Why advanced concepts handle production systems in LLD - Challenge Your Understanding

Challenge - 5 Problems

🧠 Conceptual

intermediate

Why is fault tolerance critical in production systems?

In production systems, why is fault tolerance considered a key advanced concept?

A It ensures the system continues operating despite failures, preventing downtime.

B It simplifies the system by removing error handling components.

C It reduces the need for backups by deleting faulty data automatically.

D It allows the system to run faster by ignoring errors.

💡 Hint

Think about what happens if a system crashes unexpectedly in production.

Fault tolerance means the system can handle errors or failures without stopping, which is essential to keep services available to users.

❓ Architecture

intermediate

Which architecture best supports scalability in production?

Which system architecture is best suited to handle increasing user load in a production environment?

A Monolithic architecture with a single server handling all requests.

B Microservices architecture with independent services scaling separately.

C Tightly coupled components sharing the same database.

D Single-threaded application running on one machine.

💡 Hint

Consider how parts of the system can grow independently to handle more users.

Microservices allow scaling individual services based on demand, improving scalability and fault isolation.

❓ scaling

advanced

How does horizontal scaling improve production system availability?

What is the main advantage of horizontal scaling in production systems?

A It reduces the number of servers to simplify management.

B It upgrades the CPU and memory of a single machine to handle more load.

C It stores all data on one server for faster access.

D It adds more machines to share the load, reducing single points of failure.

💡 Hint

Think about spreading work across multiple machines versus improving one machine.

Horizontal scaling adds more servers to distribute load and improve fault tolerance, enhancing availability.

❓ tradeoff

advanced

What is a tradeoff when using eventual consistency in production?

Choosing eventual consistency in a distributed system means:

A Data may be temporarily inconsistent but the system remains highly available.

B Data is always immediately consistent but system availability decreases.

C The system never loses data but becomes very slow.

D All data updates are blocked until all nodes confirm.

💡 Hint

Consider the balance between data accuracy and system uptime.

Eventual consistency allows temporary differences in data across nodes to keep the system available and responsive.

❓ estimation

expert

Estimate the required server capacity for a production system handling 1 million daily users

A production system expects 1 million daily active users, each making 10 requests per hour during 10 peak hours. Each request requires 100ms CPU time on average. Estimate the minimum number of servers needed if each server can handle 100 requests per second.

A Approximately 100 servers

B Approximately 3 servers

C Approximately 28 servers

D Approximately 10 servers

💡 Hint

Calculate total requests during peak, then requests per second, then divide by server capacity.

Total requests = 1,000,000 users * 10 requests/hour * 10 hours = 100 million requests/day. Peak hour requests = 1,000,000 * 10 = 10 million requests/hour. Requests per second = 10,000,000 / 3600 ≈ 2777. Servers needed = 2777 / 100 ≈ 28.