Cache-aside, Read-through, Write-through, Write-behind.
Are you preparing for a like Meta or Google, or
| Concept | Key Interview Focus | Practical Example | | :--- | :--- | :--- | | (Vertical vs. Horizontal) | Understand the limits of vertical scaling (adding more power to a single machine). Focus on horizontal scaling, where you add more machines to distribute load. | Discuss how moving from a single server to a cluster of servers helps you handle millions of concurrent users. | | Database Trade-offs (SQL vs. NoSQL) | Evaluate if the data is highly structured (relational) or unstructured (non-relational), and whether the workload is read-heavy, write-heavy, or both. | For a chat application with high message volume, NoSQL might be chosen for its write scalability, whereas a banking system would require SQL for its strict transactional guarantees. | | Caching (Redis, Memcached) | Be specific about caching strategies: write-through, write-around, or write-behind. Identify what to cache (e.g., user session data) and what not to cache (e.g., real-time stock prices). | A newsfeed system would heavily cache frequently accessed posts from the last 24 hours to reduce load on the database. | | Load Balancing (Round-robin, Hashing) | Explain how a load balancer distributes incoming requests across a pool of servers. Mention how session persistence (sticky sessions) can be handled. | Placing a load balancer (e.g., NGINX, HAProxy) in front of a cluster of application servers to ensure no single server becomes overwhelmed. | | Message Queues (Kafka, RabbitMQ) | Recognize scenarios requiring asynchronous processing. Describe how a queue can decouple producers from consumers, providing fault tolerance and load leveling. | When uploading a video, the system can return a "processing" status immediately while a background worker processes the video, picked from a queue. | | Content Delivery Network (CDN) | Identify when to use a CDN for serving static assets (images, CSS, JavaScript) geographically closer to users to reduce latency. | For a global social media platform, user profile pictures would be served via a CDN to ensure fast loading times worldwide. | | Database Replication | Distinguish between master-slave replication (for read-heavy workloads) and master-master replication (for higher write availability). Explain how it improves fault tolerance. | Configuring a database cluster with one master node for writes and multiple read replicas to handle a large volume of search queries. | | Database Sharding (Horizontal Partitioning) | Explain how data is distributed across multiple databases based on a shard key. Discuss the challenges of re-sharding and cross-shard queries. | Sharding user data by user_id across 10 database servers to handle billions of user profiles. | | Rate Limiting | Explain how APIs are protected from abuse (e.g., DoS attacks) by limiting the number of requests a user can make in a given time window. | An API Gateway that allows only 100 requests per minute from a single IP address for a free-tier service. | | Consistent Hashing | Describe its role in distributed systems for minimizing data movement when servers are added or removed, often used in load balancing and sharding. | Explaining how consistent hashing is used behind the scenes in a distributed caching system like Redis Cluster or Amazon DynamoDB. | | CAP Theorem (Consistency, Availability, Partition Tolerance) | Analyze a real-world scenario and state the fundamental trade-offs: you can only guarantee two of these three properties at any given time. | Designing a banking system (CP) vs. designing a social media feed (AP). |
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Best for unstructured data, high write throughput, and massive scale. Includes Key-Value (Redis), Document (MongoDB), Columnar (Cassandra), and Graph (Neo4j) databases. The 4-Step Framework for the Interview
Every read receives the most recent write or an error.
Choosing the right storage layer depends entirely on the data access patterns: Cache-aside, Read-through, Write-through, Write-behind
Every read receives the most recent write or an error.
: Vertical vs. horizontal scaling and when to use each.
"System Design Interview Fundamentals" by Rylan Liu is an essential resource for anyone preparing for a system design interview. With its comprehensive coverage of key topics, expert advice, and verified PDF version, this book is a must-have for software engineers looking to ace their next interview. Focus on horizontal scaling, where you add more
Highly regarded for its structure and practical application of theory to real-world scenarios. Review Note:
: Perform back-of-the-envelope calculations for daily active users (DAU), read/write ratios, network bandwidth requirements, and multi-year storage accumulation.