AWS CloudFormation automates the deployment process, while CloudWatch provides observability, tracking, and tracing capabilities. The entire solution can be deployed using CloudFormation, which helps automate deployments across development, quality assurance, and production accounts. This automation can be integrated into your development pipeline, enabling iterative development and consistent deployments across your SAP landscape.

IAM secures AWS Glue and Amazon AppFlow through permission controls and authentication. These managed services access only specified data. Amazon AppFlow facilitates access to SAP workloads. Data is encrypted in transit and at rest. AWS CloudTrail logs API calls for auditing. S3 buckets and cross-region replication can store data. For enhanced security, run Amazon AppFlow over AWS PrivateLink with Elastic Load Balancing and SSL termination using AWS Certificate Manager.

Amazon AppFlow and AWS Glue can reliably move large volumes of data without breaking it down into batches. Amazon S3 provides industry-leading scalability, data availability, security, and performance for SAP data export and import. PrivateLink is a regional service, and as part of the Amazon AppFlow setup using PrivateLink, you will set up at least 50 percent of Availability Zones in the Region (minimum two Availability Zones per Region), providing an additional level of redundancy for ELB.

The SAP operational data provisioning framework captures changed data. Parallelization features in Amazon AppFlow and AWS Partner Solutions like BryteFlow and SNP enable customers to choose the number of parallel processes to run in the background, parallelizing large data volumes. Amazon S3 offers improved throughput with multi-part uploads through supported data integration mechanisms. The parallelization capabilities and seamless integration with Amazon S3 allow for efficient and scalable data ingestion from SAP systems into AWS.

By using serverless technologies like Amazon AppFlow or AWS Glue and Amazon EC2 auto scaling, you only pay for the resources you consume. To optimize costs further, extract only the required business data groups by leveraging semantic data models (for example, BW extractors or CDS views). Minimize the number of flows based on your reporting granularity needs. Implement housekeeping by setting up data tiering or deletion in Amazon S3 for old or unwanted data.

Data extraction workloads can be scheduled or invoked in real-time, eliminating the need for underlying infrastructure to run continuously. Using serverless and auto-scaling services is a sustainable approach for data extraction workloads, as these components activate only when needed. By leveraging managed services and dynamic scaling, you minimize the environmental impact of backend services. Adopt new options for Amazon AppFlow as they become available to optimize the volume and frequency of extraction.