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Amazon DOP-C02 Exam is designed for experienced DevOps professionals seeking to validate their expertise and earn the AWS Certified DevOps Engineer - Professional certification. AWS Certified DevOps Engineer - Professional certification is intended for individuals who have a deep understanding of DevOps methodologies, practices, and tools, as well as experience deploying and managing applications on the AWS platform.
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NEW QUESTION # 203
A DevOps engineer is working on a project that is hosted on Amazon Linux and has failed a security review. The DevOps manager has been asked to review the company buildspec. yaml die for an AWS CodeBuild project and provide recommendations. The buildspec. yaml file is configured as follows:
What changes should be recommended to comply with AWS security best practices? (Select THREE.)
Answer: A,D,E
Explanation:
B . Update the CodeBuild project role with the necessary permissions and then remove the AWS credentials from the environment variable. C. Store the DB_PASSWORD as a SecureString value in AWS Systems Manager Parameter Store and then remove the DB_PASSWORD from the environment variables. E. Use AWS Systems Manager run command versus scp and ssh commands directly to the instance.
NEW QUESTION # 204
A DevOps team uses AWS CodePipeline, AWS CodeBuild, and AWS CodeDeploy to deploy an application. The application is a REST API that uses AWS Lambda functions and Amazon API Gateway Recent deployments have introduced errors that have affected many customers.
The DevOps team needs a solution that reverts to the most recent stable version of the application when an error is detected. The solution must affect the fewest customers possible.
Which solution Will meet these requirements With the MOST operational efficiency?
Answer: D
Explanation:
Option A is incorrect because setting the deployment configuration to LambdaAllAtOnce means that the new version of the application will be deployed to all Lambda functions at once, affecting all customers. This does not meet the requirement of affecting the fewest customers possible. Moreover, configuring automatic rollbacks on the deployment group is not operationally efficient, as it requires manual intervention to fix the errors and redeploy the application.
Option B is correct because setting the deployment configuration to LambdaCanary10Percent10Minutes means that the new version of the application will be deployed to 10 percent of the Lambda functions first, and then to the remaining 90 percent after 10 minutes. This minimizes the impact of errors on customers, as only 10 percent of them will be affected by a faulty deployment. Configuring automatic rollbacks on the deployment group also meets the requirement of reverting to the most recent stable version of the application when an error is detected. Creating a CloudWatch alarm that detects HTTP Bad Gateway errors on API Gateway is a valid way to monitor the health of the application and trigger a rollback if needed.
Option C is incorrect because setting the deployment configuration to LambdaAllAtOnce means that the new version of the application will be deployed to all Lambda functions at once, affecting all customers. This does not meet the requirement of affecting the fewest customers possible. Moreover, configuring manual rollbacks on the deployment group is not operationally efficient, as it requires human intervention to stop the current deployment and start a new one. Creating an SNS topic to send notifications every time a deployment fails is not sufficient to detect errors in the application, as it does not monitor the API Gateway responses.
Option D is incorrect because configuring manual rollbacks on the deployment group is not operationally efficient, as it requires human intervention to stop the current deployment and start a new one. Creating a metric filter on a CloudWatch log group for API Gateway to monitor HTTP Bad Gateway errors is a valid way to monitor the health of the application, but invoking a new Lambda function to perform a rollback is unnecessary and complex, as CodeDeploy already provides automatic rollback functionality.
References:
AWS CodeDeploy Deployment Configurations
[AWS CodeDeploy Rollbacks]
Amazon CloudWatch Alarms
NEW QUESTION # 205
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?
Answer: A
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 # 206
A company has an AWS CodePipeline pipeline that is configured with an Amazon S3 bucket in the eu-west-1 Region. The pipeline deploys an AWS Lambda application to the same Region. The pipeline consists of an AWS CodeBuild project build action and an AWS CloudFormation deploy action.
The CodeBuild project uses the aws cloudformation package AWS CLI command to build an artifact that contains the Lambda function code's .zip file and the CloudFormation template. The CloudFormation deploy action references the CloudFormation template from the output artifact of the CodeBuild project's build action.
