How to protect your APIs from abuse, control costs, and ensure fair usage. Covers token bucket, leaky bucket, fixed window, and sliding window algorithms with real implementation patterns.
The most debated architecture decision in software engineering. Learn what actually differentiates microservices from monoliths, when each is the right choice, and how to migrate without breaking everything.
How to decouple services, handle traffic spikes, and build resilient systems using message queues. Covers Kafka, RabbitMQ, SQS, and the patterns that power every large-scale distributed system.
The most common system design interview question. Walk through the complete design — from requirements to data model to scaling — with all the decisions explained.
How to scale reads, survive failures, and serve users globally. Understand synchronous vs asynchronous replication, read replicas, and the consistency trade-offs that come with each approach.
Why some queries take 50ms and others take 50 seconds — and how indexes fix it. Understand B-tree indexes, composite indexes, covering indexes, and when NOT to index.
Master consistent hashing for system design interviews. Learn how DynamoDB and CDNs scale data dynamically without reshuffling everything during node failures.
Every system design interview requires estimation. Learn the numbers, the method, and how to confidently estimate scale for any system.
DNS is the phonebook of the internet. Understanding how it works is essential for system design — from latency to failover to global load balancing.
CDNs are one of the most impactful performance optimizations you can make. Learn how they work, what they cache, and when to use them.
Caching is the single most effective way to improve system performance. Learn the strategies, patterns, and trade-offs you need to know.
Discover how load balancers scale distributed systems. Learn core load balancing algorithms like Round Robin, Least Connections, and Consistent Hashing.
A complete guide to choosing between relational (SQL) and non-relational (NoSQL) databases. Compare ACID vs BASE, scaling strategies, and real-world database examples.
ACID and BASE are two opposing models for database transactions. Learn what each guarantees, where they apply, and how to choose between them.
Struggling with the CAP theorem? Learn why you must choose between Consistency and Availability (CP vs AP), with real-world database examples like Cassandra and MongoDB.
What availability and reliability mean in distributed systems, how to measure them, and the patterns used to achieve high availability.
Two of the most important performance metrics in system design — what they mean, how they differ, and how to optimize for each.
Understand the two core approaches to scaling systems — vertical and horizontal — and when to use each in real-world architectures.
Master the core building blocks of system design. Learn horizontal vs vertical scaling, load balancing, and everything you need to ace your next engineering interview.