Migration Decision Framework and real-world case studies that closely align with enterprise architecture principles. Here is a summary of the core migration strategies covered in your current documents:

Migration Decision FrameworkThe sources outline a strategic framework for deciding how to migrate enterprise workloads, evaluating factors like time pressure, cost, risk, and team skills:

• Rehost (Lift & Shift): This is the best approach when there is high time pressure, such as a looming data center hardware refresh. It involves moving assets directly to the cloud (e.g., on-prem VMs to AWS EC2) requiring low cloud skills and offering low immediate risk, but also low initial cost optimization.
• Replatform: A middle-ground approach that involves light optimizations, such as moving VMs to containers (like ECS) or migrating self-managed databases to managed services, without completely rewriting the application's core architecture.
• Refactor: This approach requires high cloud skills and time but delivers the highest long-term cost optimization and business value. It involves fully modernizing the architecture, such as breaking a monolithic application into microservices or serverless functions.
• Repurchase & Retire: Retiring involves decommissioning unused applications, while repurchasing means replacing legacy tools with modern SaaS equivalents (e.g., replacing an on-prem CRM with Salesforce).

Key Enterprise Architecture Themes in the Case Studies:

• Phased Modernization ("Migrate then Modernize"): Rather than refactoring massive monolithic applications immediately, architects often propose a phased approach. For example, in the E-Commerce case study, the monolith is first rehosted to buy time and eliminate data center risk, and then refactored into microservices later.
• Strict Security & Compliance Guardrails: For highly regulated workloads like banking and healthcare, architectures must enforce non-negotiable compliance rules. This includes utilizing Service Control Policies (SCPs) to enforce encryption and region restrictions, implementing immutable log archives, and using isolated multi-account landing zones.
• Hybrid and Edge Computing: When physical systems cannot move to the public cloud due to sub-10ms latency requirements or disconnected operations (like in manufacturing IoT), architectures must incorporate edge layers using AWS Outposts for local compute and AWS IoT Greengrass for local machine learning inference.