Which solution will meet these requirements?
Configure reserved concurrency for the Lambda functions. Decrease the memory allocated to the Lambda functions.
Configure reserved concurrency for the Lambda functions. Increase the memory according to AWS Compute Optimizer recommendations.
Configure provisioned concurrency for the Lambda functions. Decrease the memory allocated to the Lambda functions.
Configure provisioned concurrency for the Lambda functions. Increase the memory according to AWS Compute Optimizer recommendations.
Explanations:
Decreasing memory will reduce CPU power, increasing processing time for CPU-intensive tasks. This does not optimize costs or maintain latency.
Reserved concurrency can prevent Lambda from scaling to meet high concurrency demands, potentially impacting latency. Increasing memory could help with processing time but may still not meet high throughput needs.
Provisioned concurrency ensures Lambda readiness but decreasing memory limits CPU power, potentially slowing down CPU-intensive tasks and increasing costs over time.
Provisioned concurrency helps maintain readiness and latency, while increasing memory (and therefore CPU power) optimizes performance and reduces compute duration, lowering overall costs.
I estimate that the answer is:
Configure provisioned concurrency for the Lambda functions. Increase the memory according to AWS Compute Optimizer recommendations.
I deduce that the answer is:
Configure provisioned concurrency for the Lambda functions. Increase the memory according to AWS Compute Optimizer recommendations.