AWS Asset Planning & Workload Migration Study Guide
Asset planning
AWS Asset Planning & Workload Migration Study Guide
This guide covers the essential components of Domain 4: Accelerate Workload Migration and Modernization for the AWS Certified Solutions Architect - Professional (SAP-C02) exam, focusing specifically on asset planning and assessment.
Learning Objectives
By the end of this module, you will be able to:
- Perform a comprehensive Portfolio Assessment using AWS-native tools.
- Evaluate and categorize applications according to the 7Rs migration strategies.
- Formulate a Wave Plan for migration based on workload interdependencies.
- Calculate and justify Total Cost of Ownership (TCO) for cloud vs. on-premises environments.
Key Terms & Glossary
- Total Cost of Ownership (TCO): A financial estimate intended to help buyers determine the direct and indirect costs of a product or system (on-premises hardware vs. AWS consumption).
- Wave Planning: The process of grouping migration candidates into logical "waves" based on complexity, risk, and dependencies.
- Migration Hub: A central AWS service used to track the progress of application migrations across multiple AWS and partner tools.
- Application Discovery Service (ADS): An AWS tool that collects usage and configuration data from on-premises servers to help plan migrations.
The "Big Idea"
Asset planning is the foundational stage of the migration journey. It transforms a messy list of IT assets into a strategic roadmap. Without proper asset planning, migrations often stall due to "hidden dependencies" (e.g., a database shared by three apps you didn't know about) or "cost shocks" where the TCO was poorly estimated. Success in this domain relies on moving from an Infrastructure-centric view to an Application-centric view.
Formula / Concept Box
| Concept | Calculation / Logic |
|---|---|
| TCO Comparison | |
| Migration Effort | Higher for Refactor/Modernize; Lower for Rehost (Lift & Shift) |
| Wave Logic | Group by shared data source Prioritize low-risk/low-complexity apps first (Quick Wins) |
Hierarchical Outline
- Portfolio Assessment & Discovery
- Inventory Collection: Using AWS Application Discovery Service (Agentless or Agent-based).
- Dependency Mapping: Identifying network connections between servers.
- The 7Rs Strategy Selection
- Retire: Decommissioning apps no longer needed.
- Retain: Keeping apps on-premise (e.g., legacy mainframe).
- Rehost: "Lift and shift" to EC2.
- Relocate: Moving VMware workloads to VMC on AWS.
- Repurchase: Moving to a SaaS model (e.g., Salesforce).
- Replatform: "Lift and reshape" (e.g., Move DB to RDS without code changes).
- Refactor/Architect: Full modernization using cloud-native features (Serverless, Containers).
- Migration Execution Planning
- Prioritization: Ranking apps by business impact and technical ease.
- Data Migration: Selecting tools (DataSync, Snowball, Transfer Family).
Visual Anchors
Migration Decision Workflow
Effort vs. Business Value of Migration
\begin{tikzpicture}[scale=1.2] % Axes \draw[->] (0,0) -- (6,0) node[right] {Technical Effort}; \draw[->] (0,0) -- (0,5) node[above] {Cloud Benefit};
% Points
\filldraw[blue] (1,1) circle (2pt) node[below right] {Rehost};
\filldraw[orange] (3,2.5) circle (2pt) node[below right] {Replatform};
\filldraw[red] (5,4.5) circle (2pt) node[below right] {Refactor};
% Curve
\draw[dashed, gray] (1,1) .. controls (2,2) and (4,4) .. (5,4.5);\end{tikzpicture}
Definition-Example Pairs
- Replatforming: Changing the underlying platform of an application to leverage cloud features without changing core code.
- Example: Moving a self-managed Oracle database on a Windows server to Amazon RDS for Oracle to reduce patching overhead.
- Retaining: Keeping an application in its current environment, often due to compliance or high latency requirements.
- Example: A high-frequency trading application that requires sub-millisecond local fiber access to a specific physical exchange.
- Repurchasing: Moving to a different product, typically a SaaS platform.
- Example: Moving from a self-hosted Jenkins server to using GitHub Actions or AWS CodeBuild.
Worked Examples
Scenario: The Legacy Web App
Scenario: A company has a 10-year-old Java web app running on an old version of Tomcat. It connects to a MySQL database. Management wants to move to AWS in 4 weeks to close a data center.
Step 1: Assessment
- Use AWS Migration Hub to track the project.
- Run Application Discovery Service to find dependencies.
Step 2: Strategy Selection
- Refactor? No (Too slow, 4-week deadline).
- Choice: Replatform. Move the web tier to an Elastic Beanstalk environment and the database to Amazon RDS. This meets the deadline while removing the burden of OS/DB patching.
Step 3: Execution
- Use AWS DataSync to move static assets and a database backup to AWS.
Checkpoint Questions
- Which of the 7Rs offers the fastest migration path for a large-scale data center evacuation?
- What is the primary difference between the "Agentless" and "Agent-based" versions of the AWS Application Discovery Service?
- Why is "Retire" considered a valid migration strategy in the assessment phase?
- How does AWS Migration Hub assist in a multi-partner tool environment?
[!TIP] Answers: 1. Rehost (Lift & Shift). 2. Agentless is for VMware environments (vCenter); Agent-based is for physical servers or other hypervisors. 3. It reduces the scope of migration and saves costs by identifying unused assets. 4. It provides a single dashboard to track progress from various migration tools.
Muddy Points & Cross-Refs
- Replatform vs. Refactor: This is the most common confusion. If you are changing the way the code works (e.g., breaking a monolith into microservices), it is Refactor. If you are just changing the managed service it runs on (e.g., putting a container in Fargate instead of EC2), it is usually Replatform.
- Cross-Reference: For data movement specifics, see the Data Migration Tools module (covering Snowball Edge vs. Snowcone).
Comparison Tables
Comparing Assessment Discovery Methods
| Feature | Agentless Discovery | Agent-based Discovery |
|---|---|---|
| Environment | VMware vCenter only | Physical, AWS, or Any Hypervisor |
| Data Collected | Configuration & Usage | Process-level info & Network Dependencies |
| Complexity | Low (Single appliance) | High (Install on every VM) |
| Best For | Initial rapid scan | Deep dependency mapping |