DVA-C02: How to Optimize AWS Lambda Performance for CPU-Bound Functions

Learn how to improve the performance of your AWS Lambda functions that are CPU-bound. This tutorial will show you how to adjust the memory size, use concurrency settings, and apply best practices to make your functions run faster and more efficiently.

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.

The reason is that the memory allocation of a Lambda function determines how much CPU and network bandwidth are allocated to the function. A CPU-bound function is a function that performs intensive computations and spends most of its time using the CPU resources. Increasing the memory allocation of a CPU-bound function can improve its performance by increasing the CPU power and speed. The developer can configure the memory allocation of a Lambda function from 128 MB to 10,240 MB, in 1 MB increments.

The other options are incorrect because they do not improve the function’s performance or they are not applicable:

A. Increasing the function’s CPU core count is not possible. The CPU core count of a Lambda function is determined by the memory allocation and cannot be configured separately. A Lambda function can have one or more CPU cores depending on the memory size.

C. Increasing the function’s reserved concurrency can improve the scalability and availability of the function, but not its performance. Reserved concurrency is a feature that allows the developer to set aside a portion of the concurrency limit for a specific function. Concurrency is the number of requests that a function can process simultaneously. Reserved concurrency can help to prevent throttling errors and ensure that the function has enough concurrency to handle the expected traffic. However, reserved concurrency does not affect the performance of each individual invocation of the function.

D. Increasing the function’s timeout can prevent the function from being terminated prematurely, but not improve its performance. Timeout is a feature that allows the developer to set a limit on how long a function can run before it is stopped. Timeout can help to avoid excessive charges and ensure that the function does not run longer than expected. However, timeout does not affect the speed or efficiency of each individual invocation of the function.

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