Design Interview Fundamentals Rylan Liu Pdf | System

Before designing, you need to understand the scale of the system. This determines whether you need a single database or a massive distributed cluster. Daily Active Users and Monthly Active Users.

Load balancers distribute incoming network traffic across multiple servers to ensure high availability and reliability. Common routing algorithms include Round Robin, Least Connections, and Consistent Hashing (essential for sharding and distributed caching). Asynchronous Processing and Queues

| Component | Interview Core Question | Liu’s Takeaway | | :--- | :--- | :--- | | | Round Robin vs Least Load? | Layer 4 (IP) vs Layer 7 (HTTP). Use Layer 7 for microservices. | | Database (SQL vs NoSQL) | Is your data relational or just JSON blobs? | SQL for consistency (Banking). NoSQL for scale (Amazon cart). | | Cache | When to invalidate? | Write-through (slow, consistent) vs Write-behind (fast, risky). Cache-aside is the interview standard. | | CDN | Who serves static assets? | Push (you upload) vs Pull (cache auto-grabs). Use Pull for most interviews. | | Message Queue | Need async processing? | Decouples producers from consumers. Essential for peak load smoothing. | System Design Interview Fundamentals Rylan Liu Pdf

You must quantify the problem. Ask these three question buckets:

: It provides a structured approach for answering questions coherently, ensuring you cover everything from clarifying requirements to discussing trade-offs. Before designing, you need to understand the scale

(e.g., handling geospatial indexing and matching algorithms)

Helps candidates seamlessly navigate from ambiguous, high-level user requirements to precise, detailed component-level architectures. | Layer 4 (IP) vs Layer 7 (HTTP)

: Includes end-to-end designs for common interview questions such as: Ridesharing Services (e.g., Uber/Lyft) Instagram-like platforms Rate Limiters Chat Applications Cloud File Storage (e.g., Dropbox/Google Drive) Strategic Framework

Adding more machines and introducing a load balancer.

Best for unstructured, high-volume data requiring rapid horizontal scaling (e.g., chat histories, social media feeds). Key-value, document, wide-column, and graph databases fit here. 3. Distributed Systems Theory Every Engineer Must Know

The application manages fetching data from the DB and populating the cache. Database Selection and Scaling