Token bucket algorithm in Rest API - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the Token Bucket Algorithm?

It is a method to control the rate of data flow by using tokens that allow sending data only when tokens are available.

beginner

How does the token bucket refill work?

Tokens are added to the bucket at a fixed rate until the bucket reaches its maximum capacity.

beginner

What happens when there are no tokens in the bucket?

No data can be sent until new tokens are added to the bucket.

intermediate

Why use the Token Bucket Algorithm in REST APIs?

To limit the number of requests clients can make in a time period, preventing overload and ensuring fair use.

intermediate

What is the difference between Token Bucket and Leaky Bucket algorithms?

Token Bucket allows bursts of traffic up to bucket size, while Leaky Bucket enforces a steady output rate without bursts.

In the Token Bucket algorithm, what does a token represent?

A A data packet

B Permission to send a unit of data

C A time interval

D A user request

Each token allows sending one unit of data, controlling the flow rate.

What happens when the token bucket is full and new tokens arrive?

A Tokens are discarded

B Tokens are stored in overflow

C Tokens replace old tokens

D Bucket size increases

Tokens beyond the bucket capacity are discarded to limit burst size.

Which scenario best fits using the Token Bucket algorithm?

A Randomly dropping requests

B Enforcing a strict fixed rate with no bursts

C Blocking all requests after a limit

D Allowing bursts of requests up to a limit

Token Bucket allows bursts up to the bucket size, then limits further requests.

How does the Token Bucket algorithm help REST APIs?

A By caching API responses

B By encrypting API requests

C By limiting request rate to prevent overload

D By logging user activity

It controls how many requests a client can send in a time frame.

What is the main difference between Token Bucket and Leaky Bucket algorithms?

A Token Bucket allows bursts; Leaky Bucket enforces steady rate

B Leaky Bucket allows bursts; Token Bucket enforces steady rate

C Both allow unlimited bursts

D Both enforce strict fixed rates

Token Bucket supports bursts by accumulating tokens; Leaky Bucket smooths traffic.

Explain how the Token Bucket algorithm controls the rate of requests in a REST API.

Think about tokens as tickets to send requests.

Describe the difference between Token Bucket and Leaky Bucket algorithms and when you might use each.

Consider how each handles sudden spikes in requests.

Practice

1.

What is the main purpose of the token bucket algorithm in REST APIs?

easy

A. To encrypt API responses

B. To store user data securely

C. To control the rate of incoming requests by using tokens

D. To manage database connections

Solution

1. Step 1: Understand the token bucket algorithm concept

   The token bucket algorithm limits how many requests can be processed by controlling tokens that refill over time.

2. Step 2: Identify the purpose in REST APIs

   It helps prevent too many requests at once, protecting the server from overload.

3. Final Answer:

   To control the rate of incoming requests by using tokens -> Option C

4. Quick Check:

   Token bucket controls request rate = C [OK]

Hint: Token bucket limits request rate using tokens [OK]

Common Mistakes:

• Confusing token bucket with data storage
• Thinking it encrypts data
• Assuming it manages database connections

2.

Which of the following is the correct way to represent a token bucket refill rate in pseudocode?

1. refill_rate = tokens_per_second
2. refill_rate = seconds_per_token
3. refill_rate = max_tokens * time
4. refill_rate = tokens / max_tokens

easy

A. refill_rate = seconds_per_token

B. refill_rate = tokens_per_second

C. refill_rate = max_tokens * time

D. refill_rate = tokens / max_tokens

Solution

1. Step 1: Understand refill rate meaning

   The refill rate is how many tokens are added per second to the bucket.

2. Step 2: Match with options

   refill_rate = tokens_per_second correctly shows tokens added per second, which is the refill rate.

3. Final Answer:

   refill_rate = tokens_per_second -> Option B

4. Quick Check:

   Refill rate = tokens per second [OK]

Hint: Refill rate means tokens added each second [OK]

Common Mistakes:

• Confusing refill rate with time per token
• Multiplying max tokens by time incorrectly
• Using ratios instead of rates

3.

Given a token bucket with max_tokens = 5, refill_rate = 1 token/second, and an empty bucket at time 0, what is the number of tokens available at time 3 seconds?

medium

A. 3 tokens

B. 5 tokens

C. 0 tokens

D. 1 token

Solution

1. Step 1: Calculate tokens refilled after 3 seconds

   Since refill rate is 1 token per second, after 3 seconds, 3 tokens are added.

2. Step 2: Check max tokens limit

   The bucket max is 5 tokens, so 3 tokens fit without exceeding the max.

3. Final Answer:

   3 tokens -> Option A

4. Quick Check:

   3 seconds * 1 token/sec = 3 tokens [OK]

Hint: Multiply seconds by refill rate, cap at max tokens [OK]

Common Mistakes:

• Assuming bucket fills instantly to max
• Ignoring max token limit
• Using refill rate incorrectly

4.

Consider this pseudocode snippet for token bucket check:
if tokens <= 0:
  reject_request()
else:
  tokens -= 1
  allow_request()
What is the bug in this logic?

medium

A. It should check if tokens > 0 before allowing

B. It should increase tokens instead of decreasing

C. It should reject when tokens > 0

D. It should check if tokens < 1, not <= 0

Solution

1. Step 1: Recall proper token bucket logic

   To consume 1 token, check if tokens >= 1 before decrementing (equivalent to reject if tokens < 1).

2. Step 2: Identify the bug

   The code rejects only if tokens <= 0. For fractional tokens (common in real implementations), if 0 < tokens < 1, it allows the request, decrementing to negative, which is incorrect.

3. Final Answer:

   It should check if tokens < 1, not <= 0 -> Option D

4. Quick Check:

   Reject if tokens < 1 [OK]

Hint: Allow only if tokens >= 1 [OK]

Common Mistakes:

• Using <= 0 instead of < 1 causes off-by-one errors
• Increasing tokens on request instead of decreasing
• Rejecting requests when tokens are available

5.

You want to implement a token bucket that allows bursts of up to 10 requests and refills tokens at 2 tokens per second. If a client sends 15 requests instantly after being idle for 3 seconds, how many requests will be allowed immediately?

hard

A. 6 requests

B. 5 requests

C. 15 requests

D. 10 requests

Solution

1. Step 1: Calculate tokens available after 3 seconds idle

   Refill rate is 2 tokens/second, so after 3 seconds: 2 * 3 = 6 tokens. Max tokens allowed is 10, so bucket fills to 6 tokens.

2. Step 2: Consider burst capacity

   Since the bucket max is 10, if it was full before idle, it would have 10 tokens. But starting empty, after 3 seconds it has 6 tokens.

3. Step 3: Determine allowed requests

   The client sends 15 requests instantly, but only 6 tokens are available, so only 6 requests allowed immediately.

4. Final Answer:

   6 requests -> Option A

5. Quick Check:

   3 sec * 2 tokens/sec = 6 tokens available [OK]

Hint: Tokens = min(max_tokens, refill_rate * idle_time) [OK]

Common Mistakes:

• Assuming bucket always full at max tokens
• Allowing more requests than tokens available
• Ignoring refill rate and idle time