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

For pull through cache repositories, Amazon ECR now supports repository creation templates that can be applied to a registry prefix, such as /external. These templates define default settings, including encryption configuration with a specific KMS key, tag immutability, scan on push, and more. When new cache repositories are auto-created under that prefix, they inherit the template settings automatically.

In this scenario, existing external cache repositories are noncompliant because they use SSE-S3. The company can delete those repositories (removing the noncompliant caches) and configure an ECR repository creation template for the /external prefix that specifies the required customer managed KMS key. As new images are pulled, ECR recreates the cache repositories under that prefix with KMS encryption using the specified key, guaranteeing compliance going forward.

Option A (AWS Config) would only detect noncompliance after creation and cannot enforce encryption at creation time. Option C (SCP) cannot directly control repository encryption properties. Option D misuses EventBridge; KMS cannot be a “target” that retroactively encrypts repositories.

Therefore, using an ECR repository creation template with the desired KMS key is the correct, automatic, and secure solution.

To meet the requirements of failover and disaster recovery, the company should use the following deployment strategies:

Create an Amazon Aurora global database in two AWS Regions as the data store. In the event of a failure, promote the secondary Region to the primary for the application. Update the application to use the Aurora cluster endpoint in the secondary Region. This strategy can provide a low RPO and RTO for the data, as Aurora global database replicates data with minimal latency across Regions and allows fast and easy failover12. The company can use the Amazon Aurora cluster endpoint to connect to the current primary DB cluster without needing to change any application code1.

Set up the application in two AWS Regions. Configure AWS Global Accelerator to point to Application Load Balancers (ALBs) in both Regions. Add both ALBs to a single endpoint group. Use health checks and Auto Scaling groups in each Region. This strategy can provide high availability and performance for the application, as AWS Global Accelerator uses the AWS global network to route traffic to the closest healthy endpoint3. The company can also use static IP addresses that are assigned by Global Accelerator as a fixed entry point for their application1. By using health checks and Auto Scaling groups, the company can ensure that their application can scale up or down based on demand and handle any instance failures4.

The other options are incorrect because:

Creating an Amazon Aurora Single-AZ cluster in multiple AWS Regions as the data store would not provide a fast failover or disaster recovery solution, as the company would need to manually restore data from backups or snapshots in another Region in case of a failure.

Creating an Amazon Aurora cluster in multiple AWS Regions as the data store and using a Network Load Balancer to balance the database traffic in different Regions would not work, as Network Load Balancers do not support cross-Region routing. Moreover, this strategy would not provide a consistent view of the data across Regions, as Aurora clusters do not replicate data automatically between Regions unless they are part of a global database.

Setting up the application in two AWS Regions and using Amazon Route 53 failover routing that points to Application Load Balancers in both Regions would not provide a low RTO, as Route 53 failover routing relies on DNS resolution, which can take time to propagate changes across different DNS servers and clients. Moreover, this strategy would not provide deterministic routing, as Route 53 failover routing depends on DNS caching behavior, which can vary depending on different factors.