تکامل از زیرساخت به نوآوری با SAP بر روی AWS: استراتژی فراتر از زیرساخت برای گسترش برنامه‌های SAP شما، مدیریت داده، ادغام IoT، برنامه‌های AI/ML و عملیات IT با استفاده از خدمات AWS

The world of SAP is undergoing a major transformation, with many customers either planning or actively modernizing their SAP landscapes as part of the S/4HANA digital transformation. Given the extensive SAP transformation efforts adopted by nearly all SAP customers in recent years and the profound impact these digital changes have had on their business models and IT organizations, the authors decided to write this book. As customers embark on their SAP on AWS journey, they face three main challenges: deciding on the overall strategy, selecting the right business use cases and implementing them effectively. This book aims to address these challenges by guiding readers through the process of identifying and executing the appropriate use cases. It will highlight how customers can harness AWS services beyond merely hosting their SAP systems on AWS, demonstrating the potential of these services to drive innovation. This book covers the entire journey, from defining strategy and identifying business use cases to their implementation, providing practical tips, strategies, and insights. It serves as an essential guide for customers planning to migrate or those who have already migrated their SAP workloads to AWS, helping them explore beyond just the infrastructure aspects of their journey. You Will : Discover how to go beyond just hosting SAP systems on AWS, using the full range of AWS services to innovate and extend your SAP applications. Learn how to identify the right business use cases and implement them effectively, with practical examples and real-world scenarios. Develop the mindset and skills needed to architect modern, cloud-native, event-driven architectures, balancing trade-offs between simplicity, efficiency, and cost. This book is for: Business leaders, IT professionals, and SAP specialists who are looking to modernize their SAP landscapes by leveraging AWS services Table of Contents About the Authors About the Technical Reviewers Introduction Chapter 1: Introduction: Why Evolve from Infrastructure to Innovation with SAP on AWS? What Is “Evolving from Infrastructure to Innovation”? Change of Mindset and Culture Decoupling and Why It Matters Automate Everything Fail Fast, Learn Early, and Pivot Quickly Establish Organizational Practices Role of SAP Enterprise Architects AWS Cloud Adoption Framework SAP Enterprise Architecture Framework Pillars of SAP on AWS Innovation Pillar 1: Apps and APIs Pillar 2: IoT What Are “Things” in IoT and What Is AWS IoT Core? How Does a Device Talk to AWS IoT Core or Other Services? Predictive Maintenance Pillar 3: Data and Analytics Modern Data Warehouse The Journey of Data Fully Managed Data Ingestion and Transfer Service Generative AI Capabilities Visualization Putting It All Together Exchanging Data the Easy Way How to Start Building SAP Data Lakes on AWS Data and Analytics Solutions from SAP Third-Party Data and Analytics Solutions Pillar 4: AI and ML How Deep Learning Generative AI Differs from Traditional ML How AWS Can Help in Machine Learning How Amazon Bedrock Works AI Services from AWS AI and ML Offerings from SAP Pillar 5: DevOps and SysOps DevOps DevOps for SAP DevOps for ABAP-Based Systems DevOps in BTP SysOps for SAP Modern Disaster Recovery SAP Cloud ALM AWS Solutions Library Summary Chapter 2: Fundamentals of Modern Architecture APIs and Microservices Why APIs Are Important from a Customer Angle Evolution of SAP APIs and Integration Protocols in the Context of SAP APIs Statefulness vs. Statelessness Can SAP ERP Be the API Layer? Can SAP API Management Be the API Layer? Decoupling with Microservices The Evolution of Software Architecture Monolithic Architecture Service-Oriented Architecture Microservices Serverless Coupling: The Integration Magic Word Integration Patterns Synchronous (Request-Response) Model Asynchronous Point-to-Point Model (Queue) Asynchronous Point-to-Point Model (Router) Asynchronous Point-to-Point Model (Message Bus) Event-Driven Architecture What Is an Event? Event-Driven Architecture with SAP S/4HANA, SAP BTP, and AWS Services Summary Chapter 3: Modern Data Strategy Data Archiving Types of Data to Archive Data Management Evolution: Archiving, SAP ILM, and Data Aging in SAP HANA Classic Archiving SAP Information Lifecycle Management Data Aging What to Consider Before Archiving SAP Data Data Volume and Performance Build vs. Buy Total Cost of Ownership Maintaining Data Context SAP Data Archiving Options with AWS Services Data Lakes: A Modern Approach to Data Management How to Build Data Lakes on AWS Steps to Build a Scalable Data Lake on AWS Integrating SAP Data into an AWS Data Lake Volume, Velocity, Variety (VVV Approach) SAP Data Extraction Patterns Setting the Stage: SAP Solutions Database Extraction Pattern Using Third-Party Adapters Using AWS Services Using SAP Database Client Libraries Application-Level Data Extraction Key Considerations for Application-Level Extraction Semantic Data Extraction Layer Data Virtualization and Data Federation Data Virtualization Data Federation: Integrating Disparate Data Sources Comparison of Data Federation and Data Virtualization End-to-End Enterprise Analytics Streamlining with AWS Lake Formation Applying Machine Learning Performing Analytics User Access Achieving End-to-End Enterprise Analytics Data Mesh: A Paradigm Shift in Data Architecture Importance of Data Mesh from a Data Lake Perspective Achieving Data Mesh Architecture for SAP Data Using AWS Services Enhancing Data Governance with Data Mesh Architecture Summary Chapter 4: Extending SAP Business Processes Strategic Innovation Approach How to Use the Evaluation Framework Leveraging the Right Technology Stack SAP Business Technology Platform SAP Discovery Center Critical Architectural Considerations AWS Technology Stack AWS SDK for SAP ABAP Methodology for Choosing a Technology Stack Joint Reference Architectures from SAP and AWS Data-to-Value Architecture Example Use Case: Federation of SAP and Non SAP Data Problem Solution Architecture Data Ingestion SAP Datasphere Data Federation Result Integration and App Development Example Use Case: Event-Driven User Notification Process Problem Solution Architecture Result Platform Foundation Example Use Case: High Availability for SAP Build Work Zone Problem Solution Architecture End-User Access Amazon Route 53 SAP Business Technology Platform SAP S/4HANA on AWS Result Extending SAP Business Processes with the AWS SDK for ABAP Use Case: Modernize Document Processing in SAP Problem Solution Architecture Result Use Case: Increasing Efficiency in Financial Consolidation by 90% Problem Solution Architecture Data Preparation Model Training Model Integration Result Use Case: Improving Location Accuracy Problem Solution Architecture Result Integration of AWS B2B Data Interchange into SAP Business Processes Use Cases of AWS B2B Data Interchange specific to SAP Use Case: Creating a Data Lake Use Case: Integrating EDI Data into SAP Systems Architecture Summary Chapter 5: Smart Factory What Is a Smart Factory? Edge and Edge Devices Importance of Smart Factories Enable Digital Manufacturing Create Smart Products Optimize Supply Chain Management Attain Sustainability Goals Digital Manufacturing and Its Key Tenets Industrial Data Lakes and Analytics AWS IoT SiteWise IoT SiteWise Edge and Its Capabilities Data Ingestion Using AWS IoT SiteWise AWS IoT Core and Data Ingestion Overall Equipment Effectiveness Metric Predictive Maintenance Amazon Monitron Amazon Lookout for Equipment Predictive Quality Digital Twin Voice Technology AWS Solutions for Manufacturing and Industry Asset Maintenance & Reliability Asset Performance Management Automation Software Management Cloud Manufacturing Execution System (MES) Connected Worker Composable Operations Applications Industrial Data Fabric Lean Daily Management Computer Vision for Quality Insights Operational Technology (OT) Cybersecurity Predictive Quality SAP Solutions to Enable Digital Manufacturing