Throughput, latency, and availability in HLD - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Throughput in a Web Service

Imagine a web service that handles user requests. Which of the following best describes throughput?

A The number of requests the service can handle per second.

B The time it takes for a single request to be processed.

C The percentage of time the service is operational.

D The amount of data transferred in a single request.

💡 Hint

Think about how many requests the system can complete over time.

Throughput measures how many requests a system can process in a given time, usually per second.

❓ Architecture

intermediate

Reducing Latency in a Distributed System

You have a distributed system with multiple servers across regions. Which architectural choice will most effectively reduce latency for users?

A Use a single powerful server to handle all requests.

B Deploy servers closer to users geographically.

C Store all data in a central database far from users.

D Increase the number of servers in a single data center.

💡 Hint

Latency depends on the time data takes to travel between user and server.

Deploying servers closer to users reduces the distance data travels, lowering latency.

❓ scaling

advanced

Scaling for High Availability

Your system must maintain high availability even during server failures. Which design choice best supports this?

A Schedule maintenance during peak hours to fix issues quickly.

B Use a single server with a powerful CPU and memory.

C Use multiple redundant servers with automatic failover.

D Store backups only once per week to save storage space.

💡 Hint

Think about how to keep the system running if one server stops working.

Redundancy and automatic failover ensure the system stays available despite failures.

❓ tradeoff

advanced

Tradeoff Between Latency and Throughput

In a system design, increasing throughput sometimes increases latency. Which scenario best explains this tradeoff?

A Adding more servers to handle requests in parallel.

B Processing each request immediately, reducing latency but lowering throughput.

C Using caching to serve requests faster without affecting throughput.

D Batch processing many requests together to improve throughput but causing delay for each request.

💡 Hint

Think about how grouping requests affects speed and quantity.

Batching increases throughput by processing many requests at once but adds waiting time, increasing latency.

❓ estimation

expert

Estimating System Availability

A system has 3 independent servers, each with 99.9% uptime. What is the approximate overall system availability if it requires at least one server to be up?

A 99.9999%

B 99.999%

C 99.0%

D 99.7%

💡 Hint

Calculate the chance all servers fail simultaneously, then subtract from 100%.

Availability = 1 - (probability all servers fail). Each server fails 0.1% = 0.001. All fail = 0.001^3 = 0.000000001. So availability ≈ 1 - 0.000000001 = 99.9999999%, closest option 99.9999% (A).

Practice

1. Which metric best describes how many requests a system can handle per second?

easy

A. Throughput

B. Latency

C. Availability

D. Scalability

Solution

1. Step 1: Understand throughput meaning

   Throughput measures the amount of work or requests a system can process in a given time.

2. Step 2: Compare with other metrics

   Latency measures response time, availability measures uptime, scalability is about growth capacity.

3. Final Answer:

   Throughput -> Option A

4. Quick Check:

   Throughput = Requests per second [OK]

Hint: Throughput = how much work done per time [OK]

Common Mistakes:

• Confusing latency with throughput
• Mixing availability with throughput
• Thinking scalability equals throughput

2. Which of the following correctly defines latency in system design?

easy

A. The total number of requests processed per second

B. The time taken to respond to a single request

C. The percentage of time the system is operational

D. The ability to add more servers to handle load

Solution

1. Step 1: Define latency

   Latency is the delay or time taken for a system to respond to one request.

2. Step 2: Eliminate other options

   The total number of requests processed per second describes throughput. The ability to add more servers to handle load describes scalability. The percentage of time the system is operational describes availability.

3. Final Answer:

   The time taken to respond to a single request -> Option B

4. Quick Check:

   Latency = Response time [OK]

Hint: Latency = response time per request [OK]

Common Mistakes:

• Confusing latency with throughput
• Thinking availability is latency
• Mixing scalability with latency

3. A system processes 1000 requests in 10 seconds. Each request takes 5 milliseconds to respond. What is the system's throughput and average latency?

medium

A. Throughput: 1000 requests/sec, Latency: 5 ms

B. Throughput: 100 requests/sec, Latency: 50 ms

C. Throughput: 10 requests/sec, Latency: 5 ms

D. Throughput: 100 requests/sec, Latency: 5 ms

Solution

1. Step 1: Calculate throughput

   Throughput = total requests / total time = 1000 / 10 = 100 requests per second.

2. Step 2: Understand latency

   Latency is given as 5 milliseconds per request.

3. Final Answer:

   Throughput: 100 requests/sec, Latency: 5 ms -> Option D

4. Quick Check:

   Throughput = 100, Latency = 5 ms [OK]

Hint: Throughput = total requests ÷ time; latency given directly [OK]

Common Mistakes:

• Dividing latency by number of requests
• Confusing throughput units
• Multiplying latency by total requests

4. A system claims 99.9% availability but is down for 10 minutes in a day. What is the actual availability and is the claim correct?

medium

A. Actual availability is 99.31%, claim is incorrect

B. Actual availability is 99.93%, claim is correct

C. Actual availability is 99.93%, claim is incorrect

D. Actual availability is 99.31%, claim is correct

Solution

1. Step 1: Calculate total minutes in a day

   24 hours x 60 minutes = 1440 minutes per day.

2. Step 2: Calculate availability

   Availability = (Total time - downtime) / Total time = (1440 - 10) / 1440 = 1430 / 1440 ≈ 0.9931 or 99.31%.

3. Step 3: Compare with claim

   Claim is 99.9%, actual is 99.31%, so claim is incorrect.

4. Final Answer:

   Actual availability is 99.31%, claim is incorrect -> Option A

5. Quick Check:

   Availability = 99.31%, Claim wrong [OK]

Hint: Availability = (uptime ÷ total time) x 100% [OK]

Common Mistakes:

• Using hours instead of minutes
• Incorrectly subtracting downtime
• Misreading percentage claim

5. You design a web service that must handle 10,000 requests per second with an average latency under 100 ms and 99.99% availability. Which design choice best balances these requirements?

hard

A. Use a single powerful server with caching to reduce latency

B. Use a database with strong consistency but no replication

C. Distribute load across multiple servers with load balancers and health checks

D. Optimize only latency by increasing CPU speed on one server

Solution

1. Step 1: Analyze throughput and availability needs

   10,000 requests/sec and 99.99% availability require scaling and fault tolerance.

2. Step 2: Evaluate design options

   Using a single powerful server with caching or optimizing CPU speed on one server risks overload and downtime. Using a database with strong consistency but no replication risks availability due to lack of fault tolerance. Distributing load across multiple servers with load balancers and health checks supports scaling and high availability.

3. Final Answer:

   Distribute load across multiple servers with load balancers and health checks -> Option C

4. Quick Check:

   Scaling + availability = load balancer + health checks [OK]

Hint: Scale horizontally with load balancers for throughput and availability [OK]

Common Mistakes:

• Relying on single server for high throughput
• Ignoring replication for availability
• Focusing only on latency without scaling