DOP-C02 Exam Dumps : AWS Certified DevOps Engineer - Professional

ECR pull-through cache caches images from upstream repositories for resilience.

Private repo with basic scanning ensures vulnerability detection on pushed images.

Enabling pull-through caching on a private repo combines caching and vulnerability scanning seamlessly.

Public repos do not support pull-through caching of upstream images.

Replication rules are for multi-Region replication, not upstream caching.

These solutions will meet the requirement because they will prevent the loss of notification messages in the future. An Amazon SQS queue is a service that provides a reliable, scalable, and secure message queue for asynchronous communication between distributed components. You can use an SQS queue to buffer messages from an SNS topic and ensure that they are delivered and processed by a Lambda function, even if the function or the database is temporarily unavailable.

Option C will configure an SQS dead-letter queue for the SNS topic. A dead-letter queue is a queue that receives messages that could not be delivered to any subscriber after a specified number of retries. You can use a dead-letter queue to store and analyze failed messages, or to reprocess them later. This way, you can avoid losing messages that could not be delivered to the Lambda function due to network errors, throttling, or other issues.

Option D will subscribe an SQS queue to the SNS topic and configure the Lambda function to process messages from the SQS queue. This will decouple the SNS topic from the Lambda function and provide more flexibility and control over the message delivery and processing. You can use an SQS queue to store messages from the SNS topic until they are ready to be processed by the Lambda function, and also to retry processing in case of failures. This way, you can avoid losing messages that could not be processed by the Lambda function due to database errors, timeouts, or other issues.

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AWS CDK recommends using Level 3 (L3) custom constructs to encapsulate reusable multi-resource infrastructure patterns (networking, compute, DB). Then, define a single set of environment-aware stacks that accept environment parameters for deployment. This ensures consistency with minimal code duplication, per AWS CDK best practices and design patterns whitepaper.