SuperDRI: Graph-Guided Autonomous Troubleshooting for Cloud Databases
Summary: SuperDRI learns typed InvestiGraph troubleshooting workflows from 1,300+ historical cloud-database incidents, replacing hand-authored playbooks. Agentic graph traversal generates read-only KQL queries, incorporates engineer feedback, and autonomously diagnoses production incidents. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Yiwen Zhu (Microsoft)
- 2. Joyce Cahoon (Microsoft)
- 3. Qiushi Bai (Microsoft)
- 4. Anna Pavlenko (Microsoft)
- 5. Divya Vermareddy (Microsoft)
- 6. Meina Wang (Microsoft)
- 7. Mathieu Demarne (Microsoft)
- 8. Wenjing Wang (Microsoft)
- 9. Swati Bararia (Microsoft)
- 10. Hannah Lerner (Microsoft)
- 11. Katherine Lin (Microsoft)
- 12. Subru Krishnan (Microsoft)
- 13. Miso Cilimdzic (Microsoft)
BibTeX Citation
@article{zhu_vldb26,
title = {{SuperDRI: Graph-Guided Autonomous Troubleshooting for Cloud Databases}},
author = {Zhu, Yiwen and Cahoon, Joyce and Bai, Qiushi and Pavlenko, Anna and Vermareddy, Divya and Wang, Meina and Demarne, Mathieu and Wang, Wenjing and Bararia, Swati and Lerner, Hannah and Lin, Katherine and Krishnan, Subru and Cilimdzic, Miso},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {12},
pages = {4678--4681},
doi = {10.14778/3827998.3828095},
url = {https://doi.org/10.14778/3827998.3828095},
year = {2026}
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