Amazon Web Services DOP-C02 Exam With Confidence Using Practice Dumps

The requirement is to automatically apply different baseline CloudFormation templates based on OU placement when new AWS accounts are created, while keeping operational overhead as low as possible. Because the company is already using AWS Organizations and is planning a comprehensive account management strategy, the most AWS-native and efficient solution is AWS Control Tower with Customizations for AWS Control Tower (CfCT) .

CfCT is specifically designed to extend Control Tower’s baseline by allowing administrators to deploy OU-scoped CloudFormation templates automatically. The solution uses a manifest file to map CloudFormation templates to specific OUs, ensuring that each new account receives the correct baseline configuration immediately after provisioning. Templates and configuration are stored in a version-controlled Git repository, providing auditability, change tracking, and rollback capabilities.

Option B adds unnecessary operational complexity by introducing a custom CodePipeline that must be manually triggered and maintained. This duplicates functionality that CfCT already provides natively. Options C and D rely on custom Lambda logic and EventBridge rules, which increase maintenance burden, reduce transparency, and lack built-in OU-aware governance features.

AWS documentation explicitly recommends Customizations for AWS Control Tower for OU-based, scalable, and automated baseline deployments. Therefore, Option A delivers the required functionality with the least operational overhead and aligns with AWS best practices for multi-account governance.

CodeDeploy supports TimeBasedLinear traffic shifting for ECS blue/green deployments. Traffic increments by linearPercentage every linearInterval until 100%. This provides zero-downtime gradual rollout — as per CodeDeploy ECS Blue/Green Traffic Shifting documentation.

The current design colocates the web tier, database, and cache on the same EC2 instances. This causes resource contention and makes it difficult to scale each layer independently. The correct solution is to separate these concerns into independently scalable managed services.

Option D uses an Application Load Balancer (ALB) in front of an Auto Scaling group for the web application. ALB is designed for HTTP/HTTPS traffic, supports path-based and host-based routing, and can spread load evenly across multiple instances and Availability Zones, eliminating the issue where one instance is overloaded.

The database is migrated to Amazon Aurora with Multi-AZ , which provides high availability, automated failover, and managed backups. Aurora offloads database management and ensures consistent performance.

For caching, Option D introduces Amazon ElastiCache for Redis , a managed in-memory cache that is purpose-built for low-latency reads, independent scaling, and high availability through replication and clustering.

Option A and C misuse NLB for HTTP traffic or for Redis exposure and introduce unnecessary complexity. Option B keeps Redis on EC2 (via NLB + ASG in a single AZ), which reduces availability and does not leverage managed caching.

Thus, Option D best separates tiers and improves performance and availability.