CONTAX Instance Scheduler Application

One of the pillars of the AWS Well-Architected Framework is Cost Optimization. In it, AWS encourages its customers to:

Adopt a consumption model. Pay only for the computing resources you consume, and increase or decrease usage depending on business requirements. For example, development and test environments are typically only used for eight hours a day during the work week. You can stop these resources when they’re not in use for a potential cost savings of 75% (40 hours versus 168 hours).

With large monolithic workloads such as SAP S/4HANA, this is easier said than done. SAP production workloads are designed to run nonstop with downtimes and maintenance windows planned well in advance. On AWS that approach needn't be taken for non-productive instances. With CONTAX's S/4HANA instance scheduling application, it is possible for non-technical users to schedule the starting and stopping of SAP S/4HANA instances when they're not in use.

If AWS customers shut down their SAP HANA instances outside of work hours, it’s possible for them to see a significant reduction in compute cost even when compared to compute reservation payed upfront. The graph below shows an example of such a cost savings for an r6i.16xlarge instance as compared to various AWS billing options.

To help make the scheduling of non-productive SAP S/4HANA instances easier for our customers, CONTAX has created a web based-application that allows non-technical users to create and update schedules to automate the starting and stopping of non-productive SAP S/4HANA instances.

The SAP start/stop automation scripts are deployed within our customers’ AWS accounts using a CloudFormation template. In addition to the S/4HANA start/stop automation document, the template creates a role to allow CONTAX’s instance scheduler application to create and update schedules using AWS EventBridge.

All of the authorization and automation is controlled within the customer’s AWS account, and is able to be reviewed by the customer team before deployment.

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