Modern Internet services are hosted in a large collection of computers in datacenters. A hardware upgrade, a software update, or even a system configuration change can be costly. The performance impact needs to be evaluated so that one can make the decision on accepting or rejecting the change. A good understanding of the evaluation results, including the root-cause of performance change, is important for further system optimization and customization.
Evaluating the performance in the scale of a cluster has been a big challenge for a long time. Traditional benchmark-based performance analysis conducts load testing in an isolated environment, which cannot represent the behavior of a variety of co-located workloads with varying intensities in the field like Alibaba Cloud.
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