CI pipeline fails on test failures exceeding threshold
Slack notifications for failed tests and performance regressions
Automated rollback capability for flagged releases

18. Open Questions, Risks & Trade-offs

Decisions requiring product / engineering alignment

Feature scope definition: How much of Figma's core functionality should be prioritized in the initial release vs. gradually added?
Design system maturity: Should we build a new design system from scratch or leverage existing Figma components and patterns?
Real-time collaboration model: What level of concurrent editing support is required for MVP vs. future iterations?
Export capability scope: Should we support all Figma export formats (SVG, PNG, PDF) in the first release or start with basic image exports?

Key risks with mitigation plan

Risk	Impact	Likelihood	Mitigation
High latency in collaborative editing	High	Medium	Implement delta-based sync with optimistic updates and conflict resolution strategies
Bundle size bloat from design tools	High	High	Use code splitting, lazy loading, and tree-shaking; implement progressive loading of tools
Inconsistent rendering across browsers	Medium	High	Implement comprehensive browser testing and fallback strategies
Performance degradation with large canvas operations	High	Medium	Use virtualization techniques and canvas optimization strategies
Security vulnerabilities in third-party design libraries	High	Medium	Implement strict dependency vetting, regular security scanning, and sandboxing

Architectural trade-offs made with justification

Trade-off	Decision	Justification
Server-side rendering vs. client-side rendering	Client-side rendering with SSR fallback	Figma's interactive canvas requires heavy client-side computation; SSR would be inefficient for real-time UI
Monorepo vs. polyrepo	Monorepo with shared design system	Enables better code sharing, consistent versioning, and easier cross-component refactoring
State management approach	Hybrid (Zustand for local state, React Query for server state)	Combines simplicity of Zustand with robustness of React Query for data fetching
Image handling strategy	CDN + client-side optimization pipeline	Balances performance with flexibility to support various image formats and sizes
Real-time communication	WebSocket + polling fallback	Provides low-latency collaboration while maintaining backward compatibility

Alternatives considered and rejected

Alternative	Reason for rejection
Astro-based Islands Architecture	Too experimental and not mature enough for a complex design tool with real-time collaboration
Custom Canvas Engine	Too time-intensive and error-prone; leveraging established libraries like Fabric.js or Konva.js is more practical
Full SSR with server-side canvas rendering	Would significantly increase complexity and latency for real-time interactions
Micro-Frontend Architecture	Overkill for a single product with tight coupling between features; increases complexity without clear benefit
Vanilla React without component library	Would require significant time to build consistent UI components and maintain accessibility

Technical debt acknowledged

Canvas rendering abstraction: Current implementation tightly couples to specific canvas libraries, making future migration harder
State synchronization complexity: Real-time state updates introduce potential race conditions and consistency issues that will require ongoing attention
Testing coverage gaps: E2E tests for collaborative features are limited due to complexity of simulating concurrent user interactions
Performance monitoring depth: Current RUM implementation focuses on basic metrics but lacks granular canvas performance insights
Internationalization readiness: i18n support is basic and will require significant refactoring to handle complex design tool text content properly

19. Phased Implementation Roadmap

Phase 1: MVP (Minimum Viable Product)

Timeline: 8-12 weeks Focus: Core functionality with minimal dependencies

Key Deliverables:

Basic Figma design system implementation (components, tokens, themes)
Core UI library with 10-15 essential components (buttons, forms, cards, navigation)
Component library documentation with Storybook
Basic design token system (color, spacing, typography) with 3-5 themes
Core state management setup (Zustand or Redux Toolkit)
Authentication flow with basic RBAC
Performance baseline established (LCP < 2.5s, TTFB < 500ms)
Basic CI/CD pipeline with linting and unit tests

Dependencies:

Design system assets from design team
Authentication backend endpoints
Component library ownership established

Phase 2: Scale & Hardening (Weeks 12-24)

Timeline: 12-16 weeks Focus: Performance optimization, reliability, and feature expansion

Key Deliverables:

Complete component library (50+ components) with full accessibility support
Advanced state management patterns (React Query for server state, Zustand for client)
Internationalization support with 3-5 locales
Real-time collaboration features (WebSocket integration)
Comprehensive testing suite (unit, integration, E2E with 80% coverage)
Performance optimization (image optimization, code splitting, lazy loading)
Service worker implementation for PWA capabilities
Advanced monitoring stack (RUM, error tracking, synthetic tests)
Feature flag system for progressive rollouts

Dependencies:

Design system maturity and design token consistency
Backend API stability for collaboration features
CI pipeline with automated performance testing

Phase 3: Excellence & Optimization (Weeks 24-36)

Timeline: 12 weeks Focus: Reliability, observability, and cost optimization

Key Deliverables:

Advanced accessibility compliance (WCAG 2.1 AA)
Multi-region deployment strategy with CDN optimization
Advanced caching and edge rendering strategies (Edge Functions)
Comprehensive error budget monitoring and alerting
Performance regression detection in CI/CD pipeline
Security hardening (CSP, SRI, XSS prevention)
Micro-frontend architecture for team autonomy
Advanced internationalization with RTL support and locale-specific formatting
Automated visual regression testing suite

Dependencies:

Multi-region infrastructure availability
Advanced monitoring stack maturity
Team structure and ownership boundaries established for micro-frontends

Critical Path Dependencies:

Design system assets availability (Week 2)
Authentication backend stability (Week 4)
Component library ownership and governance (Week 6)
CI/CD pipeline with performance testing (Week 8)
Multi-region infrastructure setup (Week 12)

Risk Mitigation:

Phase 1 deliverables are designed to be deployable and provide business value
Phase 2 includes performance and reliability improvements as a safety net
Phase 3 focuses on optimization and observability to ensure long-term maintainability
Each phase includes rollback capability for feature flags and deployments