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Function execution model

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The function execution model involves Lambda provisioning and managing the resources required to run your functions. Whenever an event occurs, AWS Lambda automatically scales your function instances based on the number of concurrent requests. Each instance of your function, known as a container, is…

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AWS Certified Solutions Architect - Function execution model Example Questions

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Question 1

An AWS Lambda function is triggered by Amazon S3 object-created events to process uploaded images. After periods of low traffic, the first few invocations have significantly higher startup latency than steady-state. What is the most effective way to reduce this startup latency without changing the application code?

Correct Answer: Enable Provisioned Concurrency for the Lambda function to keep execution environments warm and reduce cold-start latency.

Provisioned Concurrency pre-initializes a set number of Lambda execution environments so that requests can be served immediately, eliminating the cold-start penalty that causes high startup latency after idle periods. This directly improves invocation start time without requiring code changes. Adjusting timeout does not reduce latency and only changes the maximum allowed runtime; increasing memory can speed CPU- or network-bound execution but does not remove cold starts; using Step Functions is for workflow orchestration and does not address Lambda startup latency; adding EC2 instances or more S3 buckets has no effect on Lambda invocation latency.

Question 2

An online game uses an AWS Lambda function to process player actions. The function is invoked synchronously at an average rate of 5000 requests per minute, and each invocation runs for about 30 seconds. The AWS account’s unreserved concurrency is currently 200, and no reserved or provisioned concurrency is configured for the function. What should you do to ensure the function can handle the required throughput?

Correct Answer: Increase the function's concurrency limit

At 5000 requests per minute (~83.3 per second) and an average execution time of 30 seconds, the function requires approximately 83.3 × 30 ≈ 2500 concurrent executions. With only 200 unreserved concurrency available, the function will throttle heavily. The correct action is to increase the Lambda concurrency quota for the account and configure sufficient reserved concurrency for the function so it can scale to the needed level. AWS Batch is for batch/queued jobs and does not address Lambda concurrency. Deploying in multiple regions adds complexity and does not bypass the per‑region concurrency quota constraint for each region. AWS Auto Scaling does not apply to Lambda, which scales automatically within its concurrency quotas.

Question 3

A developer needs to create an AWS Lambda function that is triggered when a new object is added to an Amazon S3 bucket. What should be the execution role for this Lambda function?

Correct Answer: Create an IAM role with AmazonS3ReadOnlyAccess and AWSLambdaExecute policies

Create an IAM role with AmazonS3ReadOnlyAccess and AWSLambdaExecute policies. This allows the Lambda function to read objects from the Amazon S3 bucket and execute the function. The other options do not provide the necessary permissions for this scenario.

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