Traces, Metrics, and Logs for Anomaly Detection and Root Cause Localization in Microservices

Here are the data used in our paper published at ICSE 2023: "Eadro: An End-to-End Troubleshooting Framework for Microservices on Multi-source Data".Please make sure to cite our paper whenever you use the data in your research:@inproceedings{DBLP:conf/icse/LeeYCSL23, author = {Cheryl Lee and Tianyi Yang and Zhuangbin Chen and Yuxin Su and Michael R. Lyu}, title = {Eadro: An End-to-End Troubleshooting Framework for Microservices on Multi-source Data}, booktitle = {45th {IEEE/ACM} International Conference on Software Engineering, {ICSE} 2023, Melbourne, Australia, May 14-20, 2023}, pages = {1750--1762}, publisher = {{IEEE}}, year = {2023}, url = {https://doi.org/10.1109/ICSE48619.2023.00150}, doi = {10.1109/ICSE48619.2023.00150}, timestamp = {Wed, 19 Jul 2023 10:09:12 +0200}, biburl = {https://dblp.org/rec/conf/icse/LeeYCSL23.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }

Related Organizations

Chinese University of Hong Kong
China (People's Republic of)

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	1
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average