Model Driven Provisioning: Bridging the Gap Between Declarative Object Models and Procedural Provisioning Tools

Abstract

Abstract. Today's enterprise data centers support thousands of mission-critical business applications composed of multiple distributed heterogeneous components. Application components exhibit complex dependencies on the configuration of multiple data center network, middleware, and related application resources. Applications are also associated with extended life-cycles, migrating from development to testing, staging and production environments, with frequent roll-backs. Maintaining end-to-end data center operational integrity and quality requires careful planning of (1) application deployment design, (2) resource selection, (3) provisioning operation selection, parameterization and ordering, and (4) provisioning operation execution. Current data center management products are focused on workflow-based automation of the deployment processes. Workflows are of limited value because they hard-code many aspects of the process, and are thus sensitive to topology changes. An emerging and promising class of model-based tools is providing new methods for designing detailed deployment topologies based on a set of requirements and constraints. In this paper we describe an approach to bridging the gap between generated "desired state" models and the elemental procedural provisioning operations supported by data center resources. In our approach, we represent the current and desired state of the data center using object models. We use AI planning to automatically generate workflows that bring the data center from its current state to the desired state. We discuss our optimizations to Partial Order Planning algorithms for the provisioning domain. We validated our approach by developing and integrating a prototype with a state of the art provisioning product. We also present initial results of a performance study.

Towards solid IT Change Management: Automated detection of conflicting IT change plans

“…We identified a research gap when it comes to detect conflicts among IT change plans in multi-operator Change Management environments and by IT change planning solutions [3], [4], [5], [6], [7], [8]. To prevent the occurrence of conflicting IT changes, threatening to render IT change plans infeasible, we proposed an approach for the automated detection of conflicting IT changes.…”

“…The authors propose an algorithm to refine abstract IT changes without giving logical guarantees about the feasibility of the generated plans. More recent works, such as [4], [5], [7], including our own research [6], [8], propose approaches for IT change planning that reason about the precondition and effects of IT changes within a single plan. For example, the works by Cordeiro et al [5] and Trastour et al [7] focus on the refinement of IT changes, while our hybrid approach [6] addresses refinement and state-based reasoning at the same time.…”

“…In addition to that, object-oriented models have been used in previous research by Eilam et al [23] to describe the state of a data center. IT Change plans are generated by different uncoordinated IT operators or by automated IT change planners [3], [6], [8], [4], [5], [7] based on the current state of the OO CMDB (Step 1). Generated plans are stored in a conflicting plan database (C-plan DB), i.e., a database of unscheduled, but not yet verified to be conflict-free, plans in…”

“…To ensure this, ITIL proposes a Change Management process comprising the evaluation, authorization, planning, test, scheduling, implementation, documentation, and review of IT changes [1]. IT Change Planning, an important step of the Change Management process, has been subject to intensive research [3], [4], [5], [6], [7], [8]. This let to IT change planners which can generate a single sound plan that, when executed, achieves a Request for Change.…”

“…The advantage of our approach lies within the tight integration of object-oriented (OO) Configuration Management Databases (CMDBs), frequently used by commercial CMDB systems [10] and suggested by the Common Information Model (CIM) [11] to model the current state of software and hardware in a data center. In addition to that, previously proposed work on IT change planning [3], [4], [5], [6], [7], [8] and scheduling [12], [13] remains unchanged while inter-plan conflicts are prevented. The remainder of this work is organized as follows: In Section II we discuss related work and its shortcomings with respect to the occurrence of conflicting IT changes.…”