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

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AWS Certified DevOps Engineer - Professional Questions and Answers

Question 1

A company's application uses a fleet of Amazon EC2 On-Demand Instances to analyze and process data. The EC2 instances are in an Auto Scaling group. The Auto Scaling group is a target group for an Application Load Balancer (ALB). The application analyzes critical data that cannot tolerate interruption. The application also analyzes noncritical data that can withstand interruption.

The critical data analysis requires quick scalability in response to real-time application demand. The noncritical data analysis involves memory consumption. A DevOps engineer must implement a solution that reduces scale-out latency for the critical data. The solution also must process the noncritical data.

Which combination of steps will meet these requirements? (Select TWO.)

Options:

A.

For the critical data, modify the existing Auto Scaling group. Create a warm pool instance in the stopped state. Define the warm pool size. Create a new version of the launch template that has detailed monitoring enabled. use Spot Instances.

B.

For the critical data, modify the existing Auto Scaling group. Create a warm pool instance in the stopped state. Define the warm pool size. Create a new version of the launch template that has detailed monitoring enabled. Use On-Demand Instances.

C.

For the critical data. modify the existing Auto Scaling group. Create a lifecycle hook to ensure that bootstrap scripts are completed successfully. Ensure that the application on the instances is ready to accept traffic before the instances are registered. Create a new version of the launch template that has detailed monitoring enabled.

D.

For the noncritical data, create a second Auto Scaling group that uses a launch template. Configure the launch template to install the unified Amazon CloudWatch agent and to configure the CloudWatch agent with a custom memory utilization metric. Use Spot Instances. Add the new Auto Scaling group as the target group for the ALB. Modify the application to use two target groups for critical data and noncritical data.

E.

For the noncritical data, create a second Auto Scaling group. Choose the predefined memory utilization metric type for the target tracking scaling policy. Use Spot Instances. Add the new Auto Scaling group as the target group for the ALB. Modify the application to use two target groups for critical data and noncritical data.

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Question 2

A company has many AWS accounts. During AWS account creation the company uses automation to create an Amazon CloudWatch Logs log group in every AWS Region that the company operates in. The automaton configures new resources in the accounts to publish logs to the provisioned log groups in their Region.

The company has created a logging account to centralize the logging from all the other accounts. A DevOps engineer needs to aggregate the log groups from all the accounts to an existing Amazon S3 bucket in the logging account.

Which solution will meet these requirements in the MOST operationally efficient manner?

Options:

A.

In the logging account create a CloudWatch Logs destination with a destination policy. For each new account subscribe the CloudWatch Logs log groups to the. Destination Configure a single Amazon Kinesis data stream and a single Amazon Kinesis Data Firehose delivery stream to deliver the logs from the CloudWatch Logs destination to the S3 bucket.

B.

In the logging account create a CloudWatch Logs destination with a destination policy for each Region. For each new account subscribe the CloudWatch Logs log groups to the destination. Configure a single Amazon Kinesis data stream and a single Amazon Kinesis Data Firehose delivery stream to deliver the logs from all the CloudWatch Logs destinations to the S3 bucket.

C.

In the logging account create a CloudWatch Logs destination with a destination policy for each Region. For each new account subscribe the CloudWatch Logs log groups to the destination Configure an Amazon Kinesis data stream and an Amazon Kinesis Data Firehose delivery stream for each Region to deliver the logs from the CloudWatch Logs destinations to the S3 bucket.

D.

In the logging account create a CloudWatch Logs destination with a destination policy. For each new account subscribe the CloudWatch Logs log groups to the destination. Configure a single Amazon Kinesis data stream to deliver the logs from the CloudWatch Logs destination to the S3 bucket.

Question 3

A company runs a microservices application on Amazon Elastic Kubernetes Service (Amazon EKS). Users recently reported significant delays while accessing an account summary feature, particularly during peak business hours.

A DevOps engineer used Amazon CloudWatch metrics and logs to troubleshoot the issue. The logs indicated normal CPU and memory utilization on the EKS nodes. The DevOps engineer was not able to identify where the delays occurred within the microservices architecture.

The DevOps engineer needs to increase the observability of the application to pinpoint where the delays are occurring.

Which solution will meet these requirements?

Options:

A.

Deploy the AWS X-Ray daemon as a DaemonSet in the EKS cluster. Use the X-Ray SDK to instrument the application code. Redeploy the application.

B.

Enable CloudWatch Container Insights for the EKS cluster. Use the Container Insights data to diagnose the delays.

C.

Create alarms based on the existing CloudWatch metrics. Set up an Amazon Simple Notification Service (Amazon SNS) topic to send email alerts.

D.

Increase the timeout settings in the application code for network operations to allow more time for operations to finish.