#scalability

Design scalable URL shortening service (like TinyURL). Components: 1. API design (REST/GraphQL). 2. Hashing algorithm (Base62). 3. Database schema (NoSQL vs SQL) and partitioning. 4. Cache layer (Redis) for redirect performance. 5. Unique ID generation (KGS - Key Generation Service). 6. Analytics service (async processing). 7. Rate limiting and abuse prevention. 8. High availability and georedundancy strategy.

Design microservices architecture effectively. Principles: 1. Single Responsibility (one service, one business capability). 2. Decentralized Data (each service owns its database). 3. API Gateway (single entry point). 4. Service Discovery (Consul, Eureka). 5. Asynchronous Communication (message queues, events). 6. Circuit Breaker (fault tolerance). 7. Containerization (Docker, Kubernetes). Challenges: distributed tracing, data consistency, testing. Use API versioning. Implement health checks. Centralized logging (ELK). Monitoring (Prometheus, Grafana). Start with monolith, extract services gradually. Not always the right choice - consider team size and complexity.

Optimize application performance systematically. Techniques: 1. Profile first (identify bottlenecks with profiler). 2. Database optimization (indexes, query optimization, connection pooling). 3. Caching (Redis, Memcached, CDN). 4. Lazy loading (load data on demand). 5. Code-level optimization (efficient algorithms, avoid premature optimization). 6. Asynchronous processing (queues, background jobs). 7. Minification and compression (gzip, Brotli). Frontend: bundle splitting, image optimization, tree shaking. Backend: horizontal scaling, load balancing. Measure impact (before/after metrics). Use APM tools (New Relic, Datadog). 80/20 rule: optimize the 20% causing 80% slowness.

Protect APIs with rate limiting. Strategies: 1. Fixed window (requests per minute). 2. Sliding window for smoother limits. 3. Token bucket for burst handling. 4. Leaky bucket for consistent rate. 5. Per-user vs global limits. 6. Redis for distributed rate limiting. 7. Return 429 with Retry-After header. 8. Different tiers for API keys. Use middleware like express-rate-limit. Implement exponential backoff guidance.

Build comprehensive design system that scales across teams and products. Foundation elements: 1. Color palette: primary (3-5 colors), secondary, semantic colors (success, warning, error). 2. Typography scale: modular scale ratio (1.125, 1.25, 1.5), weight hierarchy (regular, medium, bold). 3. Spacing system: 8px base unit, scale (8, 16, 24, 32, 48, 64px). 4. Iconography: consistent style, 24px base size, stroke width standardization. Component library: 1. Atomic level: buttons, inputs, labels with all states (default, hover, active, disabled). 2. Molecular level: search bars, form fields with validation states. 3. Organism level: headers, cards, navigation systems. Documentation structure: 1. Design principles: brand personality, user experience guidelines. 2. Usage guidelines: when to use each component, accessibility requirements. 3. Code snippets: implementation examples for developers. Tools: Figma for design components, Storybook for development documentation, design tokens for consistency across platforms. Governance: design system team ownership, regular audits, contribution process for new patterns.

Make informed technical architecture decisions for product scalability. Architecture decision process: 1. Define requirements: performance, scalability, compliance needs. 2. Research options: evaluate technologies, frameworks, cloud services. 3. Prototype: build proof-of-concepts for critical decisions. 4. Document trade-offs: benefits, drawbacks, costs of each option. 5. Decision review: technical team consensus on approach. Key decisions: 1. Monolith vs. microservices: start simple, split when needed. 2. Database choice: relational vs. NoSQL based on data structure. 3. Cloud strategy: single vs. multi-cloud, vendor lock-in considerations. 4. API design: REST vs. GraphQL, versioning strategy. 5. Frontend architecture: SPA vs. MPA, framework selection. Documentation: Architecture Decision Records (ADRs) for future reference. Non-functional requirements: security, performance, maintainability, compliance. Technical debt management: plan for refactoring, monitor system health metrics. Balance: current needs vs. future flexibility, time-to-market vs. technical excellence.