System Design Masterclass

Explore how APIs enable web and mobile apps through REST, GraphQL, and gRPC, contrast microservices with monoliths, and learn practical API design basics.

Deploy an API gateway as a central reverse proxy that handles authentication, rate limiting, routing, logging, load balancing, caching, and service discovery for microservices.

Scale your system by moving from vertical to horizontal scaling, and boost resilience with load balancing, caching, and CDNs, while adopting microservices, auto scaling, and multi-region deployment.

Define availability as uptime divided by uptime plus downtime, and outline strategies like redundancy, load balancing, failover, data replication, and monitoring to achieve high availability expressed in nines.

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.

Identify the single point of failure in a distributed system by mapping architecture and dependencies. Implement redundancy, load balancing, failover, data replication, chaos testing, and monitoring.

Identify how idempotency ensures the same outcome after repeated requests, and apply strategies like idempotency keys, upserts, and idempotent http methods in distributed systems.

Explore how checksums provide a data fingerprint for verification after transmission or storage. Learn about parity bits, CRCs, and cryptographic hashes like MD5 and SHA-256 to detect errors and tampering.

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.

Boost system performance and reduce latency by caching data in RAM and a content delivery network, and apply read/write strategies with eviction policies like LRU, LFU, FIFO, TTL.

Explore caching strategies such as read-through, cache aside, write-through, write around, and write back to optimize latency and data consistency.

Explore seven cache eviction strategies, from LRU and LFU to TTL and two-tiered caching, and learn how each balances speed, memory, and data freshness.

Understand distributed caching to scale data across multiple nodes, using data distribution, replication, sharding, and eviction policies like lru, lfu, and ttl, with dedicated or co-located caches.

Discover how a geographically distributed network of edge servers, guided by dns, delivers html, javascript, images, and videos with low latency and high availability.

Explore relational databases and NoSQL types: key-value, document, graph, wide column, and more, and learn how data models, scalability, and use cases guide system design.

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.

Explore acid transactions by illustrating atomicity, consistency, isolation, and durability. See how begin transaction and commit or rollback, with a write ahead log, preserve database integrity.

Explore how database indexes speed data retrieval by creating index structures on key columns, enabling lookups with pointers, and balancing overhead, maintenance, and support for b-trees, hash tables, and bitmaps.

Explore database sharding, a horizontal scaling technique that partitions data into shards using a shard key and routing queries across hash, range, or directory strategies.

Explore database scaling strategies to keep apps responsive as user data grows, including vertical scaling, indexing, sharding, vertical partitioning, caching, replication, materialized views, and denormalization.

Discover how WebSockets enable full duplex bidirectional, real time communication between client and server over a single TCP connection, delivering low latency for live updates and interactive apps.

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.

Explore how message queues enable decoupled, fault-tolerant asynchronous communication between producers and consumers, with types like point-to-point and pub-sub, and best practices for reliability and scalability.

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.

Learn how bloom filters use a bit array and multiple hash functions for space-efficient, probabilistic set membership with possible false positives and no false negatives.

Explore concurrency and parallelism, defining concurrency as progressing on multiple tasks via rapid context switching and threads, and parallelism as true simultaneous execution across cores.

Contrast batch and stream processing for data pipelines. Choose batch for scheduled, high-throughput workloads; choose stream for real-time insights using Kafka, Flink, or Kinesis.

Discover how system design interviews assess your ability to design scalable, reliable software; learn a structured Fang seven-step framework from clarifying requirements to trade-offs and scalability considerations.

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.

Master system design with Python across 30 topics, covering scalability, availability, cap theorem, caching, sql vs nosql, and reliability concepts. Build a solid mental model for interviews and scalable architectures.