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Questions # 21:

A company uses a trunk-based development branching strategy. The company has two AWS CodePipeline pipelines that are integrated with a Git provider. The pull_request pipeline has a branch filter that matches the feature branches. The main_branch pipeline has a branch filter that matches the main branch.

When pull requests are merged into the main branch, the pull requests are deployed by using the main_branch pipeline. The company ' s developers need test results for all submitted pull requests as quickly as possible from the pull_request pipeline. The company wants to ensure that the main_branch pipeline ' s test results finish and that each deployment is complete before the next pipeline execution.

Which solution will meet these requirements?

Options:

Configure the pull_request pipeline to use SUPERSEDED mode. Configure the main_branch pipeline to use QUEUED mode.

Configure the pull_request pipeline to use PARALLEL mode. Configure the main_branch pipeline to use QUEUED mode.

Configure the pull_request pipeline to use PARALLEL mode. Configure the main_branch pipeline to use SUPERSEDED mode.

Configure the pull_request pipeline to use QUEUED mode. Configure the main_branch pipeline to use SUPERSEDED mode.

Questions # 22:

A company is developing a web application that runs on Amazon EC2 Linux instances. The application requires monitoring of custom performance metrics. The company must collect metrics for API response times and database query latency across multiple instances. Which solution will generate the custom metrics with the LEAST operational overhead?

Options:

Install the Amazon CloudWatch agent on the instances. Configure the agent to collect the custom metrics. Instrument the application to send the metrics to the agent.

Use Amazon Managed Service for Prometheus to scrape the custom metrics from the application. Use the Amazon CloudWatch agent to forward the metrics to CloudWatch.

Create a custom AWS Lambda function that polls the application endpoints and database at regular intervals. Program the Lambda function to calculate the custom metrics and to send the metrics to Amazon CloudWatch by using PutMetricData API calls.

Implement custom logging in the application code to record the custom metrics. Use Amazon CloudWatch Logs Insights to extract and analyze the metrics.

Questions # 23:

A DevOps engineer needs to apply a core set of security controls to an existing set of AWS accounts. The accounts are in an organization in AWS Organizations. Individual teams will administer individual accounts by using the AdministratorAccess AWS managed policy. For all accounts. AWS CloudTrail and AWS Config must be turned on in all available AWS Regions. Individual account administrators must not be able to edit or delete any of the baseline resources. However, individual account administrators must be able to edit or delete their own CloudTrail trails and AWS Config rules.

Which solution will meet these requirements in the MOST operationally efficient way?

Options:

Enable AWS Control Tower. Enroll the existing accounts in AWS Control Tower. Grant the individual account administrators access to CloudTrail and AWS Config.

Designate an AWS Config management account. Create AWS Config recorders in all accounts by using AWS CloudFormation StackSets. Deploy AWS Config rules to the organization by using the AWS Config management account. Create a CloudTrail organization trail in the organization’s management account. Deny modification or deletion of the AWS Config recorders by using an SCP.

Create an AWS CloudFormation template that defines the standard account resources. Deploy the template to all accounts from the organization ' s management account by using Cloud Formation StackSets Create an SCP that prevents updates or deletions to CloudTrail resources or AWS Config resources unless the principal is an administrator of the organization ' s management account.

Questions # 24:

A company runs several applications in the same AWS account. The applications send logs to Amazon CloudWatch.

A data analytics team needs to collect performance metrics and custom metrics from the applications. The analytics team needs to transform the metrics data before storing the data in an Amazon S3 bucket. The analytics team must automatically collect any new metrics that are added to the CloudWatch namespace.

Which solution will meet these requirements with the LEAST operational overhead?

Options:

Configure a CloudWatch metric stream to include metrics from the application and the CloudWatch namespace. Configure the metric stream to deliver the metrics to an Amazon Data Firehose delivery stream. Configure the Firehose delivery stream to invoke an AWS Lambda function to transform the data. Configure the delivery stream to send the transformed data to the S3 bucket.

