Abstract: According to one aspect of the present disclosure a method and technique for dynamic system level agreement provisioning is disclosed. The method includes: identifying, by a data processing system of a computing environment service provider, service level criteria for a customer of computing services; determining characteristics of the computing environment; identifying a time period for providing the computing services; evaluating one or more utility functions defining service level variables; and automatically determining, by the data processing system, a service level agreement (SLA) provision for the customer based on the one or more utility functions.

Abstract: According to one aspect of the present disclosure a system and technique for dynamic system level agreement provisioning includes: a computing environment configured with allocatable computing resources; and a host having a processor unit operable to execute a service level agreement (SLA) module. The SLA module is configured to: identify service level criteria for a customer of computing services of the computing environment; determine characteristics of the computing environment; identify a time period for providing the computing services; evaluate one or more utility functions defining service level variables; and automatically determine a service level agreement (SLA) provision for the customer based on the one or more utility functions.

Abstract: Risk associated with over-committing shared resources is determined. In response to receiving a request to provision a new workload, a candidate mix of virtual machines is selected from plurality of virtual machines already running on a cloud infrastructure. A utilization profile is then created for an aggregate behavior of the candidate mix of virtual machines and a new virtual machine running the new workload. A risk inherent in over-commitment if the new workload is grouped with the candidate mix of virtual machines is determined, and whether that risk is acceptable. If the risk is acceptable, the new workload is provisioned by over-committing the candidate mix of virtual machines with the new virtual machine running on the cloud infrastructure.

Abstract: Risk associated with over-committing shared resources is determined. In response to receiving a request to provision a new workload, a candidate mix of virtual machines is selected from plurality of virtual machines already running on a cloud infrastructure. A utilization profile is then created for an aggregate behavior of the candidate mix of virtual machines and a new virtual machine running the new workload. A risk inherent in over-commitment if the new workload is grouped with the candidate mix of virtual machines is determined, and whether that risk is acceptable. If the risk is acceptable, the new workload is provisioned by over-committing the candidate mix of virtual machines with the new virtual machine running on the cloud infrastructure.