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A DevOps engineer manages a Java-based application that runs in an Amazon Elastic Container Service (Amazon ECS) cluster on AWS Fargate. Auto scaling has not been configured for the application. The DevOps engineer has determined that the Java Virtual Machine (JVM) thread count is a good indicator of when to scale the application. The application serves customer traffic on port 8080 and makes JVM metrics available on port 9404. Application use has recently increased. The DevOps engineer needs to configure auto scaling for the application. Which solution will meet these requirements with the LEAST operational overhead?

A.

Deploy the Amazon CloudWatch agent as a container sidecar. Configure the CloudWatch agent to retrieve JVM metrics from port 9404. Create CloudWatch alarms on the JVM thread count metric to scale the application. Add a step scaling policy in Fargate to scale up and scale down based on the CloudWatch alarms.

B.

Deploy the Amazon CloudWatch agent as a container sidecar. Configure a metric filter for the JVM thread count metric on the CloudWatch log group for the CloudWatch agent. Add a target tracking policy in Fargate. Select the metric from the metric filter as a scale target.

C.

Create an Amazon Managed Service for Prometheus workspace. Deploy AWS Distro for OpenTelemetry as a container sidecar to publish the JVM metrics from port 9404 to the Prometheus workspace. Configure rules for the workspace to use the JVM thread count metric to scale the application. Add a step scaling policy in Fargate. Select the Prometheus rules to scale up and scaling down.

D.

Create an Amazon Managed Service for Prometheus workspace. Deploy AWS Distro for OpenTelemetry as a container sidecar to retrieve JVM metrics from port 9404 to publish the JVM metrics from port 9404 to the Prometheus workspace. Add a target tracking policy in Fargate. Select the Prometheus metric as a scale target.

A DevOps engineer has implemented a Cl/CO pipeline to deploy an AWS Cloud Format ion template that provisions a web application. The web application consists of an Application Load Balancer (ALB) a target group, a launch template that uses an Amazon Linux 2 AMI an Auto Scaling group of Amazon EC2 instances, a security group and an Amazon RDS for MySQL database The launch template includes user data that specifies a script to install and start the application.

The initial deployment of the application was successful. The DevOps engineer made changes to update the version of the application with the user data. The CI/CD pipeline has deployed a new version of the template However, the health checks on the ALB are now failing The health checks have marked all targets as unhealthy.

During investigation the DevOps engineer notices that the Cloud Formation stack has a status of UPDATE_COMPLETE. However, when the DevOps engineer connects to one of the EC2 instances and checks /varar/log messages, the DevOps engineer notices that the Apache web server failed to start successfully because of a configuration error

How can the DevOps engineer ensure that the CloudFormation deployment will fail if the user data fails to successfully finish running?

A.

Use the cfn-signal helper script to signal success or failure to CloudFormation Use the WaitOnResourceSignals update policy within the CloudFormation template Set an appropriate timeout for the update policy.

B.

Create an Amazon CloudWatch alarm for the UnhealthyHostCount metric. Include an appropriate alarm threshold for the target group Create an Amazon Simple Notification Service (Amazon SNS) topic as the target to signal success or failure to CloudFormation

C.

Create a lifecycle hook on the Auto Scaling group by using the AWS AutoScaling LifecycleHook resource Create an Amazon Simple Notification Service (Amazon SNS) topic as the target to signal success or failure to CloudFormation Set an appropriate timeout on the lifecycle hook.

D.

Use the Amazon CloudWatch agent to stream the cloud-init logs Create a subscription filter that includes an AWS Lambda function with an appropriate invocation timeout Configure the Lambda function to use the SignalResource API operation to signal success or failure to CloudFormation.

A DevOps team supports an application that runs on a large number of Amazon EC2 instances in an Auto Scaling group. The DevOps team uses AWS CloudFormation to deploy the EC2 instances. The application recently experienced an issue. A single instance returned errors to a large percentage of requests. The EC2 instance responded as healthy to both Amazon EC2 and Elastic Load Balancing health checks. The DevOps team collects application logs in Amazon CloudWatch by using the embedded metric format. The DevOps team needs to receive an alert if any EC2 instance is responsible for more than half of all errors. Which combination of steps will meet these requirements with the LEAST operational overhead? (Select TWO.)