Configure a CloudWatch metrics stream to include all the metrics and to deliver the metrics to an Amazon Data Firehose delivery stream. Configure the Firehose delivery stream to invoke an AWS Lambda function to transform the data. Configure the delivery stream to send the transformed data to the S3 bucket.

Configure metric filters for the CloudWatch logs to create custom metrics. Configure a CloudWatch metric stream to deliver the application metrics to the S3 bucket.

Configure subscription filters on the application log groups to target an Amazon Data Firehose delivery stream. Configure the Firehose delivery stream to invoke an AWS Lambda function to transform the data. Configure the delivery stream to send the transformed data to the S3 bucket.

Questions # 25:

A DevOps engineer is implementing governance controls for a company that requires its infrastructure to be housed within the United States. The company has many AWS accounts in an organization in AWS Organizations that has all features enabled. The engineer must restrict which AWS Regions the company can use. The engineer must also ensure that an alert is sent as soon as possible if any activity outside the governance policy occurs. The controls must be automatically enabled on any new Region outside the United States. Which combination of steps will meet these requirements? (Select TWO.)

Options:

Create an Organizations SCP deny policy that has a condition that the aws:RequestedRegion property does not match a list of all US Regions. Include an exception in the policy for global services. Attach the policy to the root of the organization.

Configure AWS CloudTrail to send logs to Amazon CloudWatch Logs. Enable CloudTrail for all Regions. Use a CloudWatch Logs metric filter to create a metric in non-US Regions. Configure a CloudWatch alarm to send an alert if the metric is greater than 0.

Use an AWS Lambda function that checks for AWS service activity. Deploy the Lambda function to all Regions. Write an Amazon EventBridge rule that runs the Lambda function every hour. Configure the rule to send an alert if the Lambda function finds any activity in a non-US Region.

Use an AWS Lambda function to query Amazon Inspector to look for service activity in non-US Regions. Configure the Lambda function to send alerts if Amazon Inspector finds any activity.

Create an Organizations SCP allow policy that has a condition that the aws:RequestedRegion property matches a list of all US Regions. Include an exception in the policy for global services. Attach the policy to the root of the organization.

Questions # 26:

A company has a guideline that every Amazon EC2 instance must be launched from an AMI that the company ' s security team produces Every month the security team sends an email message with the latest approved AMIs to all the development teams.

The development teams use AWS CloudFormation to deploy their applications. When developers launch a new service they have to search their email for the latest AMIs that the security department sent. A DevOps engineer wants to automate the process that the security team uses to provide the AMI IDs to the development teams.

What is the MOST scalable solution that meets these requirements?

Options:

Direct the security team to use CloudFormation to create new versions of the AMIs and to list! the AMI ARNs in an encrypted Amazon S3 object as part of the stack ' s Outputs Section Instruct the developers to use a cross-stack reference to load the encrypted S3 object and obtain the most recent AMI ARNs.

Direct the security team to use a CloudFormation stack to create an AWS CodePipeline pipeline that builds new AMIs and places the latest AMI ARNs in an encrypted Amazon S3 object as part of the pipeline output Instruct the developers to use a cross-stack reference within their own CloudFormation template to obtain the S3 object location and the most recent AMI ARNs.

Direct the security team to use Amazon EC2 Image Builder to create new AMIs and to place the AMI ARNs as parameters in AWS Systems Manager Parameter Store Instruct the developers to specify a parameter of type SSM in their CloudFormation stack to obtain the most recent AMI ARNs from Parameter Store.

Direct the security team to use Amazon EC2 Image Builder to create new AMIs and to create an Amazon Simple Notification Service (Amazon SNS) topic so that every development team can receive notifications. When the development teams receive a notification instruct them to write an AWS Lambda function that will update their CloudFormation stack with the most recent AMI ARNs.

