AWS Certified Solutions Architect - Professional Exam SAP-C02 Exam Questions

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Question #1 (Topic: Demo Questions)

A company has an application that uses an on-premises Oracle database. The company is migrating the database to the AWS Cloud. The database contains customer data and stored procedures.

The company needs to migrate the database as quickly as possible with minimum downtime. The solution on AWS must provide high availability and must use managed services for the database.

Which solution will meet these requirements?

Use AWS DMS to replicate data from the on-premises Oracle database to a new Amazon RDS for Oracle database. Transfer the database files to an Amazon S3 bucket. Configure the RDS database to use the S3 bucket as database storage. Set up S3 replication for high availability. Redirect the application to the RDS DB instance.

Create a database backup of the on-premises Oracle database. Upload the backup to an Amazon S3 bucket. Shut down the on-premises Oracle database to avoid any new transactions. Restore the backup to a new Oracle cluster that consists of Amazon EC2 instances across two Availability Zones. Redirect the application to the EC2 instances.

Use AWS DMS to replicate data from the on-premises Oracle database to a new Amazon DynamoDB table. Use DynamoDB Accelerator (DAX) and implement global tables for high availability. Rewrite the stored procedures in AWS Lambda. Run the stored procedures in DAX. After replication, redirect the application to the DAX cluster endpoint.

Use AWS DMS to replicate data from the on-premises Oracle database to a new Amazon Aurora PostgreSQL database. Use AWS SCT to convert the schema and stored procedures. Redirect the application to the Aurora DB cluster.

Correct Answer: D

Explanation:

The requirements emphasize minimum downtime, rapid migration, managed database services, high availability, and support for stored procedures. For Oracle-to-AWS migrations with minimal downtime, AWS DMS can replicate ongoing changes from the source database to the target, which reduces cutover downtime. However, a critical constraint is that the database contains stored procedures. If the company moves to a different engine, it must convert schema objects and procedural code.

Option D is the only option that combines an online replication approach (AWS DMS) with a managed, highly available target database (Amazon Aurora PostgreSQL) and explicitly includes schema and stored procedure conversion with AWS SCT. This aligns with a fast migration approach: SCT prepares the converted schema and stored procedures, while DMS performs ongoing replication of data changes until cutover, minimizing downtime. Aurora PostgreSQL is a managed service and supports high availability through multi-AZ architecture and managed failover capabilities within a Region.

Option A is incorrect because Amazon RDS does not use an S3 bucket ''as database storage'' in the way described. RDS storage is managed by the RDS service, and S3 replication is not the mechanism used to provide database high availability. High availability for RDS is typically achieved through Multi-AZ configurations and/or cluster-based architectures depending on engine. The described storage approach is not a valid managed RDS architecture.

Option B does not meet the managed database requirement because it restores Oracle onto EC2 instances, which is self-managed. It also does not meet minimum downtime because it requires shutting down the on-premises database to avoid new transactions before restoring the backup. This is a longer outage model than an online migration with continuous replication.

Option C is not feasible and would require major redesign. DynamoDB is not a relational database replacement for Oracle stored procedures. DAX is a DynamoDB cache and cannot run stored procedures. The option also incorrectly suggests running stored procedures ''in DAX.'' This does not meet the ''migrate as quickly as possible with minimum downtime'' requirement due to extensive refactoring and redesign.

Therefore, migrating to Aurora PostgreSQL using AWS SCT for schema and stored procedure conversion, and AWS DMS for ongoing replication to minimize downtime, is the best fit.

Question #2 (Topic: Demo Questions)

A company has an internal application running on AWS that is used to track and process shipments in the company's warehouse. Currently, after the system receives an order, it emails the staff the information needed to ship a package. Once the package is shipped, the staff replies to the email and the order is marked as shipped.

The company wants to stop using email in the application and move to a serverless application model.

Which architecture solution meets these requirements?

Use AWS Batch to configure the different tasks required to ship a package. Have AWS Batch trigger an AWS Lambda function that creates and prints a shipping label. Once that label is scanned, as it leaves the warehouse, have another Lambda function move the process to the next step in the AWS Batch job.

When a new order is created, store the order information in Amazon SQS. Have AWS Lambda check the queue every 5 minutes and process any needed work. When an order needs to be shipped, have Lambda print the label in the warehouse. Once the label has been scanned, as it leaves the warehouse, have an Amazon EC2 instance update Amazon SQS.

