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Amazon DOP-C02 (AWS Certified DevOps Engineer - Professional) Certification Exam is a highly sought-after certification for IT professionals working with cloud computing and DevOps methodologies. AWS Certified DevOps Engineer - Professional certification is designed for individuals who have experience working with AWS services, as well as implementing and managing continuous delivery systems and automation processes.

Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q143-Q148):

NEW QUESTION # 143
A DevOps engineer used an AWS Cloud Formation custom resource to set up AD Connector. The AWS Lambda function ran and created AD Connector, but Cloud Formation is not transitioning from CREATE_IN_PROGRESS to CREATE_COMPLETE.
Which action should the engineer take to resolve this issue?

A. Ensure the Lambda function code returns a response to the pre-signed URL.
B. Ensure the Lambda function code has exited successfully.
C. Ensure the Lambda function IAM role has cloudformation UpdateStack permissions for the stack ARN.
D. Ensure the Lambda function IAM role has ds ConnectDirectory permissions for the AWS account.

Answer: A

NEW QUESTION # 144
A DevOps engineer has implemented a Cl/CO pipeline to deploy an AWS Cloud Format ion template that provisions a web application. The web application consists of an Application Load Balancer (ALB) a target group, a launch template that uses an Amazon Linux 2 AMI an Auto Scaling group of Amazon EC2 instances, a security group and an Amazon RDS for MySQL database The launch template includes user data that specifies a script to install and start the application.
The initial deployment of the application was successful. The DevOps engineer made changes to update the version of the application with the user dat a. The CI/CD pipeline has deployed a new version of the template However, the health checks on the ALB are now failing The health checks have marked all targets as unhealthy.
During investigation the DevOps engineer notices that the Cloud Formation stack has a status of UPDATE_COMPLETE. However, when the DevOps engineer connects to one of the EC2 instances and checks /varar/log messages, the DevOps engineer notices that the Apache web server failed to start successfully because of a configuration error How can the DevOps engineer ensure that the CloudFormation deployment will fail if the user data fails to successfully finish running?

A. Use the Amazon CloudWatch agent to stream the cloud-init logs Create a subscription filter that includes an AWS Lambda function with an appropriate invocation timeout Configure the Lambda function to use the SignalResource API operation to signal success or failure to CloudFormation.
B. Use the cfn-signal helper script to signal success or failure to CloudFormation Use the WaitOnResourceSignals update policy within the CloudFormation template Set an appropriate timeout for the update policy.
C. Create a lifecycle hook on the Auto Scaling group by using the AWS AutoScaling LifecycleHook resource Create an Amazon Simple Notification Service (Amazon SNS) topic as the target to signal success or failure to CloudFormation Set an appropriate timeout on the lifecycle hook.
D. Create an Amazon CloudWatch alarm for the UnhealthyHostCount metric. Include an appropriate alarm threshold for the target group Create an Amazon Simple Notification Service (Amazon SNS) topic as the target to signal success or failure to CloudFormation

Answer: B

Explanation:
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-attribute-updatepolicy.html

NEW QUESTION # 145
A company is storing 100 GB of log data in csv format in an Amazon S3 bucket SQL developers want to query this data and generate graphs to visualize it. The SQL developers also need an efficient automated way to store metadata from the csv file.
Which combination of steps will meet these requirements with the LEAST amount of effort? (Select THREE.)

A. Use the AWS Glue Data Catalog as the persistent metadata store.
B. Query the data with Amazon Redshift.
C. Use Amazon DynamoDB as the persistent metadata store.
D. Filter the data through Amazon QuickSight to visualize the data.
E. Fitter the data through AWS X-Ray to visualize the data.
F. Query the data with Amazon Athena.

Answer: A,D,F

Explanation:
Explanation
https://docs.aws.amazon.com/glue/latest/dg/components-overview.html

NEW QUESTION # 146
A company needs a strategy for failover and disaster recovery of its data and application. The application uses a MySQL database and Amazon EC2 instances. The company requires a maximum RPO of 2 hours and a maximum RTO of 10 minutes for its data and application at all times.
Which combination of deployment strategies will meet these requirements? (Select TWO.)

A. 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.
B. Create an Amazon Aurora cluster in multiple AWS Regions as the data store. Use a Network Load Balancer to balance the database traffic in different Regions.
C. 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.
D. Create an Amazon Aurora Single-AZ cluster in multiple AWS Regions as the data store. Use Aurora's automatic recovery capabilities in the event of a disaster.
E. Set up the application in two AWS Regions. Use Amazon Route 53 failover routing that points to Application Load Balancers in both Regions. Use health checks and Auto Scaling groups in each Region.

Answer: A,C

Explanation:
Verified answer: B and E
Short 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.

NEW QUESTION # 147
A DevOps engineer is architecting a continuous development strategy for a company's software as a service (SaaS) web application running on AWS. For application and security reasons users subscribing to this application are distributed across multiple. Application Load Balancers (ALBs) each of which has a dedicated Auto Scaling group and fleet of Amazon EC2 instances The application does not require a build stage and when it is committed to AWS CodeCommit, the application must trigger a simultaneous deployment to all ALBs Auto Scaling groups and EC2 fleets.
Which architecture will meet these requirements with the LEAST amount of configuration?

A. Create an AWS CodePipeline pipeline for each ALB-Auto Scaling group pair that deploys the application using an AWS CodeDeploy application and deployment group created for the same ALB-Auto Scaling group pair.
B. Create a single AWS CodePipeline pipeline that deploys the application in parallel using a single AWS CodeDeploy application and unique deployment group for each ALB-Auto Scaling group pair.
C. Create a single AWS CodePipeline pipeline that deploys the application using a single AWS CodeDeploy application and single deployment group.
D. Create a single AWS CodePipeline pipeline that deploys the application in parallel using unique AWS CodeDeploy applications and deployment groups created for each ALB-Auto Scaling group pair.

Answer: B

Explanation:
Explanation
https://docs.aws.amazon.com/codedeploy/latest/userguide/deployment-groups.html

NEW QUESTION # 148
......

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