In this course, 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 course is intended for SAP architects and SAP Operators who deploy and maintain SAP workloads on AWS. This course also aligns with the objectives of the AWS Certified: SAP on AWS Specialty (PAS-C01) exam.
Prerequisites
To get the most from this course, 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.
The AWS Backup Service. AWS Backup presents itself as the simplest way to define a data protection policy to backup AWS accounts and resources such as EC2 instances and even VMWare workloads on-premises or on AWS among many others. AWS backup provides a centralized and automated way to implement data protection across your AWS and Hybrid Workloads. You get to define a backup policy from a central console or using the AWS CLI or APIs. It's fully managed.
It's a policy-based solution where you get to define backup schedules, assign application and service resources for backup, define retention management, lifecycle management and even recovery. The automation in terms of defining a backup plan including resources backup frequency, retention and restore policies will save you time and effort, especially when compared to developing custom scripts for snapshot creation and storage or using manual procedures.
Another convenience is that you can apply backup policies to your AWS resources by tagging them, which makes it simple to implement. Your data is encrypted in transit and at rest. And AWS backup provides you consolidated backup activity logs across AWS services. The services PCI and ISO Compliant as well as HIPAA eligible. A high-level diagram of the functionality provided by AWS Backup is as shown. The source is the AWS documentation.
Notice, the service provides all the integrations to compute, storage and database services as well as the ability to configure, monitor, restore, and audit your backups. For workloads implemented on your facilities, AWS backup integrates with AWS Storage Gateway which enables your on-premises applications to seamlessly use AWS storage. You can use AWS Backup to back-up your application data stored in AWS Storage Gateway volumes. Backups of AWS Storage Gateway volumes are securely stored on AWS and are compatible with Amazon EBS, allowing you to restore your volumes to AWS or to your on-premises environment. This integration also allows you to apply the same backup policies to both your AWS resources and your on-premises data stored on AWS Storage Gateway volumes.
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).