
Deploy an API gateway as a central reverse proxy that handles authentication, rate limiting, routing, logging, load balancing, caching, and service discovery for microservices.
Explore the Cap theorem and its tradeoffs among consistency, availability, and partition tolerance in distributed systems, highlighting strong, eventual, and tunable consistency and quorum-based approaches.
Distribute incoming traffic across multiple back end servers with a load balancer to prevent bottlenecks, enabling scalability and high availability through health checks, SSL termination, and routing decisions.
Learn load balancing algorithms that distribute traffic across servers to prevent overload and improve availability, including round robin, weighted round robin, least connections, least response time, and IP hash.
Explore the differences between SQL and NoSQL databases, including data models, schemas, scalability, query languages, and transaction support, to identify the best fit for your system design.
Compare long polling and WebSockets for real-time updates, explaining how HTTP's request-response model differs from duplex, persistent connections. Assess their pros, cons, and use cases for scalable apps.
Learn rate limiting in system design, including token bucket, leaky bucket, fixed window, and sliding window algorithms, their trade-offs, and practical implementation ideas.
Explore how service discovery coordinates dozens of microservices with a central service registry, enabling dynamic registration, health checks, and client-side or server-side routing, including sidecars and orchestrators.
Explore designing a parking garage system by clarifying functional and non-functional requirements, defining apis for reservation and payment, and building a scalable architecture with a database schema and api gateway.
Design a low-level parking garage system with single-level spots for compact, regular, and large vehicles; implement entry, exit, and availability using UML and Python patterns like singleton and observer.
System Design Masterclass, Design Scalable & Distributed Systems
Learn how to design scalable, reliable, and high-performance systems used by top tech companies like Google, Amazon, and Netflix.
Are you preparing for a system design interview or building the backend for a real-world application? This System Design Masterclass covers all the key concepts you need from APIs and load balancers to databases, caching, messaging queues, and distributed systems.
This course is designed for software engineers, backend developers, and architects who want to gain hands-on knowledge and confidently design large-scale systems.
What You'll Learn:
How to design REST APIs and work with API Gateways
Load balancing algorithms and how to avoid single points of failure (SPOF)
Caching strategies, eviction policies, and distributed caching systems (like Redis)
SQL vs NoSQL databases, database sharding, scaling, and indexing
WebSockets, message queues (Kafka, RabbitMQ), and asynchronous communication
CAP Theorem, ACID transactions, service discovery, Bloom filters, and more
How to prepare for system design interviews with real-world examples
Key System Design Topics Included:
RESTful APIs, Idempotency, Checksums
Load Balancing & Rate Limiting
Caching (LRU, LFU), CDNs, Distributed Caching
SQL vs NoSQL, Database Scaling, Sharding
WebSockets vs Long Polling
Message Queues, Stream vs Batch Processing
Fault Tolerance, High Availability, Proxies
Bloom Filters, Service Discovery, Concurrency
Why Take This Course?
Whether you're a developer, software architect, or job-seeker preparing for interviews, this course gives you:
essential system design concepts explained clearly and visually
System Design interview prep tips and frameworks used by FAANG engineers
Practical knowledge that you can apply to projects, products, or interviews
No Experience Needed
We start from the fundamentals and build up. By the end, you'll be confident in designing scalable systems that power real-world applications like YouTube, Uber, Netflix, or Amazon.
Who Should Take This Course?
Software Engineers preparing for FAANG-level interviews
Backend & Full Stack Developers working on scalable applications
Computer Science students looking to master system architecture
Anyone curious about how systems like YouTube, Uber, or Netflix are built
Enroll now and start designing like a systems architect!