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Amazon DOP-C02 Exam consists of multiple-choice and multiple-response questions that assess the candidate's ability to design, deploy, and manage highly available, fault-tolerant, and scalable systems on the AWS platform. DOP-C02 exam is timed, and candidates have 180 minutes to complete it. To pass the exam, candidates must achieve a minimum score of 750 out of 1000.
Achieving the AWS Certified DevOps Engineer - Professional certification can open up many career opportunities for IT professionals. AWS Certified DevOps Engineer - Professional certification validates a candidate's expertise in designing, deploying, and operating scalable and highly available systems on AWS, which is a highly sought-after skillset in today's technology landscape. Additionally, this certification demonstrates a candidate's commitment to their professional development and their ability to adapt to new technologies and practices in the rapidly-evolving field of DevOps.
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The AWS Certified DevOps Engineer - Professional Exam tests a candidate's knowledge and expertise in designing, managing, and maintaining AWS services for the purposes of DevOps. This includes continuous delivery, automation, monitoring, and infrastructure as code. In order to Pass DOP-C02 Exam, candidates must have experience with AWS services and must be proficient in working with AWS tools such as AWS Elastic Beanstalk, AWS CodePipeline, AWS CodeDeploy, and AWS CloudFormation.
NEW QUESTION # 329
A company releases a new application in a new AWS account. The application includes an AWS Lambda function that processes messages from an Amazon Simple Queue Service (Amazon SOS) standard queue. The Lambda function stores the results in an Amazon S3 bucket for further downstream processing. The Lambda function needs to process the messages within a specific period of time after the messages are published. The Lambda function has a batch size of 10 messages and takes a few seconds to process a batch of messages.
As load increases on the application's first day of service, messages in the queue accumulate at a greater rate than the Lambda function can process the messages. Some messages miss the required processing timelines.
The logs show that many messages in the queue have data that is not valid. The company needs to meet the timeline requirements for messages that have valid data.
Which solution will meet these requirements?
Answer: A
Explanation:
* Step 1: Handling Invalid Data with Failed Batch ItemsThe Lambda function is processing batches of messages, and some messages contain invalid data, causing processing delays. Lambda provides the capability to report failed batch items, which allows valid messages to be processed while skipping invalid ones. This functionality ensures that the valid messages are processed within the required timeline.
* Action:Keep the Lambda function's batch size the same and configure it to report failed batch items.
* Why:By reporting failed batch items, the Lambda function can skip invalid messages and continue processing valid ones, ensuring that they meet the processing timeline.
NEW QUESTION # 330
A company manages environments for its application in multiple AWS accounts. Each environment account is in a different OU in AWS Organizations.
A DevOps team is responsible for the application deployment process across the environments. The deployment process uses an AWS CodePipeline pipeline in a Shared Services account. The DevOps team members are in the same user group. The team members have administrative access to all accounts through AWS IAM Identity Center.
A recent deployment problem in the development environment required the DevOps team to perform manual steps. The deployment to the production environment then resulted in an incident that caused the pipeline to fail, blocking new deployments for several hours.
A DevOps engineer needs to ensure that only the pipeline can perform deployments in the production environment. The DevOps engineer must have access to the environment in case of an emergency.
Which solution will meet these requirements with the MOST operational efficiency?
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The requirement is to restrict production deployments strictly to the pipeline, while still allowing emergency access to a specific engineer.
The best approach is to restrict the DevOps team to read-only access in production accounts, minimizing risk of manual changes (Option A).
The DevOps engineer can have an admin permission set but assume the pipeline IAM role for deployment, enforcing strict control.
Applying an SCP to deny modification by anyone other than the pipeline role enforces this at the organization level.
Option B is similar but unnecessarily creates separate IAM users, increasing management overhead. Option C grants the DevOps engineer broader permissions that may conflict with controls. Option D complicates management with tagging and SCPs, increasing operational overhead.
