Load balancing for AI services in Prompt Engineering / GenAI - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is load balancing in AI services?

Load balancing is the process of distributing incoming AI service requests evenly across multiple servers or resources to ensure no single server is overwhelmed, improving speed and reliability.

beginner

Why is load balancing important for AI services?

It helps keep AI services fast and available by preventing any one server from getting too busy, which can cause delays or crashes.

intermediate

Name two common load balancing methods used in AI services.

Round Robin (requests go to servers in order) and Least Connections (requests go to the server with the fewest active connections).

intermediate

How does load balancing improve fault tolerance in AI services?

If one server fails, load balancers redirect requests to other healthy servers, keeping the AI service running smoothly.

intermediate

What role does health checking play in load balancing for AI services?

Health checks monitor servers to ensure they are working well; load balancers use this info to avoid sending requests to servers that are down or slow.

What does load balancing do in AI services?

A Deletes old AI data

B Increases the size of AI models

C Reduces the number of AI service users

D Distributes requests evenly across servers

Load balancing spreads requests evenly to keep AI services fast and reliable.

Which load balancing method sends requests to the server with the fewest active connections?

A Least Connections

B Weighted Distribution

C Random Selection

D Round Robin

Least Connections sends requests to the server with the fewest active connections to balance load.

How does load balancing help if one AI server crashes?

A It redirects requests to other servers

B It shuts down all servers

C It deletes user data

D It slows down the service

Load balancers redirect requests to healthy servers to keep the service running.

What is a health check in load balancing?

A A method to speed up AI predictions

B A way to train AI models

C A test to see if servers are working well

D A tool to increase server storage

Health checks monitor server status to avoid sending requests to bad servers.

Which of these is NOT a benefit of load balancing for AI services?

A Better reliability

B Increased server crashes

C Improved speed

D Fault tolerance

Load balancing reduces crashes by spreading load, not increasing them.

Explain in your own words why load balancing is important for AI services.

Think about what happens if one server gets too many requests.

Describe two common methods of load balancing and how they decide where to send requests.

One method cycles through servers, the other checks how busy servers are.

Practice

1. What is the main purpose of load balancing in AI services?

easy

A. To spread AI requests across multiple servers to keep response times fast

B. To increase the size of AI models automatically

C. To reduce the number of AI users at the same time

D. To store AI data in a single location

Solution

1. Step 1: Understand load balancing role

   Load balancing distributes incoming AI requests to multiple servers to avoid overload on one server.

2. Step 2: Identify the benefit

   This spreading keeps the AI service fast and responsive even when many users access it simultaneously.

3. Final Answer:

   To spread AI requests across multiple servers to keep response times fast -> Option A

4. Quick Check:

   Load balancing = spreading requests fast response [OK]

Hint: Load balancing means sharing work across servers [OK]

Common Mistakes:

• Thinking load balancing increases model size
• Believing it reduces user numbers
• Assuming it stores data in one place

2. Which of the following is a correct simple load balancing method for AI requests?

easy

A. Round-robin, where requests go to servers in order one by one

B. Randomly deleting requests to reduce load

C. Sending all requests to the first server only

D. Increasing request size to slow down processing

Solution

1. Step 1: Identify simple load balancing methods

   Round-robin sends requests to each server in turn, balancing load evenly.

2. Step 2: Check other options

   Deleting requests or sending all to one server causes problems, and increasing request size slows service.

3. Final Answer:

   Round-robin, where requests go to servers in order one by one -> Option A

4. Quick Check:

   Round-robin = simple balanced request distribution [OK]

Hint: Round-robin cycles through servers evenly [OK]

Common Mistakes:

• Thinking deleting requests helps load balancing
• Sending all requests to one server
• Confusing load balancing with slowing requests

3. Consider this Python code simulating load balancing with round-robin over 3 servers:

servers = ['S1', 'S2', 'S3']
requests = 5
for i in range(requests):
    server = servers[i % len(servers)]
    print(f'Request {i+1} sent to {server}')

What is the output for Request 4?

medium

A. Request 4 sent to S3

B. Request 4 sent to S1

C. Request 4 sent to S2

D. Request 4 sent to S4

Solution

1. Step 1: Understand the round-robin index calculation

   For request 4 (i=3), server index = 3 % 3 = 0, so server = 'S1'. But check carefully the code output.

2. Step 2: Check the printed output for request 4

   Request numbering starts at 1, so Request 4 corresponds to i=3, server = servers[3 % 3] = servers[0] = 'S1'. So output is 'Request 4 sent to S1'.

3. Final Answer:

   Request 4 sent to S1 -> Option B

4. Quick Check:

   Index 3 % 3 = 0, server S1 [OK]

Hint: Use modulo (%) to cycle server index [OK]

Common Mistakes:

• Off-by-one error in indexing servers
• Confusing request number with index
• Assuming server S4 exists

4. The following code tries to balance AI requests but has a bug:

servers = ['A', 'B']
requests = ['req1', 'req2', 'req3', 'req4', 'req5']
for i in range(len(requests)):
    server = servers[i // len(servers)]
    print(f'{requests[i]} sent to {server}')

What is the error?

medium

A. The print statement syntax is wrong

B. The servers list is empty

C. Requests list is empty

D. Using integer division (//) instead of modulo (%) causes index error

Solution

1. Step 1: Analyze the index calculation for server selection

   The code uses i // len(servers) which is integer division, so for i=2 and len(servers)=2, index = 1, which is valid, but for larger i it can go out of range.

2. Step 2: Identify correct operator for cycling

   Modulo (%) should be used to cycle through server indices repeatedly, not integer division.

3. Final Answer:

   Using integer division (//) instead of modulo (%) causes index error -> Option D

4. Quick Check:

   Use % to cycle indices, not // [OK]

Hint: Use % for cycling indices, not // [OK]

Common Mistakes:

• Confusing // with %
• Assuming empty lists cause error here
• Thinking print syntax is wrong

5. You manage an AI service with 4 servers. During peak hours, requests spike to 1000 per minute. Which load balancing strategy best ensures fast responses and avoids server overload?

hard

A. Send all requests to the fastest server only

B. Randomly drop 50% of requests to reduce load

C. Use round-robin to evenly distribute requests across all servers

D. Assign requests only to the first two servers

Solution

1. Step 1: Understand the problem of request spikes

   High request volume can overload servers if not balanced well, causing slow responses or failures.

2. Step 2: Evaluate load balancing options

   Round-robin evenly spreads requests, preventing overload. Sending all to one server or only two servers risks overload. Dropping requests reduces service quality.

3. Final Answer:

   Use round-robin to evenly distribute requests across all servers -> Option C

4. Quick Check:

   Round-robin = balanced load, fast response [OK]

Hint: Spread requests evenly to avoid overload [OK]

Common Mistakes:

• Overloading one or two servers
• Dropping requests unnecessarily
• Ignoring load balancing benefits