Amazon DBS-C01 Exam

Correct Answer: A

Explanation from Amazon documents:

Performance Insights is a feature of Amazon Aurora MySQL that helps you quickly assess the load on your database and determine when and where to take action. Performance Insights displays a dashboard that shows the database load in terms of average active sessions (AAS), which is the average number of sessions that are actively running SQL statements at any given time. Performance Insights also shows the top SQL statements, waits, hosts, and users that are contributing to the database load.

Amazon DevOps Guru is a fully managed service that helps you improve the operational performance and availability of your applications by detecting operational issues and recommending specific actions for remediation. Amazon DevOps Guru applies machine learning to automatically analyze data such as application metrics, logs, events, and traces for behaviors that deviate from normal operating patterns. Amazon DevOps Guru supports Amazon RDS as a resource type and can monitor the performance and availability of your RDS databases.

By turning on Performance Insights for the Aurora MySQL database and configuring and turning on Amazon DevOps Guru for RDS, the database specialist can automatically detect and diagnose database performance issues and resolve bottlenecks faster. This solution will allow the database specialist to monitor the database load and identify the root causes of performance problems using Performance Insights, and receive actionable insights and recommendations from Amazon DevOps Guru to improve the operational performance and availability of the database.

Therefore, option A is the correct solution to meet the requirements. Option B is not sufficient because creating a CPU usage alarm will only notify the database specialist when the CPU utilization is high, but it will not help diagnose or resolve the database performance issues. Option C is not efficient because using the Amazon RDS query editor to get the process ID of the query that is causing the database to lock and running a command to end the process will require manual intervention and may cause data loss or inconsistency. Option D is not efficient because using the SELECT INTO OUTFILE S3 statement to query data from the database and saving the data directly to an Amazon S3 bucket will incur additional time and cost, and using Amazon Athena to analyze the files for long-running queries will not help prevent or resolve locking contention on the database.

According to the Amazon Redshift documentation1, you can enable database encryption for your clusters to help protect data at rest. You can use either AWS Key Management Service (AWS KMS) or a hardware security module (HSM) to manage the top-level encryption keys in this hierarchy. The process that Amazon Redshift uses for encryption differs depending on how you manage keys.

To copy encrypted snapshots across Regions, you need to create a snapshot copy grant in the destination Region and specify a CMK in that Region. You also need to configure cross-Region snapshots in the source Region and provide the destination Region, the snapshot copy grant, and retention periods for the snapshots. This way, you can automate the process of backing up the cluster data in compliance with the corporate policies.

General Purpose SSD storage is a cost-effective storage option that is ideal for a broad range of workloads running on medium-sized DB instances1.General Purpose storage is best suited for development and testing environments1.Since the database is primarily used for nightly batch processing, it does not require high I/O performance or low latency that Provisioned IOPS storage offers12.Magnetic storage and Throughput Optimized HDD are not recommended for new storage needs, and they have lower storage limits than General Purpose SSD and Provisioned IOPS SSD1. Therefore, General Purpose SSD storage meets the requirements most cost-effectively.