What are the MOST operationally efficient solutions to reduce the function throttling?
(Choose two.)
Migrate the function to Amazon Elastic Kubernetes Service (Amazon EKS).
Increase the maximum age of events in Lambda.
Increase the function’s reserved concurrency.
Add the lambda:GetFunctionConcurrency action to the execution role.
Request a service quota change for increased concurrency.
Explanations:
Migrating the function to Amazon EKS does not address the immediate issue of Lambda function throttling. EKS is a container orchestration service and may not provide the same operational efficiency for event-driven functions that Lambda offers. Furthermore, it would require significant changes in architecture and management, which does not solve the throttling problem directly.
Increasing the maximum age of events in Lambda affects the event processing timing and does not directly reduce throttling. Throttling occurs when the concurrency limit is reached, and simply increasing the age of events does not change the available concurrency for processing incoming events.
Increasing the function’s reserved concurrency directly increases the number of concurrent executions that the function can handle. This adjustment prevents throttling by ensuring that the function can scale to meet incoming demand, allowing for more simultaneous executions.
Adding the lambdaaction to the execution role is related to permissions and does not affect the concurrency limits of the Lambda function itself. This action allows for reading the concurrency settings, but does not modify or increase the concurrency available to the function.
Requesting a service quota change for increased concurrency directly addresses the issue of throttling. By increasing the overall concurrency limit at the account level, more simultaneous executions of the Lambda function can be allowed, thus reducing the likelihood of throttling when demand increases.