Planning service assets deployment based on information about dynamics of IT services use

Deployment of new service assets in operational IT environment is associated with the risk of disruption of the assets of its “basic” condition. Such disruptions cause failures of functioning services. To reduce the risk of disruption, the deploying service assets are divided by releases – sub-sets of service assets that will be embedded in the IT environment in one period. The traditional approach to formation and deployment of releases uses information on services structural properties to predict the number of failures due to the deployment of each service asset, each release and each application for deployment. As a result, the task of managing deployment of service assets is reduced to a sequential solution of three tasks: determining number of releases; determining composition of releases; building a release deployment schedule. The approach is based on the assumption that incorrect deployment of releases is manifested through the failure of services immediately after deployment. In practice, as a rule, this assumption is usually not fulfilled, because the use of various services by users who detect service failures is cyclical (daily, weekly, monthly, quarterly, annual). Many service failures can be detected by users in periods of time that are quite remote from the deployment time of the corresponding IT assets. The article contains the case where the managing process of IT provider configurations of the metallurgical company is well developed, i.e. its configuration database contains information on frequency of various services use at different periods of time. Information on dynamics of services application by users is used to predict time sequence of operating services failures due to deployment of each application. As a result, the task of forming and scheduling deployment of releases is formalized in the form of a discrete nonlinear programming task, the solution procedure of which allows simultaneous determination of number of releases, their composition and schedule for their deployment.