🏗️ High-Level Design (HLD)
Scale systems to millions of users — networking, databases, caching, message queues, distributed systems, reliability, and full case studies.
Phase B-I — Foundations (Weeks 11–15)
HLD Fundamentals
Scalability, CAP Theorem, Consistency Models, Availability Patterns, Load Balancing, Latency vs Throughput. Back-of-envelope estimation and the SD Interview Framework.
Databases at Scale
Indexing (B-Tree, Hash, Composite, Covering), ACID vs BASE, SQL vs NoSQL decision framework, Replication, Sharding strategies, and a practical DB Selection Guide.
Caching
Cache-Aside, Write-Through, Write-Back, Read-Through. LRU/LFU eviction, cache invalidation, stampede prevention. Redis data structures (Strings, Hashes, Sets, Sorted Sets) and CDN caching.
Message Queues & Kafka
Async messaging patterns, Kafka architecture (partitions, offsets, consumer groups), at-least-once vs exactly-once, backpressure.
Coming Soon
Next HLD module — to be announced.
Phase B-II — System Designs at Scale (Weeks 16–20)
Design Twitter/X Feed
Fan-out on write vs read, hybrid timeline generation, graph DBs, custom cache.
Design WhatsApp
WebSockets, Cassandra, session store, delivery receipts, presence system.
Design YouTube
Chunked upload, transcoding (temporal parallelism), HLS adaptive streaming, 3-tier CDN, sharded view counter, Elasticsearch search.
Design a Rate Limiter
5 algorithms (fixed/sliding window, token/leaky bucket), Redis Lua scripts, distributed limiting, HTTP 429 headers, multi-tier architecture.
Consistent Hashing & Service Discovery
Hash ring, virtual nodes, Consul, ZooKeeper, client vs server-side discovery, health checks, gossip protocol, Raft consensus.
Phase B-III — Advanced & Distributed Topics (Weeks 21–24)
Storage Systems
Object storage (S3), blob storage, HDFS, time-series DBs, search engines (Elasticsearch), columnar analytics (BigQuery, Redshift).
Special Topics
Full-text search, notification systems (push/pull), geospatial systems, unique ID generation (UUID, Snowflake), top-K / trending.
ML Systems Design
Feature stores, model serving infrastructure, A/B testing at scale, recommendation system design, stream processing for ML pipelines.
Kubernetes & Containers
Docker fundamentals, Kubernetes architecture (pods, services, ingress), horizontal pod autoscaling, rolling deployments, Helm.
Module Coverage Summary
| Phase | Modules | Weeks | Topics |
|---|---|---|---|
| B-I: Foundations | B1–B5 | 11–15 | HLD Fundamentals, Databases at Scale, Caching, Message Queues, URL Shortener |
| B-II: System Designs | B6–B10 | 16–20 | Twitter Feed, WhatsApp, YouTube, Rate Limiter, Consistent Hashing |
| B-III: Advanced | B11–B14 | 21–24 | Distributed Transactions, Interview Framework, ML Systems, Kubernetes |