The Well-Architected Framework

Intermediate
3m 28s
63
3.6/5

In this lesson, we discuss planning for data recovery, including disaster recovery of SAP workloads in AWS. We present and discuss some of the design and best practices gathered by AWS customers, AWS Experts, and SAP Specialists running SAP workloads on AWS.

Learning Objectives

We introduce best practices for business continuity and disaster recovery related to SAP workloads on AWS. The recommendations are aligned with the Reliability pillar of the Well-Architected Framework and focus on planning for data protection and recovery of SAP solutions implemented using AWS services.

Intended Audience

This lesson is intended for SAP architects and SAP Operators who deploy and maintain SAP workloads on AWS. This lesson also aligns with the objectives of the AWS Certified: SAP on AWS Specialty (PAS-C01) exam.

Prerequisites

To get the most from this lesson, you will need to meet the requirements for the AWS Solutions Architect Associate or AWS SysOps Associate certifications or the equivalent experience. This includes the function, anatomy, and operation of core AWS services that are relevant to SAP implementations, such as: 

  • The AWS global infrastructure, Amazon VPCs, Amazon EC2, EBS, EFS, S3, Glacier, IAM, CloudWatch, CloudTrail, the AWS CLI, Amazon Route 53
  • The Well-Architected Framework

It is also assumed that you are familiar with SAP software workloads and their implementation. SAP is well known for enterprise resource planning (ERP) applications, including SAP Business Suite, SAP Net weaver, SAP S/4HANA solutions, and supporting products.

About the Author
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Jorge Negrón
AWS Content Architect
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Experienced in architecture and delivery of cloud-based solutions, the development, and delivery of technical training, defining requirements, use cases, and validating architectures for results. Excellent leadership, communication, and presentation skills with attention to details. Hands-on administration/development experience with the ability to mentor and train current & emerging technologies, (Cloud, ML, IoT, Microservices, Big Data & Analytics).

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