Common use of Management Lifecycle Clause in Contracts

Management Lifecycle. We now elaborate the management lifecycle from the viewpoint of managing as well as controlling programmable and highly observable resources. We define management and control as follows:  Management determines infrastructure configuration, resource allocations and variability constraints.  Control determines how the system responds to requests considering the constraints of management policy and information about current system state (e.g. topology, reachability, etc.). Management and control can be defined through policies where a policy is a machine-readable document used by the Platform to implement management or control decisions. It should be noted that “experiment” is a term that describes the context of use and that the lifecycle is equally applicable in all DevOps and business intelligence processes. The fact that we are conducting an experiment does not change the capabilities needed to manage and control the system. Figure 16 provides an outline of the lifecycle showing the relationship between management motivation (business intelligence, verification and validation, and experimentation down to control within the infrastructure. At the topmost level, the motivation is established setting out an objective with desired outcomes. For an experiment, this could be to test a hypothesis or for business intelligence, this could be to investigate performance of a media service within a specific geographic region. In each case, the decision maker explores service management knowledge to understand how to establish better management and control policies in relation to performance criteria. Each level has different temporal characteristics. An experiment as a construct that lives over a prolonged period of time (hours or days), reserving the necessary resources for the realization of the experiment through suitable interfaces from the (FLAME) experimentation platform, see Section 6.1. Although we consider the agreement on resource allocation as a technical operation at this level, the overall process is positioned to a large extent at the business level of the system since we see this interaction as being largely intertwined with the governance model of the platform and infrastructure provider.

Management Lifecycle. We now elaborate the management lifecycle from the viewpoint of managing as well as controlling programmable and highly observable resources. We define management and control as follows:  • Management determines infrastructure configuration, resource allocations and variability constraints.  • Control determines how the system responds to requests considering the constraints of management policy and information about current system state (e.g. topology, reachability, etc.). Management and control can be defined through policies where a policy is a machine-readable document used by the Platform to implement management or control decisions. It should be noted that “experiment” is a term that describes the context of use and that the lifecycle is equally applicable in all DevOps and business intelligence processes. The fact that we are conducting an experiment does not change the capabilities needed to manage and control the system. Figure 16 provides an outline of the lifecycle showing the relationship between management motivation (business intelligence, verification and validation, and experimentation down to control within the infrastructure. At the topmost level, the motivation is established setting out an objective with desired outcomes. For an experiment, this could be to test a hypothesis or for business intelligence, this could be to investigate performance of a media service within a specific geographic region. In each case, the decision maker explores service management knowledge to understand how to establish better management and control policies in relation to performance criteria. Each level has different temporal characteristics. An experiment as a construct that lives over a prolonged period of time (hours or days), reserving the necessary resources for the realization of the experiment through suitable interfaces from the (FLAME) experimentation platform, see Section 6.1. Although we consider the agreement on resource allocation as a technical operation at this level, the overall process is positioned to a large extent at the business level of the system since we see this interaction as being largely intertwined with the governance model of the platform and infrastructure provider.