Activity-Based Scheduling of IT Changes
AIMS '07 Proceedings of the 1st international conference on Autonomous Infrastructure, Management and Security: Inter-Domain Management
A Runtime Constraint-Aware Solution for Automated Refinement of IT Change Plans
DSOM '08 Proceedings of the 19th IFIP/IEEE international workshop on Distributed Systems: Operations and Management: Managing Large-Scale Service Deployment
Strategy-Trees: A Feedback Based Approach to Policy Management
MACE '08 Proceedings of the 3rd IEEE international workshop on Modelling Autonomic Communications Environments
Computer Networks: The International Journal of Computer and Telecommunications Networking
DSOM '09 Proceedings of the 20th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management: Integrated Management of Systems, Services, Processes and People in IT
Achieving High-Level Directives Using Strategy-Trees
MACE '09 Proceedings of the 4th IEEE International Workshop on Modelling Autonomic Communications Environments
Scheduling-capable autonomic manager for policy-based IT change management system
Enterprise Information Systems
Business-driven decision support for change management: planning and scheduling of changes
DSOM'06 Proceedings of the 17th IFIP/IEEE international conference on Distributed Systems: operations and management
Strategy-trees: a novel approach to policy-based management
Strategy-trees: a novel approach to policy-based management
Cloud services evaluation framework
Proceedings of the Workshop on Open Source and Design of Communication
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Change management in a cloud environment is often complicated by the different needs of the cloud clients. Changes are not applied all at once. For example, a client may require that a change to the Platform-as-Service (PaaS) instance assigned to it must only be done on the weekend while another client allows for the change to be done at any time. The time periods at which changes can be applied may be specified in SLAs. A change deployment schedule for making changes to PaaS instances often depends on the cloud provider policies and on the SLAs between the clients and the cloud provider. Different sets of cloud provider policies may result in different deployment schedules. Changes are not always successful. This may result in a change being unsuccessful and a return to a previous state in order to re-start the change. Neither is desirable since it may be impact SLA guarantees such as service availability or service time that could result in the cloud provider paying out penalties. Since changes are not all applied at once it may be desirable to modify the change deployment schedule. For example, if an operator is not highly skilled or if the change's complexity is higher than expected then it may be preferable to apply the change during a time period when there are relatively few customers in order to minimize SLA violations. This paper shows how strategy trees can be incorporated into an autonomic change management system that could result in a switch of cloud provider policy sets to determine a new deployment schedule on the fly. Our experiments show that this approach can save time while minimizing SLA violations.