Towards Building Autonomous Data Services on Azure
Summary: ML-driven automation for Azure cloud data services to configure, optimize, and operate autonomous data services. Leverages workload traces and telemetry to meet SLAs and minimize cost, offering perspectives for providers and users on building autonomous, data-driven services. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yiwen Zhu (Microsoft)
- 2. Yuanyuan Tian (Microsoft)
- 3. Joyce Cahoon (Microsoft)
- 4. Subru Krishnan (Microsoft)
- 5. Ankