Conference Paper

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

DOI: 10.1007/11925071_21 Conference: Middleware 2006, ACM/IFIP/USENIX 7th International Middleware Conference, Melbourne, Australia, November 27-December 1, 2006, Proceedings
Source: DBLP


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.

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Available from: Kaoutar El Maghraoui, Feb 11, 2014
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    • "In addition, in case some constraints cannot be checked statically, none of these previous works propose how to embed the constraints in the planning problem. None of [1] [4] [5] [13] [17] [20] take into account invariants given by the software architect. "
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    ABSTRACT: On the one hand, ACME is a language designed in the late 90s as an interchange format for software architectures. The need for recon guration at runtime has led to extend the language with speci c support in Plastik. On the other hand, PDDL is a predicative language for the description of planning problems. It has been designed in the AI community for the International Planning Competition of the ICAPS conferences. Several related works have already proposed to encode software architectures into PDDL. Existing planning algorithms can then be used in order to generate automatically a plan that updates an architecture to another one, i.e., the program of a recon guration. In this paper, we improve the encoding in PDDL. Noticeably we propose how to encode ADL types and constraints in the PDDL representation. That way, we can statically check our design and express PDDL constraints in order to ensure that the generated plan never goes through any bad or inconsistent architecture, not even temporarily.
    Full-text · Article · Jun 2012
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    • "In CHAMPS (Keller et al. 2004), the requested operators are translated into a set of imperative tasks and organized as a workflow to satisfy the given constraints and maximize the degree of parallelism. The work in (El Maghraoui et al. 2006) proposes translating the facts from Object Oriented Configuration Management Database (OO CMDB) to PDDL and uses a variant of Partial-Order Planner for "
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    ABSTRACT: This paper presents a prototype system called SFplanner which uses an automated planning technique to generate workflows for reconfiguring a computing infrastructure. The system allows an administrator to specify a configuration task which consists of current state, desired state and global constraints. This task is compiled to a grounded finite-domain representation as the input for the standard (unmodified) Fast-Downward planner in order to automatically generate a workflow. The execution of the workflow will bring the system into the desired state, preserving the global constraints at every stage of the workflow.
    Full-text · Article · Jan 2012
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    • "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 Step 2. The Conflict Detection layer removes a plan pl from the C-plan DB (Step 3) and checks whether the database of conflict-free plans (CF-plan DB) remains conflict-free if pl is added to it. "
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    ABSTRACT: Change Management, a core process of the Information Technology Infrastructure Library (ITIL), is concerned with the management of changes to networks and services to satisfy business goals and to minimize costly disruptions on the business. As part of Change Management, IT changes are planned for and scheduled for execution. With several uncoordinated IT operators and different (semi-)automated tools participating in the generation of IT change plans conflicts among them are likely to occur. Furthermore, state of the art IT change planners fail to prevent conflicts among plans. Conflicting IT changes, which render each other infeasible, ultimately lead to failed IT change plans and threaten the continuity of a business due to unsatisfied business goals. To tackle this problem we propose an algorithm for the automated detection of conflicting IT change plans. The algorithm is applied to several IT changes from the network and service management domain. Using simulation we identify and discuss characteristics of IT changes and plans that make deciding conflict freeness among plans more difficult. We find that our algorithm is able to decide the absence of conflicts among synthetically generated IT change plans (1-200 CRs per plan, up to 2000 CRs in total) in the context of large CMDBs (50,000 CIs) and modestly skewed IT changes. The advantage of our solution lies within the tight integration of object-oriented models, frequently used to describe CMDBs in research and commercial systems. Furthermore, existing IT change planners and schedulers remain unchanged while our solution prevents inter-plan conflicts.
    Preview · Conference Paper · May 2011
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