Roadmap › 0. Fundamentals › Step 5
HLD
System Design — High-Level Design (HLD) from Basics to Case Studies
How to design large systems — requirements and estimation, scalability and availability, latency vs throughput, CAP and consistency models, load balancing, caching strategies, database choice, replication, partitioning and sharding, consistent hashing, queues and event streaming, rate limiting, search, storage and CDNs, observability, and full case studies (URL shortener, news feed, chat, notification service, e-commerce checkout, file storage, ride booking) with the HLD interview framework.
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Interview framework
Requirements → estimation → API → data model → diagram → deep dive → bottlenecks/failures → trade-offs.
Estimation shortcuts
1M/day ≈ 12/s · peak 2–10× · day ≈ 10⁵ s · 99.9 % ≈ 8.8 h/yr down · 99.99 % ≈ 53 min/yr.
Building blocks
DNS/CDN · load balancer · API gateway · stateless services · cache (Redis) · SQL + replicas · NoSQL · object storage · queue/stream · search index · rate limiter · monitoring.
Data scaling ladder
Indexes → caching → read replicas → vertical scale → partitioning → sharding (consistent hashing) → multi-region.
Trade-offs to say out loud
Consistency vs availability · latency vs consistency · push vs pull · SQL vs NoSQL · sync vs async · cost vs redundancy · simplicity (monolith) vs independence (microservices).