A.

Create a CloudWatch Contributor Insights rule that groups logs from the CloudWatch application logs based on instance ID and errors.

B.

Create a resource group in AWS Resource Groups. Use the CloudFormation stack to group the resources for the application. Add the application to CloudWatch Application Insights. Use the resource group to identify the application.

C.

Create a metric filter for the application logs to count the occurrence of the term "Error." Create a CloudWatch alarm that uses the METRIC_COUNT function to determine whether errors have occurred. Configure the CloudWatch alarm to send a notification to an Amazon Simple Notification Service (Amazon SNS) topic to notify the DevOps team.

D.

Create a CloudWatch alarm that uses the INSIGHT_RULE_METRIC function to determine whether a specific instance is responsible for more than half of all errors reported by EC2 instances. Configure the CloudWatch alarm to send a notification to an Amazon Simple Notification Service (Amazon SNS) topic to notify the DevOps team.

E.

Create a CloudWatch subscription filter for the application logs that filters for errors and invokes an AWS Lambda function. Configure the Lambda function to send the instance ID and error in a notification to an Amazon Simple Notification Service (Amazon SNS) topic to notify the DevOps team.

A company runs an application on Amazon EKS. The company needs comprehensive logging for control plane and nodes, analyze API requests, and monitor container performance with minimal operational overhead.

Which solution meets these requirements?

A.

Enable CloudTrail for control plane logging; deploy Logstash as a ReplicaSet on nodes; use OpenSearch to store and analyze logs.

B.

Enable control plane logging for EKS and send logs to CloudWatch; use CloudWatch Container Insights for node and container logs; use CloudWatch Logs Insights to query logs.

C.

Enable API server control plane logging and send to S3; deploy Kubernetes Event Exporter on nodes; send logs to S3; use Athena and QuickSight for analysis.

D.

Use AWS Distro for OpenTelemetry; stream logs to Firehose; analyze data in Redshift.

A company has an application that runs on AWS Lambda and sends logs to Amazon CloudWatch Logs. An Amazon Kinesis data stream is subscribed to the log groups in CloudWatch Logs. A single consumer Lambda function processes the logs from the data stream and stores the logs in an Amazon S3 bucket.

The company's DevOps team has noticed high latency during the processing and ingestion of some logs.

Which combination of steps will reduce the latency? (Select THREE.)

A.

Create a data stream consumer with enhanced fan-out. Set the Lambda function that processes the logs as the consumer.

B.

Increase the ParallelizationFactor setting in the Lambda event source mapping.

C.

Configure reserved concurrency for the Lambda function that processes the logs.

D.

Increase the batch size in the Kinesis data stream.

E.

Turn off the ReportBatchltemFailures setting in the Lambda event source mapping.

F.

Increase the number of shards in the Kinesis data stream.

A company runs a microservices application on Amazon EKS. Users report delays accessing an account summary feature during peak hours. CloudWatch metrics and logs show normal CPU and memory utilization on EKS nodes. The DevOps engineer cannot identify where delays occur within the microservices.

Which solution will meet these requirements?

A.

Deploy the AWS X-Ray daemon as a DaemonSet in the EKS cluster. Use the X-Ray SDK to instrument the application code. Redeploy the application.

B.

Enable CloudWatch Container Insights for the EKS cluster. Use the Container Insights data to diagnose delays.

C.

Create alarms based on existing CloudWatch metrics. Set up SNS email alerts.

D.

Increase the timeout settings in the application code for network operations.

A company uses Amazon S3 to store proprietary information. The development team creates buckets for new projects on a daily basis. The security team wants to ensure that all existing and future buckets have encryption logging and versioning enabled. Additionally, no buckets should ever be publicly read or write accessible.

What should a DevOps engineer do to meet these requirements?

A.

Enable AWS CloudTrail and configure automatic remediation using AWS Lambda.

