A team will deploy an Amazon Aurora MySQL cluster for a demo environment whose data must be reset every day. Which approach provides the greatest operational efficiency to restore the database to a prior state daily?
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Correct answer: Enable the DB cluster Backtrack feature when creating the cluster, set a target backtrack window (for example, 48 hours), and schedule a daily EventBridge-triggered Lambda to perform a backtrack operation..
Why this is the answer
The Backtrack feature for Amazon Aurora MySQL is designed for quickly rewinding a DB cluster to a previous point in time without creating a new cluster or restoring from a snapshot, making it highly efficient for daily resets. Scheduling an EventBridge-triggered Lambda to perform this operation automates the process. Incorrect options: Taking and restoring manual snapshots daily is less efficient as it involves creating a new cluster each time, which takes longer and incurs more overhead than backtracking. Exporting snapshots to S3 and restoring from there adds an unnecessary step and complexity, making it less efficient than native Aurora features. Using point-in-time restore (PITR) also creates a new cluster, similar to snapshot restores, which is less efficient than Backtrack for frequent resets of the same cluster.
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