Which solution will meet this requirement?
Update the instance type of the Lambda function to a compute optimized instance with at least eight virtual CPU (vCPU).
Update the configuration of the Lambda function to use the latest Python runtime.
Increase the memory that is allocated to the Lambda function.
Configure a reserved concurrency on the Lambda function.
Explanations:
AWS Lambda does not use EC2 instance types; instead, it allocates resources based on memory settings. You cannot update the instance type like you would with EC2 instances.
While using the latest Python runtime can provide improvements, it is unlikely to significantly affect performance for image processing tasks compared to adjusting resource allocations.
Increasing the memory allocated to the Lambda function also increases the CPU available. Since Lambda allocates CPU power proportionally to the amount of memory configured, more memory can lead to faster processing times for CPU-intensive tasks like image processing.
Configuring reserved concurrency limits the number of concurrent executions but does not inherently improve the performance of the function itself. It is more related to managing throughput and ensuring availability.
I believe the answer is:
Increase the memory that is allocated to the Lambda function.