DP-300 Practice Question: Plan and configure a high availability and disaster recovery environment
Your company has an Azure SQL Database that uses active geo-replication to a secondary region. The primary database is hit by a logical corruption error. You need to restore the database to a point before the corruption occurred with minimal data loss. What should you do?
⚠ Common exam trap
DP-300 often tests the confusion between using geo-replication for disaster recovery versus point-in-time restore for logical corruption, tricking candidates into choosing failover options.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Restore the primary database to a point in time before the corruption using automated backups.
Logical corruption requires point-in-time restore from automated backups to a time before the corruption occurred. Active geo-replication replicates the corruption to the secondary, so it cannot be used to recover. Restoring the primary database to a point in time is the correct approach to minimize data loss.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Fail over to the secondary region and then fail back.
Why it's wrong here
Failover promotes the replica, which already contains the corrupted data, so it cannot rewind to a pre-corruption point. It is tempting because failover is the standard geo-replication recovery action, and it suits regional outages, whereas logical corruption requires point-in-time restore instead.
- ✗
Use the geo-replicated secondary to recover the data.
Why it's wrong here
The secondary holds a near-identical replica, so it already contains the corrupted rows; reading it cannot recover pre-corruption state. It is tempting because geo-replication enables regional failover, which suits datacentre outages, but logical corruption demands point-in-time restore to a timestamp before the error.
- ✗
Seeding the secondary from a backup of the primary.
Why it's wrong here
Seeding copies schema and data to a replica; it cannot rewind the primary to a pre-corruption timestamp. It is tempting because seeding rebuilds a secondary after failover, which suits re-establishing geo-replication, not recovering from logical corruption, where point-in-time restore is required.
- ✓
Restore the primary database to a point in time before the corruption using automated backups.
Why this is correct
Automated backups retain point-in-time restore capability, so restoring the primary to a timestamp before the logical corruption removes the bad data. Geo-replication copies corruption to the secondary, so it cannot help; point-in-time restore directly satisfies the minimal-data-loss constraint.
Go deeper
Related to this question
Learn chapter
Securing Data at Rest and in Transit
Key term
Azure SQL Performance Tuning
Azure SQL Performance Tuning is the process of optimizing the speed and efficiency of queries and database operations in Microsoft Azure SQL Database or SQL Managed Instance to reduce latency and improve throughput.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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