AWS Certified DevOps Engineer – Professional Exam (DOP-C02) - AWS

"Note that the metric filter is different from a log insights query, where the experience is interactive and provides immediate search results for the user to investigate. No automatic action can be invoked from an insights query. Metric filters, on the other hand, will generate metric data in the form of a time series. This lets you create alarms that integrate into your ITSM processes, execute AWS Lambda functions, or even create anomaly detection models." https://aws.amazon.com/blogs/mt/quantify-custom-application-metrics-with-amazon-cloudwatch- logs-and-metric-filters/

The following are the steps that the DevOps engineer should take to reduce the latency of the<br />
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Lambda function at all times of the day: Configure provisioned concurrency on the Lambda function. Configure AWS Application Auto Scaling on the Lambda function with provisioned concurrency values set to a minimum of 1 and a maximum of 100. The provisioned concurrency setting ensures that there is always a minimum number of Lambda function instances available to handle requests. The Application Auto Scaling setting will automatically scale the number of Lambda function instances up or down based on the demand for the application. This solution will ensure that the Lambda function is able to handle the increased load during the middle of the day, while also keeping the cold-start latency low.<br />
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The following are the reasons why the other options are not correct:<br />
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Option A is incorrect because it will not reduce the cold-start latency of the Lambda function.<br />
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Option B is incorrect because it will not scale the number of Lambda function instances up or down based on demand.<br />
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Option D is incorrect because it will only configure reserved concurrency on the API Gateway API,<br />
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which will not affect the Lambda function.

The following are the steps that the company can take to change the log level dynamically when the deployment occurs: Create a script that uses the CodeDeploy environment variable DEPLOYMENT_GROUP_NAME to identify which deployment group the instance is part of. Use this information to configure the log level settings. Reference this script as part of the BeforeInstall lifecycle hook in the appspec.yml file. The DEPLOYMENT_GROUP_NAME environment variable is automatically set by CodeDeploy when the deployment is triggered. This means that the script does not need to call the metadata service or the EC2 API to identify the deployment group. This solution is the least complex and requires the least management overhead. It also does not require different script versions for each deployment group.<br />
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The following are the reasons why the other options are not correct:<br />
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Option A is incorrect because it would require tagging the Amazon EC2 instances, which would be a manual and time-consuming process.<br />
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Option C is incorrect because it would require creating a custom environment variable for each environment. This would be a complex and error-prone process.<br />
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Option D is incorrect because it would use the DEPLOYMENT_GROUP_ID environment variable. However, this variable is not automatically set by CodeDeploy, so the script would need to call the metadata service or the EC2 API to get the deployment group ID. This would add complexity and overhead to the solution.

The following are the steps that the DevOps engineer should take to ensure that all EBS volumes always have the Backup_Frequency tag so that the company can perform backups at least weekly unless a different value is specified: Set up AWS Config in the account. Use a managed rule that returns a compliance failure for EC2::Volume resources that do not have a Backup Frequency tag applied. Configure a remediation action that uses a custom AWS Systems Manager Automation runbook to apply the Backup_Frequency tag with a value of weekly. The managed rule AWS::Config::EBSVolumesWithoutBackupTag will return a compliance failure for any EBS volume that does not have the Backup_Frequency tag applied. The remediation action will then use the Systems Manager Automation runbook to apply the Backup_Frequency tag with a value of weekly to the EBS volume.

To meet the requirements, the DevOps engineer should do the following: Turn on the Multi-AZ option on the Aurora cluster.<br />
Update the application to use the Aurora cluster endpoint for write operations.<br />
Update the Aurora cluster's reader endpoint for reads.<br />
Turning on the Multi-AZ option will create a replica of the database in a different Availability Zone. This will ensure that the database remains available even if one of the Availability Zones is unavailable. Updating the application to use the Aurora cluster endpoint for write operations will ensure that all writes are sent to both the primary and replica databases. This will ensure that the data is always consistent. Updating the Aurora cluster's reader endpoint for reads will allow the application to read data from the replica database. This will improve the performance of the application during the maintenance window.