GridWorkflow: A Flexible Failure Handling Framework for the Grid
HPDC '03 Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing
Recovery Oriented Computing (ROC): Motivation, Definition, Techniques,
Recovery Oriented Computing (ROC): Motivation, Definition, Techniques,
The Grid 2: Blueprint for a New Computing Infrastructure
The Grid 2: Blueprint for a New Computing Infrastructure
Proceedings of the twentieth ACM symposium on Operating systems principles
Fault Tolerance Techniques for the Merrimac Streaming Supercomputer
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Fault-tolerant grid services using primary-backup: feasibility and performance
CLUSTER '04 Proceedings of the 2004 IEEE International Conference on Cluster Computing
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The move towards IT outsourcing is the first step towards an environment where compute infrastructure is treated as a service. In utility computing this IT service has to honor Service Level Agreements (SLA) in order to meet the desired Quality of Service (QoS) guarantees. Such an environment requires reliable services in order to maximize the utilization of the resources and to decrease the Total Cost of Ownership (TCO). Such reliability cannot come at the cost of resource duplication, since it increases the TCO of the data center and hence the cost per compute unit. We, in this paper, look into aspects of projecting impact of hardware failures on the SLAs and techniques required to take proactive recovery steps in case of a predicted failure. By maintaining health vectors of all hardware and system resources, we predict the failure probability of resources based on observed hardware errors/failure events, at runtime. This inturn influences an availability aware middleware to take proactive action (even before the application is affected in case the system and the application have low recoverability). The proposed framework has been prototyped on a system running HP-UX. Our offline analysis of the prediction system on hardware error logs indicate no more than 10% false positives. This work to the best of our knowledge is the first of its kind to perform an end-to-end analysis of the impact of a hardware fault on application SLAs, in a live system.