Lambda pricing model in AWS - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding AWS Lambda Pricing Components

Which of the following factors directly affect the cost of running an AWS Lambda function?

A The number of requests and the duration of each execution measured in milliseconds.

B The size of the deployment package and the number of environment variables used.

C The number of concurrent executions and the size of the Lambda function's memory allocation.

D The AWS region and the number of API Gateway endpoints connected.

💡 Hint

Think about what AWS charges for when you invoke a Lambda function.

AWS Lambda pricing is based on the number of requests and the duration of execution, which depends on the allocated memory and execution time. The deployment package size and environment variables do not affect pricing directly.

❓ service_behavior

intermediate

Effect of Memory Allocation on Lambda Cost

You have a Lambda function that runs for 1 second. You increase its memory from 128 MB to 512 MB. How does this change affect the cost per invocation?

A The cost per invocation doubles because memory increased four times but duration halves.

B The cost per invocation stays the same because duration is unchanged.

C The cost per invocation quadruples because memory increased four times.

D The cost per invocation increases linearly with memory size and duration.

💡 Hint

Remember that cost depends on both memory size and execution time.

Cost is calculated as memory size (in GB) multiplied by execution duration (in seconds). Increasing memory from 128 MB to 512 MB is a 4x increase, so cost per invocation quadruples if duration stays the same.

❓ Architecture

advanced

Optimizing Lambda Cost with Execution Duration

You have a Lambda function that processes data in 2 seconds with 256 MB memory. You optimize the code to run in 1 second but need 512 MB memory to do so. What is the impact on cost per invocation?

A Cost remains the same because duration halves and memory doubles.

B Cost doubles because memory doubles despite duration halving.

C Cost halves because duration halves despite memory doubling.

D Cost quadruples because memory doubles and duration halves.

💡 Hint

Calculate cost as memory size times duration.

Cost = memory (GB) * duration (seconds). Doubling memory and halving duration results in the same cost.

❓ security

advanced

Impact of Lambda Provisioned Concurrency on Pricing

Which statement correctly describes how enabling Provisioned Concurrency affects AWS Lambda pricing?

A Provisioned Concurrency only affects cold start times and does not change pricing.

B You pay a fixed hourly rate for the provisioned concurrency plus the usual request and duration charges.

C Provisioned Concurrency eliminates duration charges but increases request charges.

D Provisioned Concurrency replaces the request charges with a flat monthly fee.

💡 Hint

Think about what extra resource is reserved when you enable Provisioned Concurrency.

Provisioned Concurrency reserves execution environments, so you pay an hourly fee for that reservation in addition to normal request and duration charges.

✅ Best Practice

expert

Choosing Memory Size for Cost Efficiency

You want to minimize AWS Lambda cost for a function that runs variable workloads. Which approach best balances cost and performance?

A Set memory to the lowest possible value to minimize cost per millisecond, accepting longer execution times.

B Set memory high enough to reduce execution time significantly, even if cost per millisecond is higher.

C Randomly adjust memory size and monitor costs without analyzing execution time.

D Use a memory size that results in the lowest total cost, considering both memory and execution time together.

💡 Hint

Think about total cost = memory size * execution duration.

The best practice is to find the memory size that minimizes the product of memory and execution time, not just the lowest memory or fastest execution alone.

Practice

1. What two main factors determine the cost of an AWS Lambda function?

easy

A. Number of requests and compute time

B. Storage size and network bandwidth

C. Number of users and API calls

D. Memory size and database queries

Solution

1. Step 1: Understand AWS Lambda pricing basics

   AWS Lambda charges based on how many times your function runs (requests) and how long it runs (compute time).

2. Step 2: Identify the pricing factors

   Memory size affects compute time cost but the main factors are requests and compute time.

3. Final Answer:

   Number of requests and compute time -> Option A

4. Quick Check:

   Requests + compute time = cost [OK]

Hint: Remember: pay for calls and duration only [OK]

Common Mistakes:

• Confusing storage or bandwidth as pricing factors
• Thinking memory size alone determines cost
• Mixing API calls with requests

2. Which of the following is the correct way to express AWS Lambda pricing units?

easy

A. Memory in MB and network packets

B. Requests per hour and CPU cycles

C. Number of requests and GB-seconds

D. Storage in GB and function calls

Solution

1. Step 1: Recall AWS Lambda pricing units

   Lambda pricing is based on number of requests and compute time measured in GB-seconds (memory size x execution time).

2. Step 2: Match correct units

   Requests count how many times function runs; GB-seconds measure memory used over time.

3. Final Answer:

   Number of requests and GB-seconds -> Option C

4. Quick Check:

   Requests + GB-seconds = pricing units [OK]

Hint: Think requests and memory-time units [OK]

Common Mistakes:

• Using CPU cycles or network packets incorrectly
• Confusing storage with compute time
• Mixing units like MB with packets

3. If a Lambda function runs 1,000,000 times with 512 MB memory for 1 second each, which factor mainly increases the cost?

medium

A. Execution time of 1 second per request

B. Network bandwidth used by the function

C. Memory size doubling from 256 MB to 512 MB

D. Number of requests being 1,000,000

Solution

1. Step 1: Understand cost components

   Cost depends on requests and GB-seconds (memory size x execution time x requests).

2. Step 2: Analyze impact of memory size

   Doubling memory from 256 MB to 512 MB doubles GB-seconds, increasing cost significantly, but the number of requests (1,000,000) is the main driver of total cost.

3. Final Answer:

   Number of requests being 1,000,000 -> Option D

4. Quick Check:

   Requests x GB-seconds = total cost [OK]

Hint: Number of requests greatly impacts total cost [OK]

Common Mistakes:

• Ignoring number of requests effect
• Thinking network bandwidth affects Lambda cost
• Assuming execution time or memory alone drives cost

4. A developer notices their Lambda cost is higher than expected. They set memory to 1024 MB but function runs only 100 ms. What is the likely issue?

medium

A. Memory size is too high for short execution time

B. Number of requests is too low

C. Function execution time is too long

D. Free tier is not applied to this function

Solution

1. Step 1: Review memory and execution time relation

   Cost depends on memory size multiplied by execution time. High memory with short time still costs more than lower memory.

2. Step 2: Identify cost cause

   Setting memory to 1024 MB increases GB-seconds cost even if function runs only 100 ms.

3. Final Answer:

   Memory size is too high for short execution time -> Option A

4. Quick Check:

   High memory + short time can increase cost [OK]

Hint: High memory with short run still costs more [OK]

Common Mistakes:

• Assuming short execution time always means low cost
• Ignoring memory size impact
• Thinking free tier always applies

5. A company uses Lambda functions with 256 MB memory running 200 ms per request. They want to reduce cost without changing code. Which approach helps most?

hard

A. Switch to EC2 instances for better pricing

B. Reduce memory size to 128 MB if function still runs correctly

C. Increase number of requests to use free tier fully

D. Increase memory size to reduce execution time

Solution

1. Step 1: Understand cost relation to memory and time

   Cost = requests x memory size x execution time. Reducing memory lowers GB-seconds cost if function still works.

2. Step 2: Evaluate options

   Reducing memory to 128 MB saves cost if performance is acceptable. Increasing memory or requests raises cost. Switching to EC2 is a different model and may not be cheaper.

3. Final Answer:

   Reduce memory size to 128 MB if function still runs correctly -> Option B

4. Quick Check:

   Lower memory reduces GB-seconds cost [OK]

Hint: Lower memory if function still works to save cost [OK]

Common Mistakes:

• Increasing memory without checking cost impact
• Thinking more requests reduce cost
• Assuming EC2 always cheaper than Lambda