
Amazon
 DOP-C02
 180 Minutes
207
 AWS Certified DevOps Engineer - Professional Exam
The Amazon AWS Certified DevOps Engineer – Professional DOP-C02 certification is one of the most respected cloud certifications available today. It is designed for professionals who manage, automate, and operate AWS environments.
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A: Add an AppSpec file with the CodeDeployDefault.ECSLineaMOPercentEverylMinutes deployment configuration.
B: Add the AWS::CodeDeployBlueGreen transform and the AWS::CodeDeploy::BlueGreen hook parameter with the CodeDeployDefault.ECSLinear10PercentEvery1 Minutes deployment configuration.
C: Add an AppSpec file with the ECSCanary10Percent5Minutes deployment configuration.
D: Add the AWS::CodeDeployBlueGroen transform and the AWS::CodeDeploy::BlueGreen hook parameter with the ECSCanary10Percent5Minutes deployment configuration. Step 1: Using AWS CloudFormation with ECS Blue/Green Deployments The requirement is to implement an ECS blue/green deployment where traffic is shifted gradually. AWS CodeDeploy supports such blue/green deployments with predefined configurations, like ECSLinear10PercentEvery1Minute, which shifts 10% of traffic every minute. Action: Use the AWS::CodeDeployBlueGreen transform and the appropriate hooks in the CloudFormation template. The ECSLinear10PercentEvery1Minute deployment configuration meets the requirement of shifting 10% of traffic every minute. Why: The transform and hook parameters in Cloud Formation are essential for configuring the blue/green deployment with the desired traffic-shifting behavior.
A: Create an Amazon CloudWatch Logs log group. Configure the appropriate AWS WAF web ACL to send log messages to the log group. Instruct the operations team to create CloudWatch metric filters.
B: Create an Amazon OpenSearch Service cluster and appropriate indexes. Configure an Amazon Kinesis Data Firehose delivery stream to stream log data to the indexes. Use OpenSearch Dashboards to create filters and widgets.
C: Create an Amazon S3 bucket for the log output. Configure AWS WAF to send log outputs to the S3 bucket. Instruct the operations team to create AWS Lambda functions that detect each desired log message pattern. Configure the Lambda functions to publish to an Amazon Simple Notification Service (Amazon SNS) topic.
D: Create an Amazon S3 bucket for the log output. Configure AWS WAF to send log outputs to the S3 bucket. Use Amazon Athena to create an external table definition that fits the log message pattern. Instruct the operations team to write SOL queries and to create Amazon CloudWatch metric filters for the Athena queries. Step 1: Sending AWS WAF Logs to CloudWatch Logs AWS WAF allows you to log requests that are evaluated against your web ACLs. These logs can be sent directly to CloudWatch Logs, which enables real-time monitoring and analysis. Action: Configure the AWS WAF web ACL to send log messages to a CloudWatch Logs log group. Why: This allows the operations team to view the logs in real time and analyze patterns using Cloud Watch metric filters.
A: Modify the build stage. Add a test action that has a runOrder value of 1. Use AWS CodeDeploy as the action provider to run unit tests.
B: Modify the build stage Add a test action that has a runOrder value of 2 Use AWS CodeBuild as the action provider to run unit tests
C: Modify the deploy stage Add a test action that has a runOrder value of 1 Use AWS CodeDeploy as the action provider to run unit tests
D: Modify the deploy stage Add a test action that has a runOrder value of 2 Use AWS CodeBuild as the action provider to run unit tests
A: Create an Amazon EventBridge rule that reacts to RDS storage autoscaling events from RDS events. Create an AWS Lambda function that publishes a CloudWatch custom metric. Configure the EventBridge rule to invoke the Lambda function. Visualize the custom metric by using the CloudWatch dashboard.
B: Create a trail by using AWS CloudTrail with management events configured. Configure the trail to send the management events to Amazon CloudWatch Logs. Create a metric filter in CloudWatch Logs to match the RDS storage autoscaling events. Visualize the metric filter by using the CloudWatch dashboard.
C: Create an Amazon EventBridge rule that reacts to RDS storage autoscaling events (rom the RDS events. Create a CloudWatch alarm. Configure the EventBridge rule to change the status of the CloudWatch alarm. Visualize the alarm status by using the CloudWatch dashboard.
D: Create a trail by using AWS CloudTrail with data events configured. Configure the trail to send the data events to Amazon CloudWatch Logs. Create a metric filter in CloudWatch Logs to match the RDS storage autoscaling events. Visualize the metric filter by using the CloudWatch dashboard. Step 1: Reacting to RDS Storage Autoscaling Events Using Amazon EventBridge Amazon RDS emits events when storage autoscaling occurs. To visualize these events in a CloudWatch dashboard, you can create an EventBridge rule that listens for these specific autoscaling events. Action: Create an EventBridge rule that reacts to RDS storage autoscaling events from the RDS event stream. Why: EventBridge allows you to listen to RDS events and route them to specific AWS services for processing. Step 2: Creating a Custom CloudWatch Metric via Lambda Once the EventBridge rule detects a storage autoscaling event, you can use a Lambda function to publish a custom metric to CloudWatch. This metric can then be visualized in a CloudWatch dashboard. Action: Use a Lambda function to publish custom metrics to CloudWatch based on the RDS storage autoscaling events. Why: Custom metrics allow you to track specific events like autoscaling and visualize them easily on a CloudWatch dashboard.




