Papers › The PetShop Dataset -- Finding Causes of Performance Issues across Microservices

The PetShop Dataset -- Finding Causes of Performance Issues across Microservices

8 Nov 2023arXiv:2311.04806archive 2025-07-28

Michaela Hardt, William R. Orchard, Patrick Blöbaum, Shiva Kasiviswanathan, Elke Kirschbaum

Identifying root causes for unexpected or undesirable behavior in complex systems is a prevalent challenge. This issue becomes especially crucial in modern cloud applications that employ numerous microservices. Although the machine learning and systems research communities have proposed various techniques to tackle this problem, there is currently a lack of standardized datasets for quantitative benchmarking. Consequently, research groups are compelled to create their own datasets for experimentation. This paper introduces a dataset specifically designed for evaluating root cause analyses in microservice-based applications. The dataset encompasses latency, requests, and availability metrics emitted in 5-minute intervals from a distributed application. In addition to normal operation metrics, the dataset includes 68 injected performance issues, which increase latency and reduce availability throughout the system. We showcase how this dataset can be used to evaluate the accuracy of a variety of methods spanning different causal and non-causal characterisations of the root cause analysis problem. We hope the new dataset, available at https://github.com/amazon-science/petshop-root-cause-analysis/ enables further development of techniques in this important area.

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load_scenario amazon-science/petshop-root-cause-analysis/code/rca_task.py official repository ran Apache-2.0 (permissive) · 16cec641c1aa2a80 · report
map_df amazon-science/petshop-root-cause-analysis/code/data_preprocessing.py official repository ran Apache-2.0 (permissive) · e75574a3fc479079 · report
pad_and_fill amazon-science/petshop-root-cause-analysis/code/counterfactual_attribution.py official repository ran Apache-2.0 (permissive) · a02d81be5066e190 · report
reduce_df amazon-science/petshop-root-cause-analysis/code/counterfactual_attribution.py official repository ran Apache-2.0 (permissive) · 5c4500df13246a46 · report
evaluate amazon-science/petshop-root-cause-analysis/code/rca_task.py official repository unverified Apache-2.0 (permissive) · 584c5668c01f4b7c · report
evaluate_specificity amazon-science/petshop-root-cause-analysis/code/rca_task.py official repository unverified Apache-2.0 (permissive) · e2dc0a8836eba4db · report

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