B.

Enable AWS Conflg rules and configure automatic remediation using AWS Systems Manager documents.

C.

Enable AWS Trusted Advisor and configure automatic remediation using Amazon EventBridge.

D.

Enable AWS Systems Manager and configure automatic remediation using Systems Manager documents.

A company has application code in an AWS CodeConnections compatible Git repository. The company wants to configure unit tests to run when pull requests are opened. The company wants to ensure that the test status is visible in pull requests when the tests are completed. The company wants to save output data files that the tests generate to an Amazon S3 bucket after the tests are finished. Which combination of solutions will meet these requirements? (Select THREE.)

A.

Create an IAM service role to allow access to the resources that are required to run the tests.

B.

Create a pipeline in AWS CodePipeline that has a test stage. Create a trigger to run the pipeline when pull requests are created or updated. Add a source action to report test results.

C.

Create an AWS CodeBuild project to run the tests. Enable webhook triggers to run the tests when pull requests are created or updated. Enable build status reporting to report test results.

D.

Create a buildspec.yml file that has a reports section to upload output files when the tests have finished running.

E.

Create a buildspec.yml file that has an artifacts section to upload artifacts when the tests have finished running.

F.

Create an appspec.yml file that has a files section to upload output files when the tests have finished running.

A company uses AWS CodePipeline pipelines to automate releases of its application A typical pipeline consists of three stages build, test, and deployment. The company has been using a separate AWS CodeBuild project to run scripts for each stage. However, the company now wants to use AWS CodeDeploy to handle the deployment stage of the pipelines.

The company has packaged the application as an RPM package and must deploy the application to a fleet of Amazon EC2 instances. The EC2 instances are in an EC2 Auto Scaling group and are launched from a common AMI.

Which combination of steps should a DevOps engineer perform to meet these requirements? (Choose two.)

A.

Create a new version of the common AMI with the CodeDeploy agent installed. Update the IAM role of the EC2 instances to allow access to CodeDeploy.

B.

Create a new version of the common AMI with the CodeDeploy agent installed. Create an AppSpec file that contains application deployment scripts and grants access to CodeDeploy.

C.

Create an application in CodeDeploy. Configure an in-place deployment type. Specify the Auto Scaling group as the deployment target. Add a step to the CodePipeline pipeline to use EC2 Image Builder to create a new AMI. Configure CodeDeploy to deploy the newly created AMI.

D.

Create an application in CodeDeploy. Configure an in-place deployment type. Specify the Auto Scaling group as the deployment target. Update the CodePipeline pipeline to use the CodeDeploy action to deploy the application.

E.

Create an application in CodeDeploy. Configure an in-place deployment type. Specify the EC2 instances that are launched from the common AMI as the deployment target. Update the CodePipeline pipeline to use the CodeDeploy action to deploy the application.

A DevOps engineer is building a multistage pipeline with AWS CodePipeline to build, verify, stage, test, and deploy an application. A manual approval stage is required between the test stage and the deploy stage. The development team uses a custom chat tool with webhook support that requires near-real-time notifications.

How should the DevOps engineer configure status updates for pipeline activity and approval requests to post to the chat tool?

A.

Create an Amazon CloudWatch Logs subscription that filters on CodePipeline Pipeline Execution State Change. Publish subscription events to an Amazon Simple Notification Service (Amazon SNS) topic. Subscribe the chat webhook URL to the SNS topic, and complete the subscription validation.

B.

Create an AWS Lambda function that is invoked by AWS CloudTrail events. When a CodePipeline Pipeline Execution State Change event is detected, send the event details to the chat webhook URL.

C.

Create an Amazon EventBridge rule that filters on CodePipeline Pipeline Execution State Change. Publish the events to an Amazon Simple Notification Service (Amazon SNS) topic. Create an AWS Lambda function that sends event details to the chat webhook URL. Subscribe the function to the SNS topic.

D.

Modify the pipeline code to send the event details to the chat webhook URL at the end of each stage. Parameterize the URL so that each pipeline can send to a different URL based on the pipeline environment.