Amazon Web Services DVA-C02 Exam With Confidence Using Practice Dumps

This solution is the most efficient method to grant users access to AWS resources without requiring them to log in. Amazon Cognito is a service that provides user sign-up, sign-in, and access control for web and mobile applications. Amazon Cognito identity pools support both authenticated and unauthenticated users. Unauthenticated users receive access to your AWS resources even if they aren’t logged in with any of your identity providers (IdPs). You can use Amazon Cognito to associate unauthenticated users with an IAM role that has limited access to resources, such as Amazon S3 buckets or DynamoDB tables. This degree of access is useful to display content to users before they log in or to allow them to perform certain actions without signing up. Using an identity provider to securely authenticate with the application will require users to log in, which does not meet the requirement. Creating an AWS Lambda function to create an IAM user when a user accesses the application will incur unnecessary costs and complexity, and may pose security risks if not implemented properly. Creating credentials using AWS KMS and applying them to users when using the application will also incur unnecessary costs and complexity, and may not provide fine-grained access control for resources.

For asynchronous Lambda invocations, AWS provides built-in failure handling options that require minimal code and minimal operational work. When an async invocation fails (after Lambda’s internal retry behavior), the event can be sent to a dead-letter queue (DLQ) so it is not lost. A DLQ is the standard mechanism for capturing events that could not be processed successfully, preserving the original payload for later inspection and reprocessing.

Using a DLQ (typically Amazon SQS or Amazon SNS) gives durable storage of failed events and decouples failure recovery from the main execution path. The developer can later re-drive the messages by building a simple replay process, such as moving messages from the DLQ back to the original event source or invoking the function again with the stored payloads. This aligns with the requirement: “store messages that resulted in failed invocations so the application can retry later.”

Among the options, C is the only one that uses Lambda’s native async failure capture mechanism. Options A and B introduce unnecessary complexity and do not reliably store the original failed invocation payloads as a first-class workflow (CloudWatch Logs is not a message queue, and EventBridge→SNS doesn’t automatically capture only failed events from Lambda async invocations). Option D changes the architecture to an SQS pull model for the Lambda function; while valid, it is more than needed and adds design/operational considerations (polling, batching, visibility timeouts, DLQ configuration on the queue, etc.) compared with simply enabling DLQ support for async invokes.

Therefore, the least operational overhead solution is C: configure a dead-letter queue for the Lambda function’s asynchronous invocations so failed events are stored for later retry.