Amazon Web Services help2pass passed Exam Today Dop-c02 by Kiyan q8 vce pdf

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Exam Name:	AWS Certified DevOps Engineer - Professional
Exam Code:	DOP-C02 Dumps
Vendor:	Amazon Web Services	Certification:	AWS Certified Professional
Questions:	366 Q&A's	Shared By:	kiyan

Question 64

A company recently migrated its application to an Amazon Elastic Kubernetes Service (Amazon EKS) cluster that uses Amazon EC2 instances. The company configured the application to automatically scale based on CPU utilization.

The application produces memory errors when it experiences heavy loads. The application also does not scale out enough to handle the increased load. The company needs to collect and analyze memory metrics for the application over time.

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

Options:

Attach the Cloud WatchAgentServer Pol icy managed 1AM policy to the 1AM instance profile that the cluster uses.

Attach the Cloud WatchAgentServer Pol icy managed 1AM policy to a service account role for the cluster.

Collect performance metrics by deploying the unified Amazon CloudWatch agent to the existing EC2 instances in the cluster. Add the agent to the AMI for any new EC2 instances that are added to the cluster.

Collect performance logs by deploying the AWS Distro for OpenTelemetry collector as a DaemonSet.

Analyze the pod_memory_utilization Amazon CloudWatch metric in the Containerlnsights namespace by using the Service dimension.

Analyze the node_memory_utilization Amazon CloudWatch metric in the Containerlnsights namespace by using the ClusterName dimension.

Discussion

Answer:

A, C, E

Explanation:

 Step 1: Attaching the CloudWatchAgentServerPolicy to the IAM Role

The CloudWatch agent needs permissions to collect and send metrics, including memory metrics, to Amazon CloudWatch. You can attach the CloudWatchAgentServerPolicy managed IAM policy to the IAM instance profile or service account role to grant these permissions.

Action: Attach the CloudWatchAgentServerPolicy managed IAM policy to the IAM instance profile that the EKS cluster uses.

Why: This ensures the CloudWatch agent has the necessary permissions to collect memory metrics.

[Reference: AWS documentation on CloudWatch Agent Permissions., This corresponds to Option A: Attach the CloudWatchAgentServerPolicy managed IAM policy to the IAM instance profile that the cluster uses.,  Step 2: Deploying the CloudWatch Agent to EC2 InstancesTo collect memory metrics from the EC2 instances running in the EKS cluster, the CloudWatch agent needs to be deployed on these instances. The agent collects system-level metrics, including memory usage., Action: Deploy the unified Amazon CloudWatch agent to the existing EC2 instances in the EKS cluster. Update the Amazon Machine Image (AMI) for future instances to include the CloudWatch agent., Why: The CloudWatch agent allows you to collect detailed memory metrics from the EC2 instances, which is not enabled by default., Reference: AWS documentation on Installing and Configuring the CloudWatch Agent., This corresponds to Option C: Collect performance metrics by deploying the unified Amazon CloudWatch agent to the existing EC2 instances in the cluster. Add the agent to the AMI for any new EC2 instances that are added to the cluster.,  Step 3: Analyzing Memory Metrics Using Container InsightsAfter collecting the memory metrics, you can analyze them using the pod_memory_utilization metric in Amazon CloudWatch Container Insights. This metric provides visibility into the memory usage of the containers (pods) in the EKS cluster., Action: Analyze the pod_memory_utilization CloudWatch metric in the Container Insights namespace by using the Service dimension., Why: This provides detailed insights into memory usage at the container level, which helps diagnose memory-related issues., Reference: AWS documentation on CloudWatch Container Insights., This corresponds to Option E: Analyze the pod_memory_utilization Amazon CloudWatch metric in the Container Insights namespace by using the Service dimension., , , ]

Question 65

A company uses AWS Directory Service for Microsoft Active Directory as its identity provider (IdP). The company requires all infrastructure to be

defined and deployed by AWS CloudFormation.

A DevOps engineer needs to create a fleet of Windows-based Amazon EC2 instances to host an application. The DevOps engineer has created a

CloudFormation template that contains an EC2 launch template, IAM role, EC2 security group, and EC2 Auto Scaling group. The DevOps engineer must implement a solution that joins all EC2 instances to the domain of the AWS Managed Microsoft AD directory.

