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Many enterprises are beginning to exploit shared resource pool
environments. In these environments, the application workloads exploit
a common set of hardware resources. These are complex
environments where selecting
per-application scheduler parameter settings is a challenging task. It is a
challenge because i) the capacity of resource pools are generally overbooked,
i.e., the sum of per-application peak demands are greater than the
capacity of the pool, and ii) because different applications can have
different quality of service (QoS) requirements that are affected
by the applications' ability to obtain capacity when needed.
We are designing and developing a capacity management service for
resource pools that support enterprise applications. It automatically
searches for workload assignments that best meet objectives such as
consolidation, load leveling, and problem solving. Consolidation packs
workloads onto a small set of resources, load leveling distributes
workloads across a fixed size resource pool to lessen the likelihood
of service level violations, and problem solving recommends
alternative assignments to lessen the impact of unexpected demands on
a particular resource. The service evaluates alternative workload
assignments more quickly and accurately than human operators. As a
result it can lower administrative costs, reduce the risks associated
with resource sharing, and improve the use of resource pool
infrastructure.
Related Papers and Reports
- D. Gmach, J. Rolia, L. Cherkasova, and A. Kemper: Workload
Analysis and Demand Prediction of Enterprise Data Center
Applications. Proc. of the 2007 IEEE International
Symposium on Workload Characterization (IISWC'2007), Boston,
MA, USA, September 27-29, 2007.
- D. Gmach, J. Rolia, L. Cherkasova, and A. Kemper: Capacity Management and Demand
Prediction for Next Generation Data Centers. Proc. of the
International IEEE Conference on Web Services (ICWS'2007), Salt Lake
City, Utah, USA, July 9-13, 2007.
- J. Rolia, L. Cherkasova, and R. Friedrich: Performance Engineering for EA Systems
in Next Generation Data Centres. Proc. of the Sixth International
Workshop on Software and Performance (WOSP'2007), Buenos Aires,
Argentina, February 5-8, 2007.
- L. Cherkasova and J. Rolia: R-Opus: A Composite Framework
for Application Performability and QoS in Shared Resource Pools.
In Proc. of the International Conference on Dependable Systems and
Networks, (DSN'2006), Philadelphia, PA, USA, June, 2006.
- J. Rolia, L. Cherkasova, C. McCarthy: Configuring Workload Manager Control
Parameters for Resource Pools. Proc. of the 10th IEEE/IFIP
Network Operations and Management Symposium (NOMS'2006),
Vancouver, Canada, April 2006.
- J. Rolia, L. Cherkasova, M. Arlitt, Vijay Machiraju: An
Automated Approach for Supporting Application QoS in Shared Resource
Pools. IFIP/IEEE International Workshop on Self-Managed
Systems & Services (SELFMAN'2005), France, Nice, May 19, 2005, co-located with IM 2005.
- J. Rolia, L. Cherkasova, M. Arlitt, A. Andrzejak: A Capacity Management Service for
Resource Pools. Proc. of the Fifth International Workshop on Software and
Performance (WOSP'2005), Spain, July 11-15, 2005.
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