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The AWS Certified DevOps Engineer - Professional certification exam consists of multiple-choice questions and requires a passing score of 750 out of 1000 points. DOP-C02 Exam is proctored and can be taken online or at a testing center. Candidates have 180 minutes to complete the exam, and the cost is $300 USD. Upon passing the exam, candidates will receive their AWS Certified DevOps Engineer - Professional certification, which is valid for three years.

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Amazon DOP-C02 is an exam that is designed to test the knowledge and skills of individuals seeking to become certified AWS Certified DevOps Engineers - Professionals. AWS Certified DevOps Engineer - Professional certification is awarded by Amazon Web Services (AWS), a cloud computing platform that offers a wide range of services and tools for developing, deploying, and managing applications.

Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q39-Q44):

NEW QUESTION # 39
A DevOps engineer needs to implement a solution to install antivirus software on all the Amazon EC2 instances in an AWS account. The EC2 instances run the most recent version of Amazon Linux.
The solution must detect all instances and must use an AWS Systems Manager document to install the software if the software is not present.
Which solution will meet these requirements?

A. Set up AWS Config to record all the resources in the account. Create an AWS Config custom rule to determine if the software is installed on all the EC2 instances. Configure an automatic remediation action that uses the Systems Manager document for noncompliant EC2 instances.
B. Create an association in Systems Manager State Manager. Target all the managed nodes. Include the software in the association. Configure the association to use the Systems Manager document.
C. Create an Amazon EventBridge rule that uses AWS CloudTrail to detect the RunInstances API call. Configure inventory collection in Systems Manager Inventory to determine if the software is installed on the EC2 instances. Associate the Systems Manager Inventory with the Systems Manager document.
D. Activate Amazon EC2 scanning on Amazon Inspector to determine if the software is installed on all the EC2 instances. Associate the findings with the Systems Manager document.

Answer: B

Explanation:
Option A best matches the requirement in the simplest, most direct way:
Systems Manager State Manager is designed to apply and maintain a desired state on managed instances by running associations on a schedule or continuously across targets (for example, "all managed nodes").
By using a Systems Manager document in the association that installs the antivirus package (and can be written to be idempotent: "install only if not present"), State Manager both detects drift (software missing) and remediates it automatically by reapplying the desired configuration.
This approach automatically covers all instances that are managed by Systems Manager (which is typically the standard requirement for fleet management on Amazon Linux).
Why the others are more overhead or not as direct:
B can work, but it requires building and operating a custom Config rule plus remediation wiring. That's more components and maintenance than State Manager for a straightforward "ensure software is installed" task.
C Amazon Inspector is a vulnerability management service; it's not the primary tool for "ensure a specific software package is installed everywhere" and "remediate via SSM doc" as a desired-state control.

NEW QUESTION # 40
An application running on a set of Amazon EC2 instances in an Auto Scaling group requires a configuration file to operate. The instances are created and maintained with AWS CloudFormation. A DevOps engineer wants the instances to have the latest configuration file when launched and wants changes to the configuration file to be reflected on all the instances with a minimal delay when the CloudFormation template is updated.
Company policy requires that application configuration files be maintained along with AWS infrastructure configuration files m source control.
Which solution will accomplish this?

A. In the CloudFormation template add an EC2 launch template resource. Place the configuration file content in the launch template. Add an AWS Systems Manager Resource Data Sync resource to the template to poll for updates to the configuration.
B. In the CloudFormation template add an EC2 launch template resource. Place the configuration file content in the launch template. Configure the cfn-mit script to run when the instance is launched and configure the cfn-hup script to poll for updates to the configuration.
C. In the CloudFormaiion template add an AWS Config rule. Place the configuration file content in the rule's InputParameters property and set the Scope property to the EC2 Auto Scaling group. Add an AWS Systems Manager Resource Data Sync resource to the template to poll for updates to the configuration.
D. In the CloudFormation template add CloudFormation imt metadata. Place the configuration file content m the metadata. Configure the cfn-init script to run when the instance is launched and configure the cfn-hup script to poll for updates to the configuration.

