SAA-C03 Exam Dumps - AWS Certified Solutions Architect - Associate (SAA-C03)

Amazon Aurora PostgreSQL with Babelfish allows SQL Server applications to run directly on Aurora PostgreSQL with minimal code changes. Babelfish adds a SQL Server-compatible endpoint, significantly lowering costs compared to running licensed SQL Server instances on RDS or EC2.

AWS Documentation Extract:

“Babelfish for Aurora PostgreSQL enables Aurora to understand T-SQL and SQL Server wire protocol, allowing you to run SQL Server applications on Amazon Aurora PostgreSQL with lower costs.”

(Source: Babelfish for Aurora PostgreSQL documentation)

A, D: SQL Server on EC2 or RDS incurs high Microsoft licensing costs.

C: Plain PostgreSQL would require more code refactoring than Babelfish.

Amazon RDS Proxy is a fully managed database proxy for RDS that makes applications more scalable, more resilient to database failures, and more secure. RDS Proxy pools and shares database connections, allowing applications to open and close connections as needed without overwhelming the database. This is the recommended solution when the application cannot be modified to use connection pooling itself.

AWS Documentation Extract:

"Amazon RDS Proxy helps manage database connections to improve application scalability and performance. It pools connections and shares them among application clients, which can mitigate issues caused by opening and closing many database connections."

(Source: Amazon RDS Proxy documentation)

A: Upgrading the instance does not solve connection inefficiency and can be cost-ineffective.

B: Increasing IOPS only helps if storage is a bottleneck, not if connections are the issue.

D: Multi-AZ improves availability, not connection management.

AWS STS issues temporary credentials with automatically expiring permissions based on IAM roles. This eliminates the need to manually manage or deactivate IAM users.

“You can use AWS STS to grant temporary security credentials that automatically expire after a specified duration.”

— Temporary Security Credentials

This is the least operational overhead and follows AWS best practices for short-term access.

AWS Storage Gateway file gateway presents a file interface backed by Amazon S3 and supports NFS. This allows local applications to access data via NFS while also enabling cloud applications to use the data stored in S3 for analytics and processing, fulfilling both hybrid and cloud-native requirements.

Reference Extract:

"AWS Storage Gateway file gateway offers NFS and SMB access to data stored in Amazon S3, supporting hybrid workloads for local and cloud access."

Source: AWS Certified Solutions Architect – Official Study Guide, Hybrid and Storage Gateway section.

Amazon S3 Standard-IA: This storage class is designed for data that is accessed less frequently but requires rapid access when needed. It offers lower storage costs compared to S3 Standard while still providing high availability and durability.

Access Patterns: Since the files are frequently accessed in the first 30 days and rarely accessed afterward, transitioning them to S3 Standard-IA after 30 days aligns with their access patterns and reduces storage costs significantly.

Lifecycle Policy: Implementing a lifecycle policy to transition the files to S3 Standard-IA ensures automatic management of the data lifecycle, moving files to a lower-cost storage class without manual intervention. Deleting the files after 4 years further optimizes costs by removing data that is no longer needed.

Amazon DynamoDB supports both TTL (Time to Live) for automatic deletion and Point-in-Time Recovery (PITR) for backup and restore of table data. It's ideal for frequently updated data with short retention requirements and minimal operational overhead.

TTL attribute ensures expired items are automatically removed.

PITR enables recovery from accidental deletes or application errors.

The requirement combines two key goals: reduce post-migration database administration/maintenance cost and minimize application rewrites for an existing Microsoft SQL Server application that relies heavily on T-SQL and stored procedures. Amazon Aurora PostgreSQL-Compatible with Babelfish is designed for this exact migration pattern: it helps applications written for SQL Server to run with reduced code changes by providing compatibility for commonly used SQL Server semantics, including T-SQL constructs, procedural logic, and SQL Server-style connectivity patterns (depending on feature usage). Aurora itself is a managed database service that reduces operational overhead compared to self-managed databases by offloading tasks such as provisioning, patching (within service capabilities), backups, and high availability patterns.

Option C (RDS for SQL Server) would indeed minimize rewrites because it keeps the engine the same, but it typically does not optimize operating costs as effectively as migrating off commercial SQL Server licensing/edition costs; it also keeps you on the same engine family, which often carries higher license implications and may not meet the “minimize operating costs” intent as strongly as moving to Aurora PostgreSQL with Babelfish. Option B is not suitable because Redshift Spectrum is for analytics over data in S3, not for running an OLTP ecommerce database with stored procedures. Option D is also a mismatch: EMR is for big data processing frameworks, not a relational OLTP database replacement for SQL Server.

Therefore, A best balances lower ongoing operational cost with reduced refactoring effort by using Aurora’s managed capabilities while leveraging Babelfish to ease SQL Server-to-PostgreSQL migration friction.