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Difficulty: Very hardDatabase Migration and Schema Conversion using DMS and SCT

A solutions architect is planning the migration of a mission-critical, on-premises Oracle database to an Amazon Aurora PostgreSQL-Compatible Edition DB cluster. The source database contains complex PL/SQL packages, custom functions, and several high-transaction tables, some of which do not have primary keys. To minimize the migration's impact on the source database's CPU utilization during the change data capture (CDC) phase, and to ensure that the application's Oracle-specific database functions are supported on the target database, which combination of actions should the solutions architect take?

  1. A
    Convert the schema using AWS SCT and manually rewrite the PL/SQL packages. Configure the AWS DMS replication task using the Oracle LogMiner method for CDC, and enable supplemental logging for primary keys on all source tables.
  2. Convert the schema using AWS SCT and apply the SCT extension pack to the target Aurora DB cluster. Configure the AWS DMS replication task to use the Binary Reader method for CDC, and enable supplemental logging for all columns on the source Oracle tables that lack primary keys.Answer
  3. C
    Perform an offline migration by taking a cold backup of the Oracle database, converting the schemas with AWS SCT, and using AWS DataSync to copy the database files to an Amazon S3 bucket for import into Aurora PostgreSQL.
  4. D
    Convert the schema using AWS SCT and apply the SCT extension pack to Aurora PostgreSQL. Configure the AWS DMS replication task using the Oracle LogMiner method for CDC, and scale the target Aurora PostgreSQL DB cluster using reader endpoints to offload replication processing.

Answer

Convert the schema using AWS SCT and apply the SCT extension pack to the target Aurora DB cluster. Configure the AWS DMS replication task to use the Binary Reader method for CDC, and enable supplemental logging for all columns on the source Oracle tables that lack primary keys.
The correct answer is correct because applying the AWS SCT extension pack allows the target Aurora PostgreSQL DB cluster to emulate Oracle-specific functions. Implementing the AWS DMS Binary Reader method for CDC allows DMS to read redo logs directly, minimizing resource consumption on the source database. Furthermore, enabling supplemental logging for all columns on the source Oracle tables without primary keys is required so that AWS DMS can uniquely identify rows and correctly apply updates and deletes during replication.

Step-by-Step Solution

1
Use AWS SCT to convert the Oracle database schema and apply the generated SCT extension pack to the target Aurora PostgreSQL DB cluster.
Oracle-specific features and functions are emulated successfully on the PostgreSQL target, maintaining database compatibility without manual rewrites.
Heterogeneous migrations require schema translation and target emulation for database-specific logic.
2
Configure the AWS DMS replication task with the Oracle source endpoint settings to use the Binary Reader method for CDC.
DMS reads redo logs directly from the OS or ASM directory, avoiding SQL-based LogMiner execution.
This minimizes the CPU overhead on the source Oracle database under high-transaction workloads.
3
On the source Oracle database, enable supplemental logging for all columns on tables that do not have primary keys.
Full row image information is placed in the redo logs for updates and deletes on these tables.
AWS DMS logical replication requires the value of all columns to identify target rows when primary keys are absent.

Key Concept

Heterogeneous database migration utilizing AWS SCT extension packs and optimizing AWS DMS CDC performance on Oracle sources by leveraging Binary Reader and supplemental log configuration.
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Topics

Database Migration and Schema Conversion using DMS and SCT

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