
Think at scale by moving from coding to designing systems that support millions of users. Break down problems, ask the right questions, and weigh tradeoffs with databases, caching, and microservices.
Master system design interviews by adopting an open-ended architect mindset: articulate your reasoning, handle ambiguity, and justify trade-offs among scalability, availability, performance, and cost.
Meet the instructor behind master system design, sharing real-world experience building scalable systems and explaining how they work behind the scenes, not just for interviews, and to simplify concepts.
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.
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.
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.
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.
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.
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.
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.
Are you ready to move beyond coding and start thinking like a senior engineer?
Master System Design is a complete, concept-driven course designed to help you build strong fundamentals and confidently design scalable, production-ready systems.
Most engineers struggle with system design not because they lack knowledge, but because they lack structured thinking. This course focuses on building that foundation first — helping you understand how to break down problems, identify bottlenecks, and make the right architectural decisions.
We don’t just cover theory. Instead, we take a practical, real-world approach.
You will learn how to design systems like file storage platforms, payment systems, chat applications, and large-scale distributed systems — step by step. Along the way, we will deeply explore concepts like scalability, load balancing, caching strategies, database design, microservices architecture, and failure handling techniques such as retries, circuit breakers, and idempotency.
This course also prepares you for system design interviews by teaching you how to:
Approach open-ended problems
Structure your answers clearly
Communicate your design effectively
Explain trade-offs like a senior engineer
Whether you are aiming for top product-based companies, preparing for senior-level roles, or building your own scalable applications, this course will give you the mindset and skills needed to succeed.
By the end of this course, you will not just understand system design — you will be able to confidently design systems that scale to millions of users.