AWS Certified DevOps Engineer - Professional

The best approach for gathering metrics with minimal complexity is to modify the Lambda function to log the API operation name, response code, and version number to Amazon CloudWatch Logs. Then, configure a CloudWatch Logs metric filter to increment a metric for each API operation. By specifying response code and application version as dimensions, this method efficiently captures the necessary metrics and leverages existing AWS services directly, making it a simple and effective solution for the given requirements.

To reduce the latency of the Lambda function at all times of the day, the best solution is configuring provisioned concurrency on the Lambda function along with configuring AWS Application Auto Scaling. Provisioned concurrency ensures that a predetermined number of Lambda function instances are always initialized and ready to respond, thereby mitigating cold start delays. Implementing auto-scaling allows the function to dynamically adjust the number of provisioned concurrent instances based on the application's varying load throughout the day, thus efficiently handling traffic spikes and minimizing costs during low-traffic periods.

To address the requirement of dynamically changing the log level configuration based on the deployment group with minimal management overhead, the most effective approach is to use the CodeDeploy environment variable DEPLOYMENT_GROUP_NAME. This variable can be used by a script to identify the deployment group the instance belongs to and adjust the log level settings accordingly. By referencing this script as part of the BeforeInstall lifecycle hook in the appspec.yml file, it ensures the settings are configured before the application files are installed, maintaining a single script version across all deployment groups.

To ensure that all EBS volumes always have the Backup_Frequency tag, the best solution is to use AWS CloudTrail in combination with Amazon EventBridge to react to specific EBS volume events. The solution should be able to handle both the creation and modification of EBS volumes to apply the Backup_Frequency tag correctly. This can be achieved by creating an EventBridge rule that reacts to EBS CreateVolume events or EBS ModifyVolume events. Then, a custom AWS Systems Manager Automation runbook can be configured to apply the Backup_Frequency tag with a value of weekly and specified as the target of the rule. This approach ensures that the tag is applied immediately upon the creation or modification of any EBS volume, meeting the requirement for continuous tagging compliance.

The best approach to keep the Aurora cluster available with minimal interruption during a maintenance window is to add a reader instance to the Aurora cluster and update the application to use the appropriate endpoints: the cluster endpoint for write operations and the reader endpoint for read operations. This configuration allows read operations to be offloaded to the reader instance, thereby reducing the load on the primary instance and ensuring that reads can continue even if the primary instance is undergoing maintenance. The Multi-AZ option on Amazon Aurora needs to be set at the time of cluster creation, not afterward, which makes it not applicable in this scenario. Therefore, the correct solution is to add a reader instance for increased availability and load balancing during maintenance.