SAP Solutions That Complement AWS Offerings Secrets to a Successful Implementation Summary Chapter 6: Business Transformation with AI/ML Why AI and ML Matter Now AI and ML Offerings from AWS and Use Cases Generative AI Foundation Models The Need for Amazon Bedrock Amazon Bedrock Agents How LLMs Work and How to Make Them Smarter Vector Embeddings What Is a Transformer? Customization of LLMs Prompt Engineering Fine-Tuning Supervised Fine-Tuning Full Fine-Tuning Parameter-Efficient Fine-Tuning Instruction Fine-Tuning Reinforcement Learning from Human Feedback Retrieval-Augmented Generation Amazon Q Patterns to Use Generative AI Gen AI Use Cases for SAP Technical Use Cases Amazon Q Developer to automate SAP Operational Activities Using Amazon Bedrock for Code Generation Business Use Cases Generative BI Amazon Q in QuickSight Summary Chapter 7: DevOps and SysOps for SAP DevOps in Action Putting DevOps into Practice Building a DevOps Culture Build Once Store Code Changes in Source-Controlled Repositories Automate Every Deployment Clean Your Runtime Environment Avoid Out-of-Sync Situations Control the Rollout of Changes Benefits of Automation in the Build Environment Faster Time to Market Better Code Quality Faster Bug Fixes Smoother Path to Production Efficient Infrastructure Measurable Progress Tighter Feedback Loops Collaboration and Communication Building a CI/CD Pipeline with AWS AWS CodeCommit AWS CodeBuild AWS CodeDeploy AWS CodePipeline DevOps for SAP Plan and Setup Phase Automation As a Concept on AWS Infrastructure As Code AWS Launch Wizard for SAP SAP High-Availability Architecture Custom Deployment Scripts AWS Service Catalog Integration Develop Phase Classical ABAP Development Implementing Git-Enabled Change and Transport System (gCTS) CI/CD Pipelines for SAP ABAP SAP Continuous Integration and Delivery Service in SAP BTP Project “Piper” Third-Party Tools Side-by-Side Extensions: SAP CAP and SAP ABAP RAP Test Phase Monitor and Operate Phase Observability Why Observability Matters? The Observability Maturity Model Detect, Investigate, and Remediate Detect Investigate Remediate Observability with Amazon CloudWatch How Amazon CloudWatch Works Observability with Amazon CloudWatch AppInsights for SAP SAP HANA Monitoring SAP NetWeaver Monitoring Anomaly Detection Using AI/ML How Amazon CloudWatch Application Insights Works Automated Actions on Amazon CloudWatch Alarms Integrating with Amazon EventBridge for Automated Incident Reactions SAP Traces Working with the Open Source Community SAP System Refresh SysOps for SAP Automated Operations AWS Systems Manager AWS Systems Manager for SAP (AWS SSM4SAP) Use Case 1: SAP Start and Stop Automation Using AWS Systems Manager Solution Overview Use Case 2: SAP HANA Database and OS Patching Using AWS Systems Manager Solution Overview Use Case 3: Automating SAP Configuration Health Checks on AWS Solution Overview Use Case 4: Autoscaling for SAP Solution Overview Security and Compliance AWS Config Use Case: Auditing Your SAP System on a Continuous Basis to Stay Compliant AWS CloudTrail AWS CloudTrail Lake Business Continuity Automation of DR Runbook Solution Overview How the Automation Workflow Works Benefits of This Automation Solution Summary Chapter 8: Starting your SAP on AWS Modernization Initiatives What’s Worth Solving? Strategy Is Everything Evaluation Framework SAP Signavio Ready-to-Use Solutions for Your Business Challenges AWS Solutions and SAP Missions What Are AWS Solutions? Why AWS Solutions? What Are SAP Missions? Why AWS Solutions and SAP Missions? AWS CAF in Action Creating an SAP on AWS Modernization Roadmap Modernization Process: An Iterative Approach How to Get Business Buy-in Building a Strong Business Case Presenting Your Case for Innovation Creating a Stakeholder Engagement Plan Who Are the Stakeholders? Why Is Engaging Stakeholders Important? Stakeholders from a Cloud Center of Excellence Perspective CCoE Objectives CCoE Innovation Process Demonstrating Proof of Concept Governance Enable Governance with AWS Services Transition to Operations Summary