AWS Migration & Innovation – Cloud Practitioner Study Guide
Overview
This study guide covers AWS cloud migration strategies, key migration services, the AWS Cloud Adoption Framework (CAF), and emerging technologies that support cloud innovation. Together, these topics represent core knowledge for understanding how organizations plan, execute, and optimize their move to AWS. Mastery of these concepts is essential for the AWS Cloud Practitioner certification exam.
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Cloud Migration Strategies: The 6 R's
Summary
When migrating to the cloud, organizations rarely use a one-size-fits-all approach. AWS defines six migration strategies — commonly called the 6 R's — to categorize how each application in a portfolio should be handled. Choosing the right strategy depends on business needs, time constraints, technical requirements, and cost considerations.
The 6 R's at a Glance
| Strategy | Nickname | Core Action | Cost/Effort |
|---|---|---|---|
| Rehost | Lift and Shift | Move as-is | Low |
| Replatform | Lift, Tinker, and Shift | Minor optimizations | Low–Medium |
| Repurchase | Drop and Shop | Replace with SaaS | Medium |
| Refactor | Re-architect | Rebuild from scratch | High |
| Retire | — | Decommission | Saves money |
| Retain | — | Keep on-premises | Deferred cost |
Detailed Breakdown
- Move applications to the cloud with zero modifications
- Fastest strategy; ideal for quick migrations at scale
- Example: Moving an on-premises VM directly to Amazon EC2
- Make minor optimizations to take advantage of cloud benefits
- Core architecture remains unchanged
- Example: Migrating an on-premises database to Amazon RDS
- Abandon the existing application and replace it with a SaaS product
- Involves moving to a completely different, often vendor-managed platform
- Example: Replacing a legacy on-premises CRM with Salesforce
- Completely redesign the application from the ground up using cloud-native features
- Most expensive and time-consuming strategy
- Driven by a strong business need for scalability, performance, or new features
- Example: Breaking a monolithic app into microservices using AWS Lambda and containers
- Decommission applications that are no longer needed or useful
- Reduces migration portfolio, saves costs, and focuses resources on valuable workloads
- Keep applications on-premises temporarily or indefinitely
- Used for apps not yet ready for migration (e.g., recently upgraded, compliance reasons, or requiring major refactoring first)
Key Terms
Watch Out For
> ⚠️ Rehost vs. Replatform: Both move apps to the cloud, but Replatform makes minor changes (e.g., adopting RDS), while Rehost makes no changes. Don't confuse them.
> ⚠️ Retire vs. Retain: Retire = permanently remove unused apps. Retain = keep them for now (often temporarily). These are opposites.
> ⚠️ Refactor is the most expensive strategy — exam questions may test whether you can identify when it's appropriate despite high cost.
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AWS Migration Services
Summary
AWS offers a suite of services designed to simplify, accelerate, and automate cloud migrations. These tools address data transfer at scale, database migration, server migration, and portfolio-level tracking.
AWS Snow Family
The AWS Snow Family solves the problem of moving large volumes of data to AWS when internet-based transfer is impractical due to bandwidth limitations, high costs, or time constraints. These are physical devices shipped to your location.
- Smallest and most portable Snow device
- Holds up to 8 TB of usable storage
- Designed for edge computing and remote/space-constrained environments
- Can also run compute workloads at the edge
- Mid-range device for petabyte-scale data transfers
- Available in Snowball Edge Storage Optimized and Compute Optimized variants
- Suitable for most large-scale data migration projects
- Exabyte-scale data transfer using a 45-foot shipping container
- Can transfer up to 100 PB per Snowmobile
- Used for the most massive migrations where even Snowball is insufficient
Other Key Migration Services
- Automates lift-and-shift (Rehost) migrations
- Migrates physical, virtual, and cloud servers to AWS
- Minimizes manual, error-prone migration processes
- Migrates databases to AWS quickly and securely
- Source database remains operational during migration (minimal downtime)
- Supports homogeneous migrations (e.g., Oracle → Oracle) and heterogeneous migrations (e.g., SQL Server → Amazon Aurora)
- Provides a single dashboard to track migration progress
- Aggregates data from multiple AWS and partner migration tools
- Gives full visibility into the entire migration portfolio
Key Terms
Watch Out For
> ⚠️ Snow Family sizing: Know the scale differences — Snowcone (8 TB) → Snowball (petabytes) → Snowmobile (100 PB / exabyte scale). Exam questions often test which device is appropriate for a given data size.