Answer: D

Explanation:
Explanation
Use the AWS::CloudFormation::Init type to include metadata on an Amazon EC2 instance for the cfn-init helper script. If your template calls the cfn-init script, the script looks for resource metadata rooted in the AWS::CloudFormation::Init metadata key. Reference:
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-init.html

NEW QUESTION # 41
A company is examining its disaster recovery capability and wants the ability to switch over its daily operations to a secondary AWS Region. The company uses AWS CodeCommit as a source control tool in the primary Region.
A DevOps engineer must provide the capability for the company to develop code in the secondary Region. If the company needs to use the secondary Region, developers can add an additional remote URL to their local Git configuration.
Which solution will meet these requirements?

A. Create an AWS CodeArtifact repository in the secondary Region. Create an AWS CodePipeline pipeline that uses the primary Region's CodeCommit repository for the source action. Create a Cross- Region stage in the pipeline that packages the CodeCommit repository contents and stores the contents in the CodeArtifact repository when a pull request is merged into the CodeCommit repository.
B. Create an Amazon S3 bucket in the secondary Region. Create an AWS Fargate task to perform a Git mirror operation of the primary Region's CodeCommit repository and copy the result to the S3 bucket.
Create an AWS Lambda function that initiates the Fargate task. Create an Amazon EventBridge rule that reacts to merge events in the CodeCommit repository. Configure the EventBridge rule to invoke the Lambda function.
C. Create a CodeCommit repository in the secondary Region. Create an AWS CodeBuild project to perform a Git mirror operation of the primary Region's CodeCommit repository to the secondary Region's CodeCommit repository. Create an AWS Lambda function that invokes the CodeBuild project. Create an Amazon EventBridge rule that reacts to merge events in the primary Region's CodeCommit repository. Configure the EventBridge rule to invoke the Lambda function.
D. Create an AWS Cloud9 environment and a CodeCommit repository in the secondary Region. Configure the primary Region's CodeCommit repository as a remote repository in the AWS Cloud9 environment.Connect the secondary Region's CodeCommit repository to the AWS Cloud9 environment.

Answer: C

Explanation:
The best solution to meet the disaster recovery capability and allow developers to switch over to a secondary AWS Region for code development is option A. This involves creating a CodeCommit repository in the secondary Region and setting up an AWS CodeBuild project to perform a Git mirror operation of the primary Region's CodeCommit repository to the secondary Region's repository. An AWS Lambda function is then created to invoke the CodeBuild project. Additionally, an Amazon EventBridge rule is configured to react to merge events in the primary Region's CodeCommit repository and invoke the Lambda function12. This setup ensures that the secondary Region's repository is always up-to-date with the primary repository, allowing for a seamless transition in case of a disaster recovery event1.
AWS CodeCommit User Guide on resilience and disaster recovery1.
AWS Documentation on monitoring CodeCommit events in Amazon EventBridge and Amazon CloudWatch Events2.

NEW QUESTION # 42
A company has an application that runs on Amazon EC2 instances in an Auto Scaling group. The application processes a high volume of messages from an Amazon Simple Queue Service (Amazon SQS) queue.
A DevOps engineer noticed that the application took several hours to process a group of messages from the SQS queue. The average CPU utilization of the Auto Scaling group did not cross the threshold of a target tracking scaling policy when processing the messages. The application that processes the SQS queue publishes logs to Amazon CloudWatch Logs.
The DevOps engineer needs to ensure that the queue is processed quickly.
Which solution meets these requirements with the LEAST operational overhead?

A. Create an AWS Lambda function. Configure the Lambda function to publish a custom metric by using the ApproximateNumberOfMessagesVisible SQS queue attribute and the GroupIn-ServiceInstances Auto Scaling group attribute to publish the queue messages for each instance. Create a CloudWatch subscription filter for the application logs with the Lambda function as the target. Create a target tracking scaling policy for the Auto Scaling group that uses the custom metric to scale in and out.
B. Create an AWS Lambda function that logs the ApproximateNumberOfMessagesVisible attribute of the SQS queue to a CloudWatch Logs log group. Schedule an Amazon EventBridge rule to run the Lambda function every 5 minutes. Create a metric filter to count the number of log events from a CloudWatch logs group. Create a target tracking scaling policy for the Auto Scaling group that uses the custom metric to scale in and out.
C. Create a target tracking scaling policy for the Auto Scaling group. In the target tracking policy, use the ApproximateNumberOfMessagesVisible SQS queue attribute and the GroupIn-ServiceInstances Auto Scaling group attribute to calculate how many messages are in the queue for each number of instances by using metric math. Use the calculated attribute to scale in and out.
D. Create an AWS Lambda function. Configure the Lambda function to publish a custom metric by using the ApproximateNumberOfMessagesVisible SQS queue attribute and the GroupIn-ServiceInstances Auto Scaling group attribute to publish the queue messages for each instance. Schedule an Amazon EventBridge rule to run the Lambda function every hour. Create a target tracking scaling policy for the Auto Scaling group that uses the custom metric to scale in and out.

