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DBS-C01 Deployment and Migration Practice Question

A company is migrating a 5 TB PostgreSQL database to Amazon Aurora PostgreSQL. The database has complex stored procedures and triggers. The migration must be completed within a 30-minute downtime window. Which approach would meet the requirement?

⚠ Common exam trap

Candidates often assume a full dump and restore (pg_dump/pg_restore) is the fastest method for large databases, but they overlook the need for ongoing replication to achieve a short downtime window, and they may incorrectly think Aurora read replicas can be created from external PostgreSQL sources.

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 AWS DMS with full load and ongoing replication, then perform a cutover.

AWS DMS with full load and ongoing replication allows you to migrate the 5 TB database with minimal downtime by continuously replicating changes from the source PostgreSQL to the target Aurora PostgreSQL. When you are ready, you perform a cutover, which typically takes only a few minutes, meeting the 30-minute downtime window. The complex stored procedures and triggers are handled because DMS supports ongoing replication for PostgreSQL, capturing DML and DDL changes.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Use Database Migration Service (DMS) with validation only.

    Why it's wrong here

    Validation does not migrate data.

  • Use AWS DMS with full load and ongoing replication, then perform a cutover.

    Why this is correct

    Ongoing replication allows a fast cutover.

  • Use AWS SCT to convert the schema and then use pg_dump/pg_restore.

    Why it's wrong here

    pg_dump/pg_restore for 5 TB will exceed 30 minutes.

  • Set up an Aurora read replica from the source PostgreSQL.

    Why it's wrong here

    Aurora cannot replicate from external PostgreSQL.

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