AWS Certified Solutions Architect - Associate
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A company runs an application on AWS. The application receives inconsistent amounts of usage. The application uses AWS Direct Connect to connect to an on-premises MySQL-compatible database. The on-premises database consistently uses a minimum of 2 GiB of memory.
The company wants to migrate the on-premises database to a managed AWS service. The company wants to use auto scaling capabilities to manage unexpected workload increases.
Which solution will meet these requirements with the LEAST administrative overhead?
Other
Community
UAnonymous
A
Provision an Amazon DynamoDB database with default read and write capacity settings.
B
Provision an Amazon Aurora database with a minimum capacity of 1 Aurora capacity unit (ACU).
C
Provision an Amazon Aurora Serverless v2 database with a minimum capacity of 1 Aurora capacity unit (ACU).
D
Provision an Amazon RDS for MySQL database with 2 GiB of memory.
Explanation:
Explanation
Correct Answer: C - Provision an Amazon Aurora Serverless v2 database with a minimum capacity of 1 Aurora capacity unit (ACU).
Why this is correct:
-
Auto-scaling capabilities: Aurora Serverless v2 automatically scales database capacity up and down based on actual workload demands. It can scale in fine-grained increments to handle unexpected workload increases without manual intervention.
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MySQL-compatible: Aurora is fully MySQL-compatible, meeting the requirement for migrating from an on-premises MySQL database.
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Minimum capacity setting: Setting a minimum of 1 ACU ensures the database can handle the baseline workload while being cost-effective.
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Least administrative overhead: Aurora Serverless v2 is a fully managed service that automatically handles scaling, patching, backups, and failover, requiring minimal administrative effort.
Why other options are incorrect:
A. Amazon DynamoDB:
- DynamoDB is a NoSQL database, not MySQL-compatible
- While it has auto-scaling capabilities, it doesn't meet the MySQL compatibility requirement
- Requires different application code changes
B. Standard Amazon Aurora:
- Standard Aurora requires manual scaling of instance sizes
- Doesn't provide automatic scaling capabilities without manual intervention
- Requires more administrative overhead for scaling operations
D. Amazon RDS for MySQL:
- RDS for MySQL doesn't have built-in auto-scaling for compute capacity
- Scaling requires manual intervention to change instance types
- Higher administrative overhead for managing scaling events
Key AWS Services Comparison:
- Aurora Serverless v2: Auto-scales compute capacity automatically, MySQL-compatible, minimal admin overhead
- Standard Aurora: Manual scaling required, MySQL-compatible
- RDS MySQL: Manual scaling required, MySQL-compatible
- DynamoDB: Auto-scaling available, but NoSQL (not MySQL-compatible)
Additional Considerations:
- The 2 GiB memory requirement from the on-premises database is addressed by the minimum capacity setting
- Aurora Serverless v2 can scale from 0.5 ACU to 128 ACU automatically
- Direct Connect connectivity can be maintained with Aurora Serverless v2
- Cost optimization is achieved by paying only for the capacity used
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