Learn how to improve the speed and efficiency of your AWS Lambda function for CPU-intensive tasks. Find out how to increase the function’s memory and how it affects the CPU allocation.
Table of Contents
Question
A developer has written an AWS Lambda function. The function is CPU-bound. The developer wants to ensure that the function returns responses quickly.
How can the developer improve the function’s performance?
A. Increase the function’s CPU core count.
B. Increase the function’s memory.
C. Increase the function’s reserved concurrency.
D. Increase the function’s timeout.
Answer
B. Increase the function’s memory.
Explanation
The correct answer is B. Increase the function’s memory.
This answer is based on the documentation of AWS Lambda, which states that the amount of memory allocated to a Lambda function also determines how much CPU and network bandwidth are allocated to it. By increasing the function’s memory, the developer can also increase the function’s CPU power and network performance, which can improve the function’s speed and responsiveness. This is especially important for CPU-bound functions, which are functions that perform intensive computations and are limited by the CPU resources available.
The other options are not correct because:
- Option A: Increasing the function’s CPU core count is not possible, as Lambda does not expose this configuration option to developers. The number of CPU cores available to a Lambda function depends on the memory size and the underlying hardware. Therefore, the developer cannot directly increase the function’s CPU core count.
- Option C: Increasing the function’s reserved concurrency does not improve the function’s performance, but rather its scalability. Reserved concurrency is a feature that allows developers to set aside a portion of concurrency for a specific function. Concurrency is the number of requests that a function can process simultaneously. By increasing the reserved concurrency, the developer can ensure that the function has enough concurrency to handle incoming requests without being throttled by Lambda. However, this does not affect the performance of each individual invocation of the function.
- Option D: Increasing the function’s timeout does not improve the function’s performance, but rather its reliability. The timeout setting determines how long Lambda allows a function to run before stopping it. If the timeout is reached, Lambda terminates the function and returns an error. By increasing the timeout, the developer can allow more invocations to complete successfully without being interrupted by Lambda. However, this does not affect the speed or responsiveness of each invocation of the function.
Therefore, option B is the best answer for this question.
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