The company wants to also deploy the Lambda application to the us-east-1 Region by using the pipeline in eu-west-1. A DevOps engineer has already updated the CodeBuild project to use the aws cloudformation package command to produce an additional output artifact for us-east-1.
Which combination of additional steps should the DevOps engineer take to meet these requirements? (Choose two.)
Answer: C,E
Explanation:
A) The CloudFormation template should be modified to include a parameter that indicates the location of the .zip file containing the Lambda function's code. This allows the CloudFormation deploy action to use the correct artifact depending on the region. This is critical because Lambda functions need to reference their code artifacts from the same region they are being deployed in.
B) You would also need to create a new CloudFormation deploy action for the us-east-1 Region within the pipeline. This action should be configured to use the CloudFormation template from the artifact that was specifically created for us-east-1.
NEW QUESTION # 207
A company is refactoring applications to use AWS. The company identifies an internal web application that needs to make Amazon S3 API calls in a specific AWS account.
The company wants to use its existing identity provider (IdP) auth.company.com for authentication. The IdP supports only OpenID Connect (OIDC). A DevOps engineer needs to secure the web application's access to the AWS account.
Which combination of steps will meet these requirements? (Select THREE.)
Answer: A,C,F
Explanation:
Step 1: Creating an Identity Provider in IAM
You first need to configure AWS to trust the external identity provider (IdP), which in this case supports OpenID Connect (OIDC). The IdP will handle the authentication, and AWS will handle the authorization based on the IdP's token.
Action: Create an IAM Identity Provider (IdP) in AWS using the existing provider's URL, audience, and signature. This step is essential for establishing trust between AWS and the external IdP.
Why: This allows AWS to accept tokens from your external IdP (auth.company.com) for authentication.
Reference:
So, this corresponds to Option B: Create an IAM IdP by using the provider URL, audience, and signature from the existing IdP.
Step 2: Creating an IAM Role with Specific Permissions
Next, you need to create an IAM role with a trust policy that allows the external IdP to assume it when certain conditions are met. Specifically, the trust policy needs to allow the role to be assumed based on the context key auth.company.com:aud (audience claim in the token).
Action: Create an IAM role that has the necessary permissions (e.g., Amazon S3 access). The role's trust policy should specify the OIDC IdP as the trusted entity and validate the audience claim (auth.company.com:aud), which comes from the token provided by the IdP.
Why: This step ensures that only the specified web application authenticated via OIDC can assume the IAM role to make API calls.
This corresponds to Option D: Create an IAM role that has a policy that allows the necessary S3 actions. Configure the role's trust policy to allow the OIDC IdP to assume the role if the auth.company.com:aud context key is appid_from_idp.
Step 3: Using Temporary Credentials via AssumeRoleWithWebIdentity API
To securely make Amazon S3 API calls, the web application will need temporary credentials. The web application can use the AssumeRoleWithWebIdentity API call to assume the IAM role configured in the previous step and obtain temporary AWS credentials. These credentials can then be used to interact with Amazon S3.
Action: The web application must be configured to call the AssumeRoleWithWebIdentity API operation, passing the OIDC token from the IdP to obtain temporary credentials.
Why: This allows the web application to authenticate via the external IdP and then authorize access to AWS resources securely using short-lived credentials.
This corresponds to Option E: Configure the web application to use the AssumeRoleWithWebIdentity API operation to retrieve temporary credentials. Use the temporary credentials to make the S3 API calls.
Summary of Selected Answers:
B: Create an IAM IdP by using the provider URL, audience, and signature from the existing IdP.
D: Create an IAM role that has a policy that allows the necessary S3 actions. Configure the role's trust policy to allow the OIDC IdP to assume the role if the auth.company.com:aud context key is appid_from_idp.
E: Configure the web application to use the AssumeRoleWithWebIdentity API operation to retrieve temporary credentials. Use the temporary credentials to make the S3 API calls.
This setup enables the web application to use OpenID Connect (OIDC) for authentication and securely interact with Amazon S3 in a specific AWS account using short-lived credentials obtained through AWS Security Token Service (STS).
NEW QUESTION # 208
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