To minimize backup size for large files with frequent small changes stored to a cloud repository, which backup method is most effective?

To minimize backup size for large files with frequent small changes stored to a cloud repository, which backup method is most effective?

• A. Local snapshots
• B. Differential backups
• C. File-based replication
• D. Change block tracking

Answer: (B)

Differential backups focus on capturing only what has changed since the last full backup. When you’re dealing with large files that tend to be edited in small parts, this means the backup size each run stays relatively small because you’re not copying the entire file again—just the new or altered data since the last full backup. Because you keep one full backup and then run differentials, restoring is straightforward: you pull back the last full backup and then apply the latest differential to bring the data up to date. This strikes a practical balance between storage needs in the cloud and the speed of restores. Local snapshots can be quick but often involve a broader snapshot of the volume, which may not minimize cloud storage as effectively. File-based replication generally copies whole files or relies on file-level changes, which can be inefficient for large files with small internal edits. Change block tracking is a technique used to detect exactly which blocks changed to enable incremental backups, and it can be very space-efficient, but the scenario described targets the backup method that minimizes data transfer while keeping restore simplicity, which differential backups provide.

Differential backups focus on capturing only what has changed since the last full backup. When you’re dealing with large files that tend to be edited in small parts, this means the backup size each run stays relatively small because you’re not copying the entire file again—just the new or altered data since the last full backup. Because you keep one full backup and then run differentials, restoring is straightforward: you pull back the last full backup and then apply the latest differential to bring the data up to date. This strikes a practical balance between storage needs in the cloud and the speed of restores.

Local snapshots can be quick but often involve a broader snapshot of the volume, which may not minimize cloud storage as effectively. File-based replication generally copies whole files or relies on file-level changes, which can be inefficient for large files with small internal edits. Change block tracking is a technique used to detect exactly which blocks changed to enable incremental backups, and it can be very space-efficient, but the scenario described targets the backup method that minimizes data transfer while keeping restore simplicity, which differential backups provide.