System design interview structure in HLD - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

What is the primary goal of the initial requirements gathering phase in a system design interview?

During the first step of a system design interview, what is the main purpose of gathering requirements?

A To estimate the cost of the system implementation

B To immediately start drawing the architecture diagram

C To write code for the system components

D To understand the problem scope and clarify functional and non-functional requirements

💡 Hint

Think about what helps you know what to build before designing.

The initial phase focuses on understanding what the system should do and its constraints, which guides the design decisions.

❓ Architecture

intermediate

Which component is essential to handle high traffic in a scalable web system design?

In designing a web system that must handle millions of users, which component helps distribute user requests efficiently?

A Database index

B Load balancer

C Monolithic server

D Static HTML pages

💡 Hint

Think about how to spread work evenly across servers.

A load balancer distributes incoming traffic across multiple servers to prevent overload and improve availability.

❓ scaling

advanced

What is the main tradeoff when choosing between vertical and horizontal scaling?

When scaling a system, what is the key difference and tradeoff between adding more power to one server versus adding more servers?

A Vertical scaling requires rewriting code; horizontal scaling does not

B Vertical scaling is cheaper and unlimited; horizontal scaling is expensive and limited

C Vertical scaling increases power of one server but has limits; horizontal scaling adds servers and improves fault tolerance

D Vertical scaling improves network speed; horizontal scaling improves CPU speed

💡 Hint

Consider limits of hardware and benefits of multiple machines.

Vertical scaling boosts one machine's resources but hits hardware limits; horizontal scaling adds machines, improving capacity and fault tolerance.

❓ tradeoff

advanced

Which consistency model sacrifices immediate data accuracy for better availability in distributed systems?

In distributed system design, which consistency approach allows data to be temporarily out of sync to keep the system available?

A Eventual consistency

B Strong consistency

C Immediate consistency

D Strict serializability

💡 Hint

Think about systems that accept delays in data syncing to avoid downtime.

Eventual consistency allows temporary differences in data across nodes to maintain availability and partition tolerance.

❓ estimation

expert

Estimate the number of requests per second a system must handle if it serves 10 million users daily with an average of 5 requests per user.

Given 10 million users each making 5 requests per day, what is the approximate average number of requests per second the system should support?

A Approximately 578 requests per second

B Approximately 5000 requests per second

C Approximately 2000 requests per second

D Approximately 10000 requests per second

💡 Hint

Calculate total requests per day, then divide by seconds in a day (86400).

Total requests = 10,000,000 * 5 = 50,000,000 per day. Dividing by 86400 seconds gives about 578 requests per second.

Practice

1. What is the first step you should take when starting a system design interview?

easy

A. Discuss the deployment strategy

B. Start coding the solution immediately

C. Draw the final architecture diagram

D. Understand the problem requirements clearly

Solution

1. Step 1: Identify the initial focus in system design

   The first step is to understand the problem requirements clearly to know what needs to be built.

2. Step 2: Avoid premature actions

   Jumping to coding or drawing diagrams without understanding leads to wasted effort and confusion.

3. Final Answer:

   Understand the problem requirements clearly -> Option D

4. Quick Check:

   First step = Understand requirements [OK]

Hint: Always clarify requirements before designing [OK]

Common Mistakes:

• Starting design without clarifying requirements
• Jumping to coding too early
• Ignoring problem constraints

2. Which of the following is the correct order of steps in a typical system design interview?

easy

A. Design components -> Write code -> Understand requirements -> Define APIs

B. Understand requirements -> Define APIs -> Design components -> Discuss trade-offs

C. Write code -> Define APIs -> Understand requirements -> Discuss trade-offs

D. Discuss trade-offs -> Write code -> Design components -> Understand requirements

Solution

1. Step 1: Recall the logical flow of system design

   The correct flow starts with understanding requirements, then defining APIs, designing components, and finally discussing trade-offs.

2. Step 2: Eliminate incorrect sequences

   Writing code is usually not part of the initial design steps, so options with coding first are incorrect.

3. Final Answer:

   Understand requirements -> Define APIs -> Design components -> Discuss trade-offs -> Option B

4. Quick Check:

   Logical design flow = Understand requirements -> Define APIs -> Design components -> Discuss trade-offs [OK]

Hint: Follow problem -> APIs -> design -> trade-offs order [OK]

Common Mistakes:

• Starting with coding instead of design
• Skipping API definition
• Discussing trade-offs too early

3. During a system design interview, you propose a caching layer to improve performance. Which of the following is the most likely benefit you should mention?

medium

A. Increases database storage capacity

B. Eliminates the need for load balancers

C. Reduces database load and decreases response time

D. Automatically scales the number of servers

Solution

1. Step 1: Understand caching purpose in system design

   Caching stores frequently accessed data closer to the user, reducing database queries and improving response time.

2. Step 2: Evaluate other options

   Increasing storage, removing load balancers, or auto-scaling servers are unrelated to caching benefits.

3. Final Answer:

   Reduces database load and decreases response time -> Option C

4. Quick Check:

   Caching benefit = Reduced load and latency [OK]

Hint: Cache reduces DB hits and speeds up responses [OK]

Common Mistakes:

• Confusing caching with storage increase
• Thinking caching replaces load balancers
• Assuming caching auto-scales servers

4. You designed a system with a single database server. During the interview, the interviewer points out a potential bottleneck. What is the most likely issue?

medium

A. Single point of failure and limited scalability

B. Too many load balancers causing delays

C. Excessive caching leading to stale data

D. Overuse of microservices causing complexity

Solution

1. Step 1: Analyze single database server drawbacks

   A single database server can fail and cannot handle very high traffic, causing bottlenecks.

2. Step 2: Check other options for relevance

   Load balancers, caching, and microservices issues are unrelated to having a single DB server.

3. Final Answer:

   Single point of failure and limited scalability -> Option A

4. Quick Check:

   Single DB = bottleneck and failure risk [OK]

Hint: Single DB risks failure and limits scale [OK]

Common Mistakes:

• Blaming load balancers for DB bottleneck
• Confusing caching issues with DB limits
• Ignoring single point of failure risk

5. In a system design interview, after presenting your architecture, the interviewer asks you to handle sudden traffic spikes. Which approach best addresses this?

hard

A. Implement auto-scaling with load balancers to add/remove servers dynamically

B. Use a single powerful server to handle all traffic

C. Remove caching to reduce complexity

D. Store all data in a single database to simplify writes

Solution

1. Step 1: Understand traffic spike handling

   Auto-scaling with load balancers allows the system to add or remove servers based on traffic, handling spikes efficiently.

2. Step 2: Evaluate other options

   A single server cannot handle spikes well; removing caching or using one DB limits performance and scalability.

3. Final Answer:

   Implement auto-scaling with load balancers to add/remove servers dynamically -> Option A

4. Quick Check:

   Traffic spikes = Auto-scaling + load balancers [OK]

Hint: Use auto-scaling and load balancers for spikes [OK]

Common Mistakes:

• Relying on one server for high traffic
• Removing caching unnecessarily
• Ignoring scalability needs