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Zorluk: OrtaDatabase Migration and Schema Conversion using DMS and SCT

A company is planning to migrate a self-managed PostgreSQL database hosted on-premises to an Amazon Aurora MySQL-Compatible Edition DB cluster. The migration must convert the schema and support ongoing replication to minimize cutover downtime. The source database is highly active, and the replication task must capture ongoing transactions via change data capture (CDC).

Which two actions must the solutions architect take to support schema conversion and change data capture (CDC) for this database migration? (Select two.)

  1. Use the AWS Schema Conversion Tool (SCT) to convert the PostgreSQL schema, functions, and stored procedures to MySQL-compatible formats, and apply the converted schema to the target Aurora DB cluster.Cevap
  2. Set the wal_level parameter to logical on the source PostgreSQL database to enable the generation of write-ahead logs suitable for AWS DMS replication.Cevap
  3. C
    Enable the Microsoft Change Data Capture (MS-CDC) feature on the source database tables to track transactional changes.
  4. D
    Modify the source database configuration to set the binlog_format parameter to ROW and configure binary log retention.
  5. E
    Deploy an AWS SCT extraction agent on the source database host to stream write-ahead log (WAL) records directly to the AWS DMS replication instance.

Cevap

The solutions architect must use the AWS Schema Conversion Tool (SCT) to convert the database schema to MySQL-compatible formats and apply it to the target, and set the wal_level parameter to logical on the source PostgreSQL database.
The correct actions are to use the AWS Schema Conversion Tool (SCT) to convert the PostgreSQL schema to MySQL-compatible formats, and to configure the wal_level parameter to logical on the source PostgreSQL database. Since the migration is heterogeneous (PostgreSQL to MySQL), SCT is necessary to convert schema objects and database code. For CDC, AWS DMS uses logical replication on PostgreSQL, which requires the write-ahead log level (wal_level) to be set to logical to generate the replication stream.

Adım Adım Çözüm

1
Analyze the migration type (source and target engines).
The migration is heterogeneous (PostgreSQL on-premises to Amazon Aurora MySQL), meaning the database schemas are incompatible and require schema conversion.
Identifying the compatibility of the source and target engines determines if AWS SCT is required.
2
Select the appropriate tool for schema conversion.
AWS Schema Conversion Tool (SCT) is selected to convert PostgreSQL schema, functions, and stored procedures to MySQL-compatible SQL scripts, which are then applied to the target Aurora DB cluster.
Heterogeneous schema conversion cannot be performed directly by AWS DMS and requires AWS SCT.
3
Configure the source PostgreSQL database for Change Data Capture (CDC).
Set the wal_level parameter to logical in the postgresql.conf file and restart the instance.
AWS DMS uses logical replication slots to capture ongoing changes from PostgreSQL, which requires the write-ahead log (WAL) level to be set to logical.

Anahtar Kavram

Heterogeneous database migration using AWS SCT for schema conversion and AWS DMS logical replication (wal_level = logical) for ongoing change data capture (CDC).
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Konular

Database Migration and Schema Conversion using DMS and SCT

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