Understand the purpose of system design interviews, focusing on scalability, architecture decisions, trade-offs, and real-world problem-solving skills.

Master functional vs. non-functional requirements in system design, emphasizing scalability, performance, and trade-offs for building robust, real-world systems.

Master back-of-the-envelope estimation to assess scalability, performance, and trade-offs using quick calculations in system design interviews.

Learn what to avoid in system design interviews—like skipping trade-offs, ignoring requirements, poor communication, and rigid thinking.

Get familiar with core system design concepts, key architectural components, and building blocks of scalable, distributed software systems.

Explore key characteristics of distributed systems, including scalability, reliability, availability, efficiency, fault tolerance, and manageability.

Learn how load balancing improves scalability and availability by distributing traffic using smart algorithms, health checks, and redundancy techniques.

Learn caching strategies to improve system performance, including cache types, eviction policies, read/write methods, and cache invalidation techniques.

Learn data partitioning techniques—horizontal, vertical, hybrid—and partitioning criteria to scale databases, improve performance, and balance workloads.

Understand how database indexes optimize query performance, enable efficient lookups, and impact write operations in large-scale systems.

Learn how forward and reverse proxies improve security, caching, and traffic control by mediating communication between clients and servers.

Learn how redundancy and replication improve system reliability and availability through failover strategies and synchronous, asynchronous, and semi-synchronous replication.

Compare relational and non-relational databases to understand schema flexibility, scalability, ACID compliance, and ideal use cases for each.

Understand why distributed systems must trade off between consistency, availability, and partition tolerance—only two of the three can be guaranteed at any time.

Learn how PACELC extends CAP by showing that even without partitions, distributed systems must balance latency and consistency in replicated environments.

Learn the architecture of scalable systems using consistent hashing for efficient data partitioning, replication, and dynamic node management.

Understand the system design of real-time communication protocols for scalable push-based updates between client and server.

Explore space-efficient system design using Bloom filters for fast, probabilistic membership checks with minimal memory and no false negatives.

Design highly available distributed systems using quorum-based consistency models to coordinate read/write operations across replicated nodes.

Understand the architecture of leader-based replication in distributed systems for consistent writes, fault tolerance, and coordinated data synchronization.

Learn how distributed systems use heartbeat signals to detect server failures and maintain reliable request routing and availability.

Explore how distributed systems ensure data integrity by using checksums to detect and prevent data corruption during transmission.

Test your understanding of system design basic concepts.

Demonstrating trade-offs shows maturity, critical thinking, and real-world design skills crucial for scalable, practical system architecture.

Explore consistency models in distributed systems, comparing strong and eventual consistency in terms of latency, availability, accuracy, and scalability trade-offs.

Understand the difference between latency and throughput, and explore strategies to optimize response time and data processing capacity in systems.

Understand key differences between ACID and BASE database models, balancing consistency, availability, scalability, and fault tolerance in distributed systems.

Explore read-through vs write-through caching strategies for improving read performance, data consistency, and integrity in scalable systems.

Compare batch vs stream processing in system design—complexity, resource efficiency, continuous vs scheduled data flow, and real-time responsiveness.

Understand differences between Load Balancer and API Gateway in scalable architectures—traffic distribution, request routing, API management, and availability.

Explore API Gateway vs Direct Service Exposure in distributed systems—compare centralized routing and security with direct access and reduced latency.

Understand how proxies and reverse proxies manage client and server traffic in distributed system design to improve security, caching, and scalability.

Learn the difference between API Gateways and Reverse Proxies in distributed systems, focusing on routing, security, load balancing, and orchestration.

Compare SQL vs NoSQL databases based on schema structure, scalability, ACID compliance, flexibility, and best use cases in system design.

Understand Primary-Replica vs Peer-to-Peer replication models, including data flow, consistency, scalability, fault tolerance, and use cases.

Learn the differences between data compression and deduplication for optimizing storage—focus, scope, efficiency, and best-use scenarios.

Understand server-side vs client-side caching—how they differ in location, control, performance impact, and best use across web apps.

Learn the architectural differences between REST and RPC, including stateless resource handling vs. procedure calls, flexibility, scalability, and performance trade-offs.

Compare real-time delivery strategies—Polling, Long-Polling, WebSockets, and Webhooks—for scalable, event-driven system communication.

Learn when to use a Content Delivery Network vs direct server hosting based on traffic scale, geographic distribution, and caching efficiency.

Learn serverless system design benefits like dynamic scaling and reduced ops versus traditional server hosting with full control and overhead.

Explore the architecture of stateful vs stateless systems, comparing session handling, scalability, and design trade-offs for APIs and web services.

Explore hybrid cloud vs all-cloud storage architectures, balancing scalability, compliance, and control for secure, flexible enterprise data strategies.

Learn how Token Bucket and Leaky Bucket algorithms manage network traffic shaping, rate limiting, and handling of bursty data.

Explore how system design varies for read-heavy and write-heavy workloads with techniques like batching, replication, and data partitioning.