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The DOP-C02 Exam is an updated version of the previous AWS Certified DevOps Engineer - Professional certification, which was first introduced in 2018. The new version of the exam reflects the latest trends and best practices in DevOps and AWS technologies. DOP-C02 exam consists of 75 multiple-choice and multiple-response questions, and the candidate has 180 minutes to complete it. To pass the exam, the candidate must score at least 750 out of 1000 points. AWS Certified DevOps Engineer - Professional certification is valid for three years, after which the candidate must recertify to maintain their credentials.

To prepare for the exam, candidates are encouraged to review the AWS Certified DevOps Engineer - Professional exam guide, which provides a detailed overview of the topics covered on the exam. They can also take advantage of AWS training courses, practice exams, and other resources to help them prepare for the exam.

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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q102-Q107):

NEW QUESTION # 102
A DevOps engineer is designing an application that integrates with a legacy REST API. The application has an AWS Lambda function that reads records from an Amazon Kinesis data stream. The Lambda function sends the records to the legacy REST API.
Approximately 10% of the records that the Lambda function sends from the Kinesis data stream have data errors and must be processed manually. The Lambda function event source configuration has an Amazon Simple Queue Service (Amazon SQS) dead-letter queue as an on-failure destination. The DevOps engineer has configured the Lambda function to process records in batches and has implemented retries in case of failure.
During testing the DevOps engineer notices that the dead-letter queue contains many records that have no data errors and that already have been processed by the legacy REST API. The DevOps engineer needs to configure the Lambda function's event source options to reduce the number of errorless records that are sent to the dead-letter queue.
Which solution will meet these requirements?

A. Configure the setting to split the batch when an error occurs
B. Increase the retry attempts
C. Decrease the maximum age of record
D. Increase the concurrent batches per shard

Answer: A

Explanation:
Explanation
This solution will meet the requirements because it will reduce the number of errorless records that are sent to the dead-letter queue. When you configure the setting to split the batch when an error occurs, Lambda will retry only the records that caused the error, instead of retrying the entire batch. This way, the records that have no data errors and have already been processed by the legacy REST API will not be retried and sent to the dead-letter queue unnecessarily.
https://docs.aws.amazon.com/lambda/latest/dg/with-kinesis.html

NEW QUESTION # 103
A DevOps engineer has developed an AWS Lambda function The Lambda function starts an AWS CloudFormation drift detection operation on all supported resources for a specific CloudFormation stack The Lambda function then exits Its invocation The DevOps engineer has created an Amazon EventBrdge scheduled rule that Invokes the Lambda function every hour. An Amazon Simple Notification Service (Amazon SNS) topic already exists In the AWS account. The DevOps engineer has subscribed to the SNS topic to receive notifications The DevOps engineer needs to receive a notification as soon as possible when drift is detected in this specific stack configuration.
Which solution Will meet these requirements?

A. Configure the existing EventBridge rule to also target the SNS topic Configure an SNS subscription filter policy to match the Cloud Formation stack. Attach the subscription filter policy to the SNS tomc
B. Create a second Lambda function to query the CloudFormation API for the drift detection results for the stack Configure the second Lambda function to publish a message to the SNS topic If drift ts detected Adjust the existing EventBridge rule to also target the second Lambda function
C. Configure AWS Config in the account. Use the cloudformation-stack-drift-detection-check managed rule. Create a second EventBndge rule that reacts to a compliance change event for the CloudFormaUon stack. Configure the SNS topc as a target of the second EventBridge rule.
D. Configure Amazon GuardDuty in the account with drift detection for all CloudFormation stacks. Create a second EventBndge rule that reacts to the GuardDuty drift detection event finding for the specific CloudFormation stack. Configure the SNS topic as a target of the second EventBridge rule.

