https://docs.aws.amazon.com/codepipeline/latest/userguide/reference-pipeline-structure.html AWS doc: "To specify parallel actions, use the same integer for each action you want to run in parallel. For example, if you want three actions to run in sequence in a stage, you would give the first action the runOrder value of 1, the second action the runOrder value of 2, and the third the runOrder value of 3. However, if you want the second and third actions to run in parallel, you would give the first action the runOrder value of 1 and both the second and third actions the runOrder value of 2."

The company's primary goals are to produce daily builds, publish artifacts to an Amazon S3-hosted website, and do so with the least operational overhead. Because the source repository is public and builds are produced on a fixed daily schedule, there is no requirement for complex multi-stage orchestration or manual pipeline invocations.
Option B provides the most streamlined and AWS-recommended solution. By using AWS CodeBuild directly with the public repository as the source, the company eliminates the need to manage an AWS CodePipeline altogether. CodeBuild can natively compile the project and publish build artifacts directly to an Amazon S3 bucket through its artifacts configuration. This minimizes service dependencies and operational complexity.
Using an Amazon EventBridge scheduled rule to trigger the CodeBuild project daily ensures builds occur automatically without manual intervention. Enabling artifact encryption is the AWS best practice, even for public artifacts, because encryption at rest does not prevent public read access when bucket policies allow it.
Option A relies on webhooks and push-based triggers, which do not meet the "build every day" requirement and introduce unnecessary coupling to repository activity. Options C and D retain CodePipeline, which adds extra configuration and maintenance overhead without providing additional value for this simple build-and- publish workflow.
Therefore, Option B meets all requirements with the least operational effort while following AWS- recommended CI/CD design principles.

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.

The core problem described is deployment inconsistency and lack of reliability caused by using AWS Systems Manager Run Command for application deployment. Run Command executes ad hoc commands and does not provide deployment orchestration, version tracking, lifecycle hooks, or health-based traffic control, which commonly leads to drift between EC2 instances.
The most reliable AWS-native solution is to adopt AWS CodePipeline combined with AWS CodeDeploy.
Option B introduces a structured CI/CD pipeline with a clear build stage followed by a test stage, ensuring that only tested artifacts progress to deployment. Sequential build and test stages are preferred for reliability and deterministic behavior, especially when test results must gate deployments.
Option C is essential because AWS CodeDeploy is the service specifically designed to deploy application revisions consistently across EC2 fleets. By creating a CodeDeploy application and deployment group and integrating it with the ALB, deployments gain support for lifecycle events, health checks, instance synchronization, and automatic rollback. This ensures that all EC2 instances receive the same application version and that traffic is managed safely during deployments.
Option A introduces unnecessary parallelism that does not address the core issue. Option D adds excessive complexity with Lambda orchestration. Option E incorrectly replaces CodeArtifact with S3 without addressing deployment reliability.
Therefore, combining CodePipeline (B) with CodeDeploy and ALB integration (C) provides consistent, repeatable, and reliable deployments aligned with AWS best practices.