High-Scale System Design Architecture & Scalability Blueprint
Design high-scale distributed architectures (e.g. URL shortener, Uber, Twitter, Netflix) handling millions of requests per second.
System Directive • Copy and Paste Below
Act as a Principal Infrastructure Architect at a FAANG company and senior system design interviewer. Provide an exhaustive, high-scale system design architecture for the following system. ### SYSTEM DESIGN SCOPE: - System Being Designed (e.g., TinyURL, Rate Limiter, Chat System, Video Streaming, Distributed Cache): [SYSTEM_TO_DESIGN] - Scale & Traffic Requirements: [TRAFFIC_AND_STORAGE_SCALE] - Latency SLA & Availability Targets (e.g. 99.99% uptime, <50ms read latency): [SLA_TARGETS] - Consistency Model (Strong Consistency vs Eventual Consistency / CAP Theorem): [CONSISTENCY_PREFERENCE] ### STRUCTURED ARCHITECTURAL BLUEPRINT: 1. **Scope Clarification & Back-of-the-Envelope Estimations**: - Daily Active Users (DAU), Read vs Write ratio, QPS (Queries Per Second), Peak QPS. - Storage capacity estimations for 5-year retention. - Network bandwidth requirements. 2. **API Endpoint Signatures**: - Exact REST / gRPC endpoint definitions with payload schemas. 3. **Database Schema & Storage Technology Selection**: - SQL vs NoSQL trade-offs (e.g. Cassandra for time-series vs PostgreSQL for ACID vs Redis for hot data). 4. **High-Level Component Architecture (Mermaid Diagram)**: - Flow: Client -> DNS / CDN -> Load Balancer -> API Gateway / Rate Limiter -> App Services -> Cache Cluster -> DB Cluster (Primary / Read Replicas). 5. **Deep-Dive Scaling Levers & Edge Cases**: - Data partitioning / Sharding strategy (Consistent Hashing ring to avoid hot spots). - Multi-tier caching strategy (Eviction policies, Cache-aside pattern). - Single Point of Failure (SPOF) mitigation and disaster recovery failover.
Customization & Placeholders
Specify your system and scale numbers. The output follows the official 45-minute system design interview structure.
Example Input Values
System: Distributed Rate Limiter, Scale: 500k QPS across 5 regions, SLA: <5ms overhead, Consistency: Eventual consistency with Redis cluster.
Expected Output Structure
Token Bucket algorithm implementation, Redis sliding window Lua script, global architecture diagram, and failure handling.
High-Throughput Cloud Engineering by Qubenix
Qubenix designs and deploys distributed cloud systems capable of handling enterprise traffic with sub-second performance.
More Prompts in Coding & Development
React & TypeScript Clean Component Architecture & State Management
Architect clean, maintainable React 19 / TypeScript components using compound patterns, custom hooks, and zero re-render bloat.
PostgreSQL / MySQL Query Optimization, Indexing & EXPLAIN ANALYZE
Diagnose slow database queries, optimize table schemas, and design composite B-Tree/GIN indexes to drop execution time by 90%+.
Enterprise REST & GraphQL API Schema Designer with OpenAPI Specs
Design clean, pragmatic RESTful endpoints or GraphQL schemas adhering to OpenAPI 3.1 standards, pagination, and status codes.