DOP-C02 Exam Dumps : AWS Certified DevOps Engineer - Professional

Create an AWS CodePipelme configuration and set up a post-commit hook to trigger the pipeline after tests have passed Use AWS CodeDeploy and create a Canary deployment configuration that specifies the percentage of traffic and interval

Create an AWS CodeBuild configuration that triggers when the test code is pushed Use AWS CloudFormation to trigger an AWS CodePipelme configuration that deploys the new Lambda versions and specifies the traffic shift percentage and interval

Create an AWS CodePipelme configuration and set up the source code step to trigger when code is pushed. Set up the build step to use AWS CodeBuild to run the tests Set up an AWS CodeDeploy configuration to deploy, then select the CodeDeployDefault.LambdaLinearlDPercentEvery3Minut.es Option.

Use the AWS CLI to set up a post-commit hook that uploads the code to an Amazon S3 bucket after tests have passed. Set up an S3 event trigger that runs a Lambda function that deploys the new version. Use an interval in the Lambda function to deploy the code over time at the required percentage

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 scal

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

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.

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.

Change the Auto Scaling configuration to replace the instances when they fail the load balancer ' s health checks.

Change the target group health check HealthChecklntervalSeconds parameter to reduce the interval between health checks.

Change the target group health checks from HTTP to TCP to check if the port where the application is listening is reachable.

Enable the available memory consumption metric within the Amazon CloudWatch dashboard for the entire Auto Scaling group Create an alarm when the memory utilization is high Associate an Amazon SNS topic to the alarm to receive notifications when the alarm goes off

Use the Amazon CloudWatch agent to collect the memory utilization of the EC2 instances in the Auto Scaling group Create an alarm when the memory utilization is high and associate an Amazon SNS topic to receive a notification.