Master System Design

Master system design presents six pillars—networking, API design, data modeling, caching, scaling, and consistency—and guides decisions under constraints to balance scale, performance, reliability, and cost.

Trace real-time sync from polling to long polling, server-sent events, and web sockets, comparing one-way and two-way communication for chat and live updates.

Map each connected user to a server and route websocket messages via pub/sub so the correct server delivers to the client, with message persistence and sticky load balancing.

Explore real-time messaging architecture from client to server, compare pull and push models, and learn consistent hashing and pub/sub patterns that enable scalable, decoupled WebSocket communication for chat and notifications.

Examine how contention causes race conditions and double bookings, compare locking and optimistic concurrency control with versioning to maintain correctness without blocking in high-concurrency systems.

Move from locking and optimistic concurrency to serialized queues and sharding, processing requests per show and per seat to reduce contention while preserving correctness.

Explore how caching stores frequently accessed data in faster layers to reduce latency, maximize cache hit ratio, and lower database load across application, distributed, and CDN caches.

Examine multi-level caching across browser, CDN, and application layers, including L1/L2 caches, browser memory and disk caches, and validation mechanisms like eTag and last-modified to balance latency, scalability, and consistency.

Explore cache invalidation strategies that balance performance and freshness, including TTL, write-through, cache-aside, and event-based invalidation, with their trade-offs for data consistency.

Sharding part 1 of master system design introduces partitioning concepts to enable scalable distributed architectures.

examine sharding challenges like hotspots, load imbalance, and cross-shard queries, and present strategies such as consistent hashing, rebalancing, shard key design, denormalization, and scatter-and-gather pattern.

Learn consistent hashing to distribute data across databases with minimal movement using a ring and clockwise ownership, and use virtual nodes to balance load and reduce hotspots.

Indexes speed up searches in large tables by using a B-tree structure with root and leaf nodes, enabling fast equality and range queries.

Explore why B+ trees optimize range queries and sequential access by moving data to leaf nodes and linking leaves, contrasting with B-trees' balanced structure.

Evaluate data access patterns, consistency, and scale to choose between SQL and NoSQL, then explore key-value stores, document databases, wide-column stores, and graph databases.

Compare no-sql document databases like MongoDB, highlighting document data, JSON, flexible schemas, and when to use vs relational databases for school management, ecommerce, and configuration data.

Master the key-value data model, storing data as keys and values for fast access. Use cases include user sessions, shopping carts, and preferences, with limitations on queries and relationships.

Discover graph data by treating entities as nodes and connections as edges, enabling traversal queries to reveal shortest paths and complex relationships for graph databases.

Explain the ACID and BASE models, their properties—atomicity, consistency, isolation, durability, and availability—and eventual consistency and how they shape reliability, performance, and scalability.

Master system design introduces database isolation levels, explaining dirty reads, non-repeatable reads, and phantom reads, and compares read uncommitted, read committed, repeatable read, and serializable.

Compare lock-based serialization and MVCC with commit-time validation to enforce serializable isolation, showing how locks block reads and writes, versus parallel transactions that may retry on conflict.

Explore vertical scaling by upgrading a single machine’s RAM, CPU, and storage, then switch to horizontal scaling with multiple servers behind a load balancer, addressing caching and sharding for availability.

Learn to design scalable systems with stateless architecture, JWT-based sessions, and geo-based load balancing, while using master and replica databases, caching via CDN, and auto scaling.

Master hexagonal architecture, also called ports and adapters, isolates core business logic inside a hexagon and connects it to systems via input and output ports, enabling loose coupling and testing.

Design a Google News style aggregator with content ingestion and feed delivery, aggregating metadata from thousands of publishers, enabling infinite scrolling and article redirects, prioritizing availability and low latency.

Plan the system approach, define core entities (article, publisher, user), design a region-aware feed API with cursor-based pagination, and enable click tracking and redirection.

Examine the data collection and feed services in a news aggregator, covering data fetch, parsing, storage, and a cursor-based pagination to prevent drift with ULID UID generation.

Explains scaling a news aggregator with caching and push-on-update using a CDC pipeline. Keeps Redis caches fresh with near real-time updates, avoiding thundering herd and long DB queries.

Implement category-based feeds by filtering in memory on Redis-cached feeds, storing category in each article and applying the filter at the API level to avoid DB bottlenecks and cache explosion.

Think through the problem, defining functional and non-functional requirements. Design a scalable system with ingestion and feed service, cursor-based pagination, caching, and pre-computed feeds.

Design a Dropbox-like system that synchronizes files across devices, combining file storage with metadata management to track versions, locations, and user mappings.

Enable upload, download, and near real-time file sync across devices with public or private sharing, plus versioning, soft delete, and strong security for a scalable, durable, low-latency system.

Learn to design a Dropbox-style system with client apps, an API gateway, a metadata service, and chunked file storage, plus sync and notification flows for cross-device synchronization.

Explore deduplication and fingerprinting, including file and chunk level strategies, ref counting for safe cleanup, and content-defined chunking with rolling hashes to maximize reuse.

Learn how to design scalable file uploads using pre-signed URLs and multi-part transfers, enabling direct client-to-storage uploads, dedup checks, chunked progress, and backend coordination for metadata and assembly.

Learn how to enable fast, secure file downloads using backend-generated pre-signed URLs, direct storage access, and a CDN with edge caching, signed URLs, and versioned paths.

Explore a file sync system with os-level watchers, a sync queue and upload manager that batch, chunk and deduplicate changes, plus a hybrid WebSocket and polling model for remote-to-local updates.

Explore the control and data plane separation: clients detect changes, queue for sync, and upload to storage through CDN, while the file service stores metadata and uses auth-driven pre-signed URLs.

Design a geo-based routing, regionally isolated twitter-like platform using AWS Route 53, DynamoDB, SQS, and Redis Elastic Cache to merge regional posts into a compliant global feed.

Master system design by embracing its evolving journey, updating this course with real-world learnings, starting from a simple base picture, and iteratively refining designs through practice.