Evaluating the resiliency of stateful Internet services to significant workload spikes and data hotspots requires realistic workload traces that are usually very difficult to obtain. A popular approach is to create a workload model and generate synthetic workload, however, there exists no characterization and model of stateful spikes. In this paper we analyze five workload and data spikes and find that they vary significantly in many important aspects such as steepness, magnitude, duration, and spatial locality. We propose and validate a model of stateful spikes that allows us to synthesize volume and data spikes and could thus be used by both cloud computing users and providers to stress-test their infrastructure.
In REF , the authors analyse a number of real workload and data spikes and from the results they propose and validate a model of stateful spikes that allow them to synthesize volume and data spikes, and that can be used for cloud providers.
Characterizing, modeling, and generating workload spikes for stateful services
SoCC '10
Computer Science