DieCast: Testing Distributed Systems with an Accurate Scale Model
Proceedings of the 5th ACM/USENIX Symposium on Networked Systems Design and Implementation. San Francisco, CA. April 2008
Abstract
Large-scale network services can consist of tens of thousands
of machines running thousands of unique software
configurations spread across hundreds of physical
networks. Testing such services for complex performance
problems and configuration errors remains a difficult
problem. Existing testing techniques, such as simulation
or running smaller instances of a service, have
limitations in predicting overall service behavior.
Although technically and economically infeasible at
this time, testing should ideally be performed at the same
scale and with the same configuration as the deployed
service. We present DieCast, an approach to scaling network
services in which we multiplex all of the nodes in
a given service configuration as virtual machines (VM)
spread across a much smaller number of physical machines
in a test harness. CPU, network, and disk are then
accurately scaled to provide the illusion that each VM
matches a machine from the original service in terms
of both available computing resources and communication
behavior to remote service nodes. We present
the architecture and evaluation of a system to support
such experimentation and discuss its limitations. We
show that for a variety of services—including a commercial,
high-performance, cluster-based file system—and
resource utilization levels, DieCast matches the behavior
of the original service while using a fraction of the
physical resources.
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- Authors (if Research)Diwaker Gupta, Kashi V. Vishwanath, Amin Vahdat
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- CountryUSA
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