System Design

Understand API gateways as the single entry point for microservices. Learn routing, authentication, rate limiting, request/response transformation, and circuit breaking.

Learn different caching patterns and when to use them to improve application performance and reduce database load.

Master the CAP theorem: understand why you can only guarantee two of Consistency, Availability, and Partition tolerance. Learn real-world trade-offs and examples.

Understand Content Delivery Networks (CDNs), how they reduce latency, edge caching strategies, cache invalidation, and designing a CDN architecture.

Learn the circuit breaker pattern for fault tolerance. Understand states (closed, open, half-open), implementation, and preventing cascading failures.

Learn consistent hashing for distributed systems. Understand how it enables efficient data distribution, handles node failures, and minimizes data movement during rebalancing.

Master CQRS (Command Query Responsibility Segregation): separate read and write models, when to use it, and implementation patterns.

Master database sharding strategies: horizontal partitioning, shard key selection, cross-shard queries, rebalancing, and handling failures in sharded systems.

Master event-driven architecture: event sourcing, CQRS, event streaming, event choreography vs orchestration, and building scalable event-driven systems.

Learn event sourcing: storing state changes as events, rebuilding state, event replay, and when event sourcing is the right choice.

Design for high availability: redundancy, failover strategies, health checks, circuit breakers, and achieving 99.9%+ uptime in distributed systems.

Understand the difference between horizontal (scale-out) and vertical (scale-up) scaling, their trade-offs, and when to use each approach.

Learn database indexing strategies: B-tree, hash indexes, composite indexes, covering indexes, and how to design indexes for optimal query performance.

Distribute incoming requests across multiple servers to improve performance, reliability, and scalability.

Compare message queue systems: Kafka for event streaming vs RabbitMQ for traditional messaging. Learn use cases, patterns, and when to choose each.

Master microservices architecture: service decomposition, communication patterns, data management, deployment strategies, and challenges like distributed transactions.

Compare monolithic and microservices architectures. Understand when to choose each, migration strategies, and the trade-offs involved in architectural decisions.

Learn rate limiting algorithms (token bucket, leaky bucket, sliding window), distributed rate limiting, and how to implement rate limiting in high-traffic systems.

Master Redis as a caching solution. Learn Redis data structures, persistence options, replication, clustering, and common patterns for distributed caching.

Learn database replication strategies: master-slave, master-master, synchronous vs asynchronous replication, and handling replication lag.

Compare REST and GraphQL API designs. Understand when to use each, their trade-offs, and how to design efficient APIs for different use cases.

Master retry strategies: exponential backoff, jitter, maximum retries, and how to implement robust retry logic in distributed systems.

Learn how reverse proxies work, their benefits (SSL termination, load balancing, security), and how to configure them. Understand the difference between reverse proxy and forward proxy.

Learn the Saga pattern for managing distributed transactions. Understand choreography vs orchestration, compensating transactions, and handling failures.