DOP-C02 Dumps With Exact Questions and Answers

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.

In the source AWS account, the IAM role used by the CI/CD pipeline should have permissions to access the source code repository, build artifacts, and any other resources required for the build process. In the destination AWS accounts, the IAM role used for deployment should have permissions to access the AWS resources required for deploying the application, such as EC2 instances, RDS databases, S3 buckets, etc. The exact permissions required will depend on the specific resources being used by the application. the IAM role used for deployment in the destination accounts should also have permissions to assume the IAM role for deployment in the centralized DevOps account. This is typically done using an IAM role trust policy that allows the destination account to assume the DevOps account role.

The requirement is to immediately detect and terminate EC2 instances involved in cryptocurrency mining with the least development effort. Amazon GuardDuty is the AWS-native service specifically designed to detect malicious activities such as crypto-mining by continuously analyzing CloudTrail events, VPC Flow Logs, and DNS logs. GuardDuty includes managed threat intelligence and predefined findings like CryptoCurrency:EC2/BitcoinTool.B!DNS and CryptoCurrency:EC2/BitcoinTool.B!IP, which directly identify mining behavior without custom detection logic.

Option C leverages this built-in capability. Once GuardDuty is enabled, findings are automatically generated when mining activity is detected. These findings are sent to Amazon EventBridge in near real time. An EventBridge rule can filter for cryptocurrency-related findings and trigger an AWS Lambda function. The Lambda function can then identify the affected EC2 instance and terminate it or adjust the Auto Scaling group to replace it. This approach requires minimal custom code and no log parsing, scheduled jobs, or analytics pipelines.

Options A and B rely on custom log analysis, periodic execution, and maintaining lists of mining domains or IPs, which significantly increases complexity and response time. Option D uses AWS Security Hub, which aggregates findings from GuardDuty and other services but is not intended for immediate, low-latency remediation.

Therefore, Option C provides the fastest detection, immediate response, and lowest development overhead using AWS-managed threat detection services.