AWS Certified CloudOps Engineer Associate SOA-C03 Practice Question
A company runs a multi-AZ Amazon Aurora MySQL DB cluster for order data. Automated backups are kept 7 days, and Aurora Backtrack has a 24-hour window. A deployment at 03:15 corrupted tables, discovered at 03:30. Ops must restore the database to its pre-deployment state with a 15-minute RTO and 10-minute RPO, minimizing extra cost and effort. What should they do?
Create an on-demand snapshot, restore it to a new cluster from 03:14, and switch the application to the new writer endpoint.
Export the latest automated backup to Amazon S3, load the data into a new cluster, and then promote the cluster to production.
Use Aurora Backtrack to rewind the existing cluster to 03:14 and resume operations.
Perform a point-in-time restore from automated backups to 03:14, create a new cluster, and update application endpoints.
Aurora Backtrack can rewind the entire DB cluster to an exact timestamp within the configured backtrack window without creating a new cluster, so existing endpoints remain unchanged. The rewind typically finishes in seconds or minutes, easily meeting a 15-minute RTO and a 10-minute RPO by choosing 03:14. A point-in-time restore or a snapshot restore spins up a new cluster and requires redirecting traffic, adding cost and exceeding the RTO. Exporting to Amazon S3 and re-importing takes even longer and is costlier.
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AWS Certified CloudOps Engineer Associate SOA-C03
Reliability and Business Continuity
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