Answer: C

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The default CPU utilization metric does not reflect the processing backlog in the SQS queue, so the Auto Scaling group is not scaling properly to handle the workload.
To scale the Auto Scaling group based on queue length, you can create a target tracking scaling policy that uses acustom metricthat combines the SQS queue'sApproximateNumberOfMessagesVisibleand the number of instances (GroupIn-ServiceInstances) metric usingCloudWatch metric math. This allows the scaling policy to calculate the average number of messages per instance and scale accordingly.
This approach requires no additional Lambda functions or log processing, thus minimizing operational overhead.
Option A and B require Lambda functions to publish custom metrics, which increases operational complexity.
Option D also adds complexity with logging and metric filters.
Reference:
Scaling based on SQS queue length using metric math:"You can create CloudWatch metric math expressions combining SQS and Auto Scaling group metrics to enable target tracking scaling policies that respond to queue backlog."(AWS Auto Scaling with SQS) Target Tracking Scaling Policies:"Target tracking policies can use metric math expressions as a source to make scaling decisions."(AWS Auto Scaling Target Tracking)

NEW QUESTION # 43
A company has multiple development teams in different business units that work in a shared single AWS account All Amazon EC2 resources that are created in the account must include tags that specify who created the resources. The tagging must occur within the first hour of resource creation.
A DevOps engineer needs to add tags to the created resources that Include the user ID that created the resource and the cost center ID The DevOps engineer configures an AWS Lambda Function with the cost center mappings to tag the resources. The DevOps engineer also sets up AWS CloudTrail in the AWS account. An Amazon S3 bucket stores the CloudTrail event logs Which solution will meet the tagging requirements?

A. Create an Amazon EventBridge rule that uses Amazon EC2 as the event source. Configure the rule to match events delivered by CloudTraiI. Configure the rule to target the Lambda function
B. Create an S3 event notification on the S3 bucket to invoke the Lambda function for s3. ObJectTagging:
Put events. Enable bucket versioning on the S3 bucket.
C. Create a recurring hourly Amazon EventBridge scheduled rule that invokes the Larnbda function.
Modify the Lambda function to read the logs from the S3 bucket
D. Enable server access logging on the S3 bucket. Create an S3 event notification on the S3 bucket for s3.
ObjectTaggIng.* events

Answer: A

Explanation:
Option A is incorrect because S3 event notifications do not support s3.ObjectTagging:Put events. S3 event notifications only support events related to object creation, deletion, replication, and restore. Moreover, enabling bucket versioning on the S3 bucket is not relevant to the tagging requirements, as it only keeps multiple versions of objects in the bucket.
Option B is incorrect because enabling server access logging on the S3 bucket does not help with tagging the resources. Server access logging only records requests for access to the bucket or its objects. It does not capture the user ID or the cost center ID of the resources. Furthermore, creating an S3 event notification on the S3 bucket for s3.ObjectTagging:Put events is not possible, as explained in option A.
Option C is incorrect because creating a recurring hourly Amazon EventBridge scheduled rule that invokes the Lambda function is not efficient or timely. The Lambda function would have to read the logs from the S3 bucket every hour and tag the resources accordingly, which could incur unnecessary costs and delays. A better solution would be to trigger the Lambda function as soon as a resource is created, rather than waiting for an hourly schedule.
Option D is correct because creating an Amazon EventBridge rule that uses Amazon EC2 as the event source and matches events delivered by CloudTrail is a valid way to tag the resources. CloudTrail records all API calls made to AWS services, including EC2, and delivers them as events to EventBridge. The EventBridge rule can filter the events based on the user ID and the resource type, and then target the Lambda function to tag the resources with the cost center ID. This solution meets the tagging requirements in a timely and efficient manner.
References:
S3 event notifications
Server access logging
Amazon EventBridge rules
AWS CloudTrail

NEW QUESTION # 44
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