SAP-C02 Practice Question: Accelerate Workload Migration and Modernization
A company is migrating a high-volume transactional database from on-premises to Amazon Aurora PostgreSQL. The database uses sequences, triggers, and stored procedures. The company needs to minimize downtime during cutover and ensure data consistency. Which two actions should be taken to meet these requirements? (Choose two.)
⚠ Common exam trap
The trap here is thinking that a native backup and restore can suffice for a heterogeneous migration, ignoring the need for schema conversion and ongoing replication.
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
✓
Use the AWS Schema Conversion Tool (AWS SCT) to convert the database schema and stored procedures.
AWS DMS with CDC provides ongoing replication to keep the target in sync with minimal downtime, while AWS SCT converts the schema and procedural code to Aurora PostgreSQL. Together, they address both data consistency and code compatibility for a heterogeneous migration. The other options either cause downtime, are technically infeasible, or do not handle schema conversion.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Take a full database backup and restore it to Aurora PostgreSQL using native tools.
Why it's wrong here
A full backup and restore requires significant downtime and does not provide ongoing replication. It also does not handle schema conversions for proprietary features like triggers and stored procedures. This approach would result in a longer outage and potential data inconsistencies if changes occur during the migration.
- ✓
Use the AWS Schema Conversion Tool (AWS SCT) to convert the database schema and stored procedures.
Why this is correct
AWS SCT converts the source schema, including sequences, triggers, and stored procedures, to a format compatible with Aurora PostgreSQL. This addresses the code-level incompatibilities that would otherwise require manual rewriting. It is essential for heterogeneous migrations to ensure the target database functions correctly after cutover.
- ✗
Use AWS Snowball Edge to transfer the database files to Amazon S3 and then load them into Aurora.
Why it's wrong here
AWS Snowball Edge is for bulk data transfer, not for ongoing replication or schema conversion. It would require downtime to export and ship the data, and it does not handle changes that occur during transit. This method is unsuitable for minimizing downtime in a transactional database migration with continuous writes.
- ✓
Use AWS Database Migration Service (AWS DMS) with change data capture (CDC) for ongoing replication.
Why this is correct
AWS DMS with CDC replicates ongoing changes from the source database to Aurora PostgreSQL, allowing near-zero downtime cutover. It continuously applies changes until you are ready to switch over, minimizing the need for a lengthy outage. This is a standard approach for minimizing downtime during heterogeneous migrations while keeping data consistent.
- ✗
Configure Aurora PostgreSQL as a read replica of the on-premises database.
Why it's wrong here
Aurora PostgreSQL cannot be configured as a read replica of an on-premises database because replication requires compatible engines and network connectivity. Native replication between different database engines is not supported. This option is technically invalid for a heterogeneous migration from an on-premises database to Aurora.
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Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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