Which solution will meet these requirements with the MOST operational efficiency?

Options:

In the CloudFormation template, create an AWS::SSM::Document resource that joins the EC2 instance to the AWS Managed Microsoft AD domain by using the parameters for the existing directory. Update the launch template to include the SSMAssociation property to use the new SSM document. Attach the AmazonSSMManagedlnstanceCore and AmazonSSMDirectoryServiceAccess AWS managed policies to the IAM role that the EC2 instances use.

In the CloudFormation template, update the launch template to include specific tags that propagate on launch. Create an AWS::SSM::Association resource to associate the AWS-JoinDirectoryServiceDomain Automation runbook with the EC2 instances that have the specified tags. Define the required parameters to join the AWS Managed Microsoft AD directory. Attach the AmazonSSMManagedlnstanceCore and AmazonSSMDirectoryServiceAccess AWS managed polici

Store the existing AWS Managed Microsoft AD domain connection details in AWS Secrets Manager. In the CloudFormation template, create an AWS::SSM::Association resource to associate the AWS-CreateManagedWindowslnstanceWithApproval Automation runbook with the EC2 Auto Scaling group. Pass the ARNs for the parameters from Secrets Manager to join the domain. Attach the AmazonSSMDirectoryServiceAccess and SecretsManagerReadWrite AWS managed polici

Store the existing AWS Managed Microsoft AD domain administrator credentials in AWS Secrets Manager. In the CloudFormation template, update the EC2 launch template to include user data. Configure the user data to pull the administrator credentials from Secrets Manager and to join the AWS Managed Microsoft AD domain. Attach the AmazonSSMManagedlnstanceCore and SecretsManagerReadWrite AWS managed policies to the IAM role that the EC2 instance

Discussion

Question 66

A company has microservices running in AWS Lambda that read data from Amazon DynamoDB. The Lambda code is manually deployed by developers after successful testing The company now needs the tests and deployments be automated and run in the cloud Additionally, traffic to the new versions of each microservice should be incrementally shifted over time after deployment.

What solution meets all the requirements, ensuring the MOST developer velocity?

Options:

Create an AWS CodePipelme configuration and set up a post-commit hook to trigger the pipeline after tests have passed Use AWS CodeDeploy and create a Canary deployment configuration that specifies the percentage of traffic and interval

Create an AWS CodeBuild configuration that triggers when the test code is pushed Use AWS CloudFormation to trigger an AWS CodePipelme configuration that deploys the new Lambda versions and specifies the traffic shift percentage and interval

Create an AWS CodePipelme configuration and set up the source code step to trigger when code is pushed. Set up the build step to use AWS CodeBuild to run the tests Set up an AWS CodeDeploy configuration to deploy, then select the CodeDeployDefault.LambdaLinearlDPercentEvery3Minut.es Option.

Use the AWS CLI to set up a post-commit hook that uploads the code to an Amazon S3 bucket after tests have passed. Set up an S3 event trigger that runs a Lambda function that deploys the new version. Use an interval in the Lambda function to deploy the code over time at the required percentage

Discussion

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Question 67

A company runs an application in an Auto Scaling group of Amazon EC2 instances behind an Application Load Balancer (ALB). The EC2 instances run Docker containers that make requests to a MySQL database that runs on separate EC2 instances. A DevOps engineer needs to update the application to use a serverless architecture. Which solution will meet this requirement with the FEWEST changes?

Options:

Replace the containers that run on EC2 instances and the ALB with AWS Lambda functions. Replace the MySQL database with an Amazon Aurora Serverless v2 database that is compatible with MySQL.

Replace the containers that run on EC2 instances with AWS Fargate. Replace the MySQL database with an Amazon Aurora Serverless v2 database that is compatible with MySQL.

Replace the containers that run on EC2 instances and the ALB with AWS Lambda functions. Replace the MySQL database with Amazon DynamoDB tables.

Replace the containers that run on EC2 instances with AWS Fargate. Replace the MySQL database with Amazon DynamoDB tables.

Discussion

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