Reference:
AWS Organizations Service Control Policies (SCPs):
"SCPs can restrict what actions identities in member accounts can perform, even for administrators." (AWS Organizations SCP Documentation) IAM Identity Center Role Assumption Best Practices:
"Use role assumption for limited elevated permissions instead of broad admin access." (AWS IAM Best Practices)
NEW QUESTION # 331
A DevOps engineer is deploying a new version of a company's application in an AWS CodeDeploy deployment group associated with its Amazon EC2 instances. After some time, the deployment fails. The engineer realizes that all the events associated with the specific deployment ID are in a Skipped status and code was not deployed in the instances associated with the deployment group.
What are valid reasons for this failure? (Select TWO.).
Answer: A,E
Explanation:
Explanation
https://docs.aws.amazon.com/codedeploy/latest/userguide/troubleshooting-deployments.html#troubleshooting-sk
NEW QUESTION # 332
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?
Answer: B
Explanation:
Explanation
https://docs.aws.amazon.com/codedeploy/latest/userguide/deployment-configurations.html
NEW QUESTION # 333
A company requires its internal business teams to launch resources through pre-approved AWS CloudFormation templates only. The security team requires automated monitoring when resources drift from their expected state.
Which strategy should be used to meet these requirements?
Answer: D
Explanation:
The correct answer is C. Allowing users to deploy CloudFormation stacks using AWS Service Catalog only and enforcing the use of a launch constraint is the best way to ensure that the internal business teams launch resources through pre-approved CloudFormation templates only. AWS Service Catalog is a service that enables organizations to create and manage catalogs of IT services that are approved for use on AWS. A launch constraint is a rule that specifies the role that AWS Service Catalog assumes when launching a product. By using a launch constraint, the DevOps engineer can control the permissions that the users have when launching a product. Using AWS Config rules to detect when resources have drifted from their expected state is the best way to automate the monitoring of the resources. AWS Config is a service that enables you to assess, audit, and evaluate the configurations of your AWS resources. AWS Config rules are custom or managed rules that AWS Config uses to evaluate whether your AWS resources comply with your desired configurations. By using AWS Config rules, the DevOps engineer can track the changes in the resources and identify any non-compliant resources.
Option A is incorrect because allowing users to deploy CloudFormation stacks using a CloudFormation service role only is not the best way to ensure that the internal business teams launch resources through pre- approved CloudFormation templates only. A CloudFormation service role is an IAM role that CloudFormation assumes to create, update, or delete the stack resources. By using a CloudFormation service role, the DevOps engineer can control the permissions that CloudFormation has when acting on the resources, but not the permissions that the users have when launching a stack. Therefore, option A does not prevent the users from launching resources that are not approved by the company. Using CloudFormation drift detection to detect when resources have drifted from their expected state is a valid way to monitor the resources, but it is not as automated and scalable as using AWS Config rules. CloudFormation drift detection is a feature that enables you to detect whether a stack's actual configuration differs, or has drifted, from its expected configuration. To use this feature, the DevOps engineer would need to manually initiate a drift detection operation on the stack or the stack resources, and then view the drift status and details in the CloudFormation console or API.
Option B is incorrect because allowing users to deploy CloudFormation stacks using a CloudFormation service role only is not the best way to ensure that the internal business teams launch resources through pre- approved CloudFormation templates only, as explained in option A. Using AWS Config rules to detect when resources have drifted from their expected state is a valid way to monitor the resources, as explained in option
C).
Option D is incorrect because enforcing the use of a template constraint is not the best way to ensure that the internal business teams launch resources through pre-approved CloudFormation templates only. A template constraint is a rule that defines the values or properties that users can specify when launching a product. By using a template constraint, the DevOps engineer can control the parameters that the users can provide when launching a product, but not the permissions that the users have when launching a product. Therefore, option D does not prevent the users from launching resources that are not approved by the company. Using Amazon EventBridge notifications to detect when resources have drifted from their expected state is a less reliable and consistent solution than using AWS Config rules. Amazon EventBridge is a service that enables you to connect your applications with data from a variety of sources. Amazon EventBridge can deliver a stream of real-time data from event sources, such as AWS services, and route that data to targets, such as AWS Lambda functions. However, to use this solution, the DevOps engineer would need to configure the event source, the event bus, the event rule, and the event target for each resource type that needs to be monitored, which is more complex and error-prone than using AWS Config rules.
NEW QUESTION # 334
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