> ⚠️ DMS keeps the source database running: This is a key differentiator — it supports migrations with minimal downtime, not zero downtime.
> ⚠️ MGN vs. DMS: MGN migrates servers/applications; DMS migrates databases specifically. Don't mix these up.
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AWS Cloud Adoption Framework (CAF)
Summary
The AWS Cloud Adoption Framework (CAF) is a structured guide that helps organizations plan and execute their cloud adoption journey. It organizes guidance into six perspectives, each targeting a different aspect of the organization. These perspectives are grouped into business capabilities and technical capabilities.
The Six CAF Perspectives
#### Business Capabilities (People & Process)
These perspectives ensure cloud adoption is aligned with organizational goals and that the right people and processes are in place.
- Ensures IT aligns with business needs
- Focuses on business strategy, ROI, and value creation
- Targets HR and staffing leaders
- Evaluates organizational structures, roles, skills gaps, and training requirements
- Helps manage employees through cloud transformation
- Focuses on skills and processes to align IT strategy with business strategy
- Manages cloud investments, risk, and compliance
#### Technical Capabilities (Platform & Operations)
These perspectives guide the technical teams responsible for delivering and operating cloud workloads.
- Guides architecture, infrastructure provisioning, and cloud platform design
- Focuses on adopting cloud-native technologies
- Ensures the organization meets security objectives
- Covers identity, data protection, infrastructure security
- Defines how business operations are conducted in the cloud
- Focuses on monitoring, incident management, and operational health
Key Terms
Watch Out For
> ⚠️ Memorize the split: Business/People/Governance = business capabilities; Platform/Security/Operations = technical capabilities. This is commonly tested.
> ⚠️ The People perspective ≠ the Business perspective: People focuses on HR, training, and organizational change; Business focuses on strategy and ROI alignment.
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Innovation & Emerging Technologies
Summary
AWS supports innovation through a broad portfolio of AI, machine learning, and serverless services. These tools allow organizations to modernize applications, extract insights from data, and build intelligent capabilities without deep specialized expertise.
Machine Learning & AI Services
- Fully managed service for building, training, and deploying machine learning models
- Removes heavy lifting of infrastructure management for ML workflows
- Suitable for developers and data scientists
- Uses ML to automatically discover, classify, and protect sensitive data in Amazon S3
- Identifies Personally Identifiable Information (PII) and other sensitive data
- Provides dashboards and alerts for data access visibility
- AI service for building conversational interfaces (chatbots) using voice and text
- Powers Amazon Alexa
- Belongs to the Artificial Intelligence (AI) category
- AI service that automatically extracts text and data from scanned documents
- Goes beyond basic OCR — understands the context of fields in forms and tables
- Represents AI-powered document processing innovation
Serverless Computing
- Runs code in response to events (e.g., file upload, HTTP request)
- You only pay for the compute time your code actually uses
- Eliminates the need to manage EC2 instances for event-driven workloads
Learning & Experiential Innovation
- A 1/18th scale autonomous race car and cloud-based 3D racing simulator
- Teaches developers reinforcement machine learning through competitive racing
- Makes ML accessible and engaging for beginners
Key Terms
Watch Out For
> ⚠️ Macie vs. other security services: Macie is specifically for sensitive data discovery in S3. Don't confuse it with GuardDuty (threat detection) or Inspector (vulnerability assessment).
> ⚠️ Textract ≠ simple OCR: Textract understands structure (forms, tables), not just raw text. Exam scenarios may distinguish between basic text extraction and structured document understanding.
> ⚠️ Lambda is serverless, not server-free: The servers still exist — you just don't manage them. "Serverless" refers to the abstraction, not the absence of physical hardware.
> ⚠️ DeepRacer teaches reinforcement learning specifically — not supervised or unsupervised learning. This distinction may appear in exam questions.
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Quick Review Checklist
Use this checklist to confirm you're ready for exam questions on these topics:
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Review this guide alongside AWS's official documentation and practice exam questions to reinforce these concepts before your exam.