System Design

Understand the fundamental request-response architecture where clients make requests and servers provide resources or services.

Learn the key performance metrics used to evaluate systems — how fast, how much, and how reliably a system responds.

Understand the fundamental impossibility result that forces distributed systems to choose between consistency, availability, and partition tolerance.

Practice quick math to estimate system requirements like storage, bandwidth, and QPS before diving into design.

You can reason about basic system properties, trade-offs, and capacity requirements.

Learn how domain names resolve to IP addresses and how the HTTP protocol structures web communication.

Compare the major API design paradigms — when to use resource-oriented REST, flexible GraphQL, or efficient RPC.

Understand persistent and push-based communication for real-time features like chat, notifications, and live feeds.

Learn asynchronous communication patterns using queues (RabbitMQ, SQS) and event logs (Kafka) to decouple producers and consumers.

You understand how services communicate synchronously and asynchronously.

Understand ACID transactions, schemas, normalization, indexing, and when relational databases are the right choice.

Explore key-value, document, column-family, and graph databases — their data models, strengths, and ideal use cases.

Learn cache-aside, write-through, write-back, and eviction policies to reduce latency and database load.

Understand horizontal and vertical partitioning strategies, shard keys, and how to distribute data across multiple nodes.

Learn leader-follower, multi-leader, and leaderless replication — how data is copied across nodes for durability and read scaling.

Understand how unstructured data like images, videos, and files are stored and served using systems like S3 or GCS.

You can choose, configure, and scale appropriate storage solutions.

Learn how traffic is distributed across servers using round-robin, least connections, consistent hashing, and L4/L7 balancers.

Compare scaling up a single machine versus scaling out with many machines, and understand when each is appropriate.

Understand how CDNs cache and serve static content from edge locations close to users to reduce latency.

Learn algorithms (token bucket, sliding window) and strategies to protect services from being overwhelmed by excessive requests.

Understand how systems dynamically add or remove compute resources based on demand using metrics and policies.

You can design systems that handle growth in traffic and data gracefully.

Understand strong, eventual, causal, and read-your-writes consistency — what guarantees each provides and their costs.

Learn how distributed nodes agree on values using protocols like Raft and Paxos, and why this is fundamentally hard.

Understand two-phase commit, sagas, and compensating transactions for maintaining data integrity across services.

Learn how to decompose a monolith into independently deployable services, including service boundaries, communication, and data ownership.

Understand how services find each other dynamically using registries (Consul, etcd, ZooKeeper) and DNS-based discovery.

You can reason about consistency, coordination, and failure in multi-node architectures.

Learn continuous integration, delivery pipelines, and deployment patterns like blue-green, canary, and rolling updates.

Understand Docker containers and Kubernetes orchestration for packaging, deploying, and managing services at scale.

Learn how to instrument systems with metrics, structured logs, and distributed tracing to detect and diagnose issues.

You can deploy, operate, and observe production systems.

Understand identity verification (OAuth, JWT, SSO) and access control models (RBAC, ABAC) for securing systems.

Learn TLS for data in transit, encryption at rest, key management, and how to protect sensitive user data.

Master circuit breakers, retries with backoff, bulkheads, and graceful degradation to keep systems running when things fail.

Understand RPO, RTO, backup strategies, and multi-region failover planning for business continuity.

You can design systems that are secure and resilient to failures.

Apply fundamentals to design a simple but scalable system — hashing, storage, redirection, and analytics.

Design a messaging system handling presence, delivery guarantees, group chats, and message storage at scale.

Design a feed system dealing with fan-out, ranking, caching, and handling millions of users and posts.

Design a multi-channel notification platform handling prioritization, deduplication, rate limiting, and user preferences.

Design a cache system like Memcached or Redis — consistent hashing, replication, eviction, and cluster management.

You can apply system design principles end-to-end to solve real-world problems confidently.