Amazon Web Services Updated SAP-C02 Exam Questions and Answers by elowen

The best solution is to create a tag policy that contains the allowed project tag values in the organization’s management account and create an SCP that denies the cloudformation:CreateStack API operation unless a project tag is added. A tag policy is a type of policy that can help standardize tags across resources in the organization’s accounts. A tag policy can specify the allowed tag keys, values, and case treatment for compliance. A service control policy (SCP) is a type of policy that can restrict the actions that users and roles can perform in the organization’s accounts. An SCP can deny access to specific API operations unless certain conditions are met, such as having a specific tag. By creating a tag policy in the management account and attaching it to each OU, the organization can enforce consistent tagging across all accounts. By creating an SCP that denies the cloudformation:CreateStack API operation unless a project tag is added, the organization can prevent users from creating new resources without proper tagging. This solution will meet the requirements with the least effort, as it does not involve creating additional resources or modifying existing ones. References: Tag policies - AWS Organizations, Service control policies - AWS Organizations, AWS CloudFormation User Guide

C is correct because it converts the single–Availability Zone, single-EC2-instance ECS design into a managed, multi-AZ, self-healing architecture with minimal day-to-day operations. The current design has multiple single points of failure: one EC2 instance for ECS capacity and one Availability Zone for all components. Moving the ECS service to AWS Fargate removes the need to manage EC2 instances (capacity provisioning, patching, and scaling of the container instances) and allows the service to run tasks across multiple Availability Zones for higher availability. On the database side, modifying Aurora PostgreSQL to a Multi-AZ DB cluster (by adding a replica in another AZ) increases availability and supports faster recovery from an AZ failure with AWS-managed failover.

Why the other options are less suitable:

A: Making Aurora Multi-AZ improves database availability, but it does not address the compute layer’s biggest issue: ECS is on a single EC2 instance in one AZ with no auto scaling. RDS Proxy can help with connection management, but it does not fix the application’s single-AZ ECS single-instance availability risk.

B: Cross-Region read replicas and manual failover scripts increase operational burden. Also, it keeps ECS on EC2 (still requires instance management) and introduces a manual failover process, which is the opposite of “least operational overhead.”

D: Multi-Region active-active plus Aurora global database can deliver very high availability, but it adds significant complexity (multi-Region deployment, routing strategy, global database considerations, operational procedures). That is higher operational overhead than a straightforward multi-AZ design using managed services.

The best combination is A, D, and E because it replaces self-managed components with managed AWS services. AWS IoT Core is purpose-built for MQTT-based device communication, and IoT rules can invoke Lambda functions when messages arrive, allowing serverless processing of device data. Amazon DocumentDB is compatible with MongoDB workloads and removes the operational burden of running MongoDB clusters on EC2. For report generation, AWS Step Functions can orchestrate Lambda tasks, and the reports can be written to Amazon S3 and served publicly through CloudFront. The job duration of 120–600 seconds fits within Lambda’s 15-minute maximum invocation timeout. EKS and EC2-based MongoDB would increase operational overhead, while having Lambda poll IoT devices directly is a poor design compared with device publishing through AWS IoT Core. (AWS Documentation)

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