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

Ensure that the EKS cluster ' s VPC subnets do not overlap with the 172.17.0.0/16 CIDR range.

Use kubectl to update the kubeconfig file to use the credentials that created the cluster.

Run the AWSSupport-TroubleshootEKSWorkerNode runbook.

Create an AWS Identity and Access Management (IAM) OpenID Connect (OIDC) provider for the cluster.

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 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 On-Demand 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.

Activate S3 server access logging. Import the access logs into an Amazon Aurora database. Use an Aurora SQL query to analyze the access patterns.

Activate S3 server access logging. Use Amazon Athena to create an external table with the log files. Use Athena to create a SQL query to analyze the access patterns.

Invoke an AWS Lambda function for every S3 object access event. Configure the Lambda function to write the file access information, such as user. S3 bucket, and file key, to an Amazon Aurora database. Use an Aurora SQL query to analyze the access patterns.

Record an Amazon CloudWatch Logs log message for every S3 object access event. Configure a CloudWatch Logs log stream to write the file access information, such as user, S3 bucket, and file key, to an Amazon Kinesis Data Analytics for SQL application. Perform a sliding window analysis.