A company is launching a photo-sharing app on AWS. Users upload images to an S3 bucket. A Lambda function generates thumbnails and stores them in another S3 bucket. During development the Lambda function sometimes takes more than 2 minutes to generate thumbnails, but the company requires each image to be processed in under 30 seconds. What change should the developer make to meet this requirement?

Increasing a Lambda function's memory allocation directly increases its proportional CPU, network, and disk I/O resources. This often leads to faster execution times for CPU-bound or I/O-bound tasks like image processing, helping to meet the 30-second requirement. Incorrect options: Lambda functions do not have a configurable vCPU allocation in the same way EC2 instances do; CPU resources scale with memory. Lambda functions do not have instance types like EC2 (e.g., m6a.4xlarge). Their underlying infrastructure is managed by AWS. Lambda functions do not support burstable performance in the same way EC2 instances do. Performance scales with allocated memory.