Use CodePipeline with a Git source to orchestrate the flow, CodeBuild to produce versioned artifacts in S3, and CodeDeploy to EC2 with lifecycle hooks (e.g., BeforeInstall) to run cache-clearing and unpack steps.
This gives end-to-end visibility, rollbacks, and standardized deployments.

AWS CodeDeploy supports automatic rollback capabilities, which allow the deployment to automatically revert to the last known good revision if a failure occurs during the deployment or if health checks fail.
* You can enable automatic rollback on CodeDeploy deployments by configuring rollback settings in the deployment group.
* Automatic rollback triggers can include failed deployments and alarms failing during the deployment lifecycle, which means if the health check fails, CodeDeploy will automatically roll back without manual intervention.
* Lifecycle event hooks (Option A) provide custom scripting capabilities during deployment but do not provide built-in rollback automation.
* CloudFormation (Option B) can deploy and manage infrastructure but does not control CodeDeploy rollback.
* CloudWatch alarms (Option C) can trigger notifications but require manual or additional automation to trigger rollback. Hence, enabling CodeDeploy's automatic rollback settings is the simplest and most reliable method for automatic rollback upon health check failure.
Reference from AWS Official Documentation and Study Guide:
* AWS CodeDeploy Automatic Rollback: " You can configure automatic rollback in AWS CodeDeploy to roll back a deployment if it fails or if specified CloudWatch alarms are triggered. " (AWS CodeDeploy User Guide - Automatic Rollbacks)
* AWS Certified DevOps Engineer Professional Study Guide: " Leverage CodeDeploy automatic rollback features to reduce downtime and ensure application stability during deployments. "

AWS CodeDeploy supports deployment of both Lambda functions and ECS services with native integration.
* It provides deployment strategies such as canary deployments for Lambda and blue/green deployments for ECS, which minimize downtime and risk.
* CodeDeploy automates the deployment process, which reduces manual effort and improves consistency.
* AWS Systems Manager Parameter Store is a simple, managed solution for storing configuration data securely and at scale.
* Option A uses CloudFormation stack updates with resource replacement, which can cause downtime and is less flexible for minimizing downtime compared to CodeDeploy's deployment strategies.
* Option C adds unnecessary orchestration complexity with Step Functions and cross-region deployments, increasing deployment effort.
* Option D's all-at-once deployments for Lambda and rolling updates for ECS do not minimize downtime as effectively as canary and blue/green strategies. Hence, option B meets the requirement with the least deployment effort and maximizes automation and availability.
Reference from AWS Official Documentation:
* Deploying Lambda Functions with CodeDeploy: " AWS CodeDeploy supports canary and linear deployment strategies for AWS Lambda functions to reduce deployment risk. " (CodeDeploy Lambda Deployment)
* Deploying ECS Services with CodeDeploy Blue/Green: " CodeDeploy supports blue/green deployments for ECS to minimize downtime during service updates. " (CodeDeploy ECS Blue/Green)
* AWS Systems Manager Parameter Store: " Parameter Store provides secure, hierarchical storage for configuration data management. " (Systems Manager Parameter Store)

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