Answer: C

Explanation:
A comprehensive and detailed explanation is:
Option A is incorrect because EventBridge rules cannot filter events based on the message body or attributes of the target service. Therefore, configuring an SNS subscription filter policy to match the CloudFormation stack will not work. The SNS topic will receive all events from the EventBridge rule, regardless of the stack name or drift status.
Option B is incorrect because it introduces unnecessary complexity and cost. Creating a second Lambda function to query the CloudFormation API for the drift detection results is redundant, since CloudFormation already publishes drift detection events to EventBridge. Moreover, invoking two Lambda functions every hour will incur more charges than invoking one.
Option C is incorrect because GuardDuty does not provide drift detection for CloudFormation stacks. GuardDuty is a threat detection service that monitors for malicious activity and unauthorized behavior in AWS accounts and workloads. It does not monitor or report on configuration changes or drifts in CloudFormation stacks.
Option D is correct because it leverages AWS Config and its managed rule for drift detection. AWS Config is a service that enables you to assess, audit, and evaluate the configurations of your AWS resources. It can detect configuration changes and drifts in CloudFormation stacks using the cloudformation-stack-drift-detection-check managed rule. This rule triggers an AWS Config event when a stack drifts from its expected template configuration. By creating a second EventBridge rule that reacts to this event for the specific stack, the DevOps engineer can configure the SNS topic as a target and receive a notification as soon as possible when drift is detected.
Reference:
AWS Config
Amazon SNS subscription filter policies
Amazon EventBridge rules

NEW QUESTION # 104
A company runs a fleet of Amazon EC2 instances in a VPC. The company's employees remotely access the EC2 instances by using the Remote Desktop Protocol (RDP). The company wants to collect metrics about how many RDP sessions the employees initiate every day. Which combination of steps will meet this requirement? (Select THREE.)

A. Create a flow log in VPC Flow Logs.
B. Create an Amazon CloudWatch Logs log group. Specify the log group as a target for the EventBridge rule.
C. Create an Amazon EventBridge rule that reacts to EC2 Instance State-change Notification events.
D. Create a log group subscription filter. Use EventBridge as the destination.
E. Create an Amazon CloudWatch Logs log group. Specify the log group as a destination for the flow log.
F. Create a log group metric filter.

Answer: A,E,F

NEW QUESTION # 105
A company that runs many workloads on AWS has an Amazon EBS spend that has increased over time. The DevOps team notices there are many unattached EBS volumes. Although there are workloads where volumes are detached, volumes over 14 days old are stale and no longer needed. A DevOps engineer has been tasked with creating automation that deletes unattached EBS volumes that have been unattached for 14 days.
Which solution will accomplish this?

A. Create an Amazon CloudWatch Events rule to execute an AWS Lambda function daily. The Lambda function should find unattached EBS volumes and tag them with the current date, and delete unattached volumes that have tags with dates that are more than 14 days old.
B. Configure the AWS Config ec2-volume-inuse-check managed rule with a configuration changes trigger type and an Amazon EC2 volume resource target. Create a new Amazon CloudWatch Events rule scheduled to execute an AWS Lambda function in 14 days to delete the specified EBS volume.
C. Use Amazon EC2 and Amazon Data Lifecycle Manager to configure a volume lifecycle policy. Set the interval period for unattached EBS volumes to 14 days and set the retention rule to delete. Set the policy target volumes as *.
D. Use AWS Trusted Advisor to detect EBS volumes that have been detached for more than 14 days. Execute an AWS Lambda function that creates a snapshot and then deletes the EBS volume.

Answer: A

Explanation:
The requirement is to create automation that deletes unattached EBS volumes that have been unattached for 14 days. To do this, the DevOps engineer needs to use the following steps:
Create an Amazon CloudWatch Events rule to execute an AWS Lambda function daily. CloudWatch Events is a service that enables event-driven architectures by delivering events from various sources to targets. Lambda is a service that lets you run code without provisioning or managing servers. By creating a CloudWatch Events rule that executes a Lambda function daily, the DevOps engineer can schedule a recurring task to check and delete unattached EBS volumes.
The Lambda function should find unattached EBS volumes and tag them with the current date, and delete unattached volumes that have tags with dates that are more than 14 days old. The Lambda function can use the EC2 API to list and filter unattached EBS volumes based on their state and tags. The function can then tag each unattached volume with the current date using the create-tags command. The function can also compare the tag value with the current date and delete any unattached volume that has been tagged more than 14 days ago using the delete-volume command.

NEW QUESTION # 106
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?

A. 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
B. 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.
C. 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
D. 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

Answer: B

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

NEW QUESTION # 107
......

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