SAP-C02 Practice Question: Accelerate Workload Migration and Modernization
A company is modernizing a legacy monolithic application by moving it to a microservices architecture on AWS. The application currently uses a relational database with complex joins and stored procedures. The company wants to decouple the database and improve scalability. They plan to use Amazon Aurora and need to minimize the risk of data inconsistencies during the transition. Which strategy should they use to gradually migrate the database while ensuring data consistency?
⚠ Common exam trap
The trap here is assuming that AWS SCT can split a monolithic database into microservices, but it only converts schemas between engines, not decomposes databases.
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 strangler fig pattern with AWS Database Migration Service (DMS) to replicate data between the monolithic database and new microservice databases.
The strangler fig pattern, combined with AWS DMS for continuous replication, allows gradual migration from a monolith to microservices. DMS replicates data changes in near real-time, ensuring consistency between the old and new databases. This approach minimizes risk and allows rollback if needed. Other options either do not support continuous replication or are not designed for database decomposition.
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 AWS Schema Conversion Tool (SCT) to split the monolithic database into microservice databases.
Why it's wrong here
AWS SCT converts database schemas between different database engines, but it does not split a monolithic database into multiple microservice databases. Splitting a database requires careful domain-driven design and data partitioning, which SCT does not perform. SCT is useful for heterogeneous migrations, but not for decomposing a monolith into microservices.
- ✗
Use Amazon Aurora Global Database to replicate data across microservice databases.
Why it's wrong here
Amazon Aurora Global Database is designed for disaster recovery and low-latency global reads, not for splitting a monolithic database into microservice databases. It replicates an entire Aurora cluster to other regions. It does not provide the ability to selectively replicate subsets of data to different databases, which is needed for microservices decomposition.
- ✗
Use AWS Glue to extract, transform, and load data from the monolithic database into microservice databases.
Why it's wrong here
AWS Glue is a serverless ETL service, but it is batch-oriented and not designed for continuous replication with low latency. Using Glue would introduce delays and potential inconsistencies. It is not suitable for keeping microservice databases in sync with a monolithic database during a gradual migration. DMS with CDC is more appropriate for continuous replication.
- ✓
Use the strangler fig pattern with AWS Database Migration Service (DMS) to replicate data between the monolithic database and new microservice databases.
Why this is correct
The strangler fig pattern involves gradually replacing parts of the monolith with microservices. AWS DMS can replicate data from the monolithic database to new microservice-specific databases, ensuring consistency during the transition. This allows incremental migration, reducing risk. DMS supports ongoing replication, so both systems can operate in parallel until the monolith is fully replaced.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
This SAP-C02 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the SAP-C02 exam.