Update the application to store new order information in Amazon DynamoDB. When a new order is created, trigger an AWS Step Functions workflow, mark the orders as 'in progress,' and print a package label to the warehouse. Once the label has been scanned and fulfilled, the application will trigger an AWS Lambda function that will mark the order as shipped and complete the workflow.

Store new order information in Amazon EFS. Have instances pull the new information from the NFS and send that information to printers in the warehouse. Once the label has been scanned, as it leaves the warehouse, have Amazon API Gateway call the instances to remove the order information from Amazon EFS.

Correct Answer: C

Question #3 (Topic: Demo Questions)

A company has deployed production workloads on Amazon EC2 On-Demand Instances and Amazon RDS for PostgreSQL DB instances in multiple environments. The company has the AWS Business Support plan. A solutions architect must optimize the cost of the workloads without negatively affecting the availability or compute capacity of the workloads. Which solution will meet these requirements?

Use AWS Cost and Usage Reports to analyze the most expensive instances and usage patterns. Use AWS Lambda to terminate underutilized instances. Purchase Compute Savings Plans for instances for highly utilized workloads.

Use AWS Budgets to track spending for each environment. Configure AWS Trusted Advisor cost optimization checks to rightsize instances. Create billing alerts in Amazon CloudWatch. Terminate underutilized instances. Purchase Reserved Instances for highly utilized workloads.

Opt in to AWS Compute Optimizer. Use Compute Optimizer and AWS Trusted Advisor to identify underutilized instances. Implement recommendations from Compute Optimizer, modify instance types, rightsize instances, and apply Auto Scaling groups. Purchase a Compute Savings Plan.

Use AWS Cost Explorer recommendations to rightsize underutilized instances. Create billing alerts in Amazon CloudWatch. Replace the EC2 On-Demand Instances with Spot Instances for underutilized instances. Stop any instances that are not in use.

Correct Answer: C

Explanation:

Comprehensive and Detailed

Option C is the most comprehensive and aligns with AWS best practices for cost optimization without compromising availability or performance:

AWS Compute Optimizer provides recommendations to rightsize EC2 instances, EBS volumes, and Lambda functions based on utilization metrics. By opting in, the company can receive tailored suggestions for optimizing resource configurations.

AWS Trusted Advisor offers cost optimization checks, including identifying idle or underutilized resources, which can be rightsized or terminated to reduce costs.

Implementing recommendations from Compute Optimizer and Trusted Advisor ensures that resources are appropriately sized, leading to cost savings without affecting performance.

Auto Scaling groups help maintain application availability and allow automatic scaling of EC2 instances based on demand, ensuring that compute capacity aligns with workload requirements.

Compute Savings Plans provide flexible pricing for EC2, AWS Lambda, and AWS Fargate usage, offering significant savings over On-Demand pricing in exchange for a commitment to a consistent amount of usage.

This approach ensures cost optimization while maintaining the necessary compute capacity and availability for production workloads.

AWS Compute Optimizer: Provides recommendations for optimizing AWS resources based on utilization metrics.

AWS Trusted Advisor: Offers real-time guidance to help provision resources following AWS best practices.

AWS Auto Scaling: Automatically adjusts capacity to maintain steady, predictable performance at the lowest possible cost.

AWS Savings Plans: Flexible pricing model offering lower prices compared to On-Demand pricing, in exchange for a commitment to a consistent amount of usage.

Question #4 (Topic: Demo Questions)

A company plans to refactor a monolithic application into a modern application designed deployed or AWS. The CLCD pipeline needs to be upgraded to support the modem design for the application with the following requirements

* It should allow changes to be released several times every hour.

* It should be able to roll back the changes as quickly as possible.

Which design will meet these requirements?

Deploy a Cl-CD pipeline that incorporates AMIs to contain the application and their configurations Deploy the application by replacing Amazon EC2 instances

Specify AWS Elastic Beanstak to sage in a secondary environment as the deployment target for the CI/CD pipeline of the application. To deploy swap the staging and production environment URLs.

Use AWS Systems Manager to re-provision the infrastructure for each deployment Update the Amazon EC2 user data to pull the latest code art-fact from Amazon S3 and use Amazon Route 53 weighted routing to point to the new environment

Roll out the application updates as pan of an Auto Scaling event using prebuilt AMIs. Use new versions of the AMIs to add instances, and phase out all instances that use the previous AMI version with the configured termination policy during a deployment event.

Correct Answer: B

Explanation:

It is the fastest when it comes to rollback and deploying changes every hour

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