Questions # 27:

A company ' s application uses a fleet of Amazon EC2 On-Demand Instances to analyze and process data. The EC2 instances are in an Auto Scaling group. The Auto Scaling group is a target group for an Application Load Balancer (ALB). The application analyzes critical data that cannot tolerate interruption. The application also analyzes noncritical data that can withstand interruption.

The critical data analysis requires quick scalability in response to real-time application demand. The noncritical data analysis involves memory consumption. A DevOps engineer must implement a solution that reduces scale-out latency for the critical data. The solution also must process the noncritical data.

Which combination of steps will meet these requirements? (Select TWO.)

Options:

For the critical data, modify the existing Auto Scaling group. Create a warm pool instance in the stopped state. Define the warm pool size. Create a new version of the launch template that has detailed monitoring enabled. use Spot Instances.

For the critical data. modify the existing Auto Scaling group. Create a lifecycle hook to ensure that bootstrap scripts are completed successfully. Ensure that the application on the instances is ready to accept traffic before the instances are registered. Create a new version of the launch template that has detailed monitoring enabled.

For the noncritical data, create a second Auto Scaling group that uses a launch template. Configure the launch template to install the unified Amazon CloudWatch agent and to configure the CloudWatch agent with a custom memory utilization metric. Use Spot Instances. Add the new Auto Scaling group as the target group for the ALB. Modify the application to use two target groups for critical data and noncritical data.

For the noncritical data, create a second Auto Scaling group. Choose the predefined memory utilization metric type for the target tracking scaling policy. Use Spot Instances. Add the new Auto Scaling group as the target group for the ALB. Modify the application to use two target groups for critical data and noncritical data.

Questions # 28:

A company uses AWS CodePipeline and AWS CodeDeploy to deploy application code to Amazon EC2 instances. The EC2 instances send application logs and CodeDeploy logs to Amazon CloudWatch.

Recently, the company manually rolled back a deployment because of application errors. The company wants to automate the rollback process when application errors occur.

Which solution will meet these requirements?

Options:

Create a CloudWatch metric based on the application logs. Create a CloudWatch alarm based on the metric that will activate when application errors occur. Change the deployment group settings to use the CloudWatch alarm configuration. Configure the deployment group to use an auto rollback configuration.

Configure a CloudWatch alarm that uses a custom metric for application errors that are recorded in the CodeDeploy agent logs. Configure the current deployment to use the CloudWatch alarm for its alarm configuration. Configure the deployment to use an auto rollback configuration.

Create an AWS Lambda function that will create a new deployment by using the last successful application deployment. Create an Amazon EventBridge rule that matches events from CodeDeploy that have a deployment status of FAILURE. Configure the EventBridge rule to target the Lambda function.

Create an AWS Lambda function that will create a new deployment group for the application deployment. Create a CloudWatch alarm based on metrics from the application logs. Configure the alarm to activate when an application error occurs on an EC2 instance. Configure the CloudWatch alarm to invoke the Lambda function.

Questions # 29:

A DevOps engineer needs to implement a CI/CD pipeline in an AWS account. The pipeline must consume sensitive database credentials that are stored in an AWS Systems Manager Parameter Store parameter. The Parameter Store parameter is in a separate central account. The DevOps engineer needs to create and integrate the parameter with the CI/CD account.

Which combination of steps will meet these requirements? (Select THREE.)

Options:

Use an advanced tier Parameter Store parameter to store the database credentials in the central AWS account.

Create an IAM role in the AWS account that hosts the CI/CD pipeline. Add the full ARN of the parameter to the IAM policy that is associated with the IAM role.

Use a standard tier Parameter Store parameter to store the database credentials in the central AWS account.

Use an AWS KMS managed key to encrypt the parameter. Grant decrypt permissions for the KMS key to the AWS account that hosts the CI/CD pipeline.

Use a customer managed AWS KMS key to encrypt the parameter. Grant decrypt permissions for the customer managed key to the AWS account that hosts the CI/CD pipeline.

Create an AWS Resource Access Manager (AWS RAM) resource share in the central AWS account. Share the parameter with the account that hosts the CI/CD pipeline.

Questions # 30:

A company deploys a web application on Amazon EC2 instances that are behind an Application Load Balancer (ALB). The company stores the application code in an AWS CodeCommit repository. When code is merged to the main branch, an AWS Lambda function invokes an AWS CodeBuild project. The CodeBuild project packages the code, stores the packaged code in AWS CodeArtifact, and invokes AWS Systems Manager Run Command to deploy the packaged code to the EC2 instances.

Previous deployments have resulted in defects, EC2 instances that are not running the latest version of the packaged code, and inconsistencies between instances.

Which combination of actions should a DevOps engineer take to implement a more reliable deployment solution? (Select TWO.)

Options:

Create a pipeline in AWS CodePipeline that uses the CodeCommit repository as a source provider. Create separate pipeline stages that run a CodeBuild project to build and then test the application. In the pipeline, pass the CodeBuild project output artifact to an AWS CodeDeploy action.

Create an AWS CodeDeploy application and a deployment group to deploy the packaged code to the EC2 instances. Configure the ALB for the deployment group.

Create individual Lambda functions that use AWS CodeDeploy instead of Systems Manager to run build, test, and deploy actions.

Create an Amazon S3 bucket. Modify the CodeBuild project to store the packages in the S3 bucket instead of in CodeArtifact. Use deploy actions in CodeDeploy to deploy the artifact to the EC2 instances.

Answer

A, C

Explanation

To implement a more reliable deployment solution, a DevOps engineer should take the following actions:

Create a pipeline in AWS CodePipeline that uses the CodeCommit repository as a source provider. Configure pipeline stages that run the CodeBuild project in parallel to build and test the application. In the pipeline, pass the CodeBuild project output artifact to an AWS CodeDeploy action. This action will improve the deployment reliability by automating the entire process from code commit to deployment, reducing human errors and inconsistencies. By running the build and test stages in parallel, the pipeline can also speed up the delivery time and provide faster feedback. By using CodeDeploy as the deployment action, the pipeline can leverage the features of CodeDeploy, such as traffic shifting, health checks, rollback, and deployment configuration123

Create an AWS CodeDeploy application and a deployment group to deploy the packaged code to the EC2 instances. Configure the ALB for the deployment group. This action will improve the deployment reliability by using CodeDeploy to orchestrate the deployment across multiple EC2 instances behind an ALB. CodeDeploy can perform blue/green deployments or in-place deployments with traffic shifting, which can minimize downtime and reduce risks. CodeDeploy can also monitor the health of the instances during and after the deployment, and automatically roll back if any issues are detected. By configuring the ALB for the deployment group, CodeDeploy can register and deregister instances from the load balancer as needed, ensuring that only healthy instances receive traffic45

The other options are not correct because they do not improve the deployment reliability or follow best practices. Creating separate pipeline stages that run a CodeBuild project to build and then test the application is not a good option because it will increase the pipeline execution time and delay the feedback loop. Creating individual Lambda functions that use CodeDeploy instead of Systems Manager to run build, test, and deploy actions is not a valid option because it will add unnecessary complexity and cost to the solution. Lambda functions are not designed for long-running tasks such as building or deploying applications. Creating an Amazon S3 bucket and modifying the CodeBuild project to store the packages in the S3 bucket instead of in CodeArtifact is not a necessary option because it will not affect the deployment reliability. CodeArtifact is a secure, scalable, and cost-effective package management service that can store and share software packages for application development67

1: What is AWS CodePipeline? - AWS CodePipeline

2: Create a pipeline in AWS CodePipeline - AWS CodePipeline

3: Deploy an application with AWS CodeDeploy - AWS CodePipeline

4: What is AWS CodeDeploy? - AWS CodeDeploy

5: Configure an Application Load Balancer for your blue/green deployments - AWS CodeDeploy

6: What is AWS Lambda? - AWS Lambda

7: What is AWS CodeArtifact? - AWS CodeArtifact

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Viewing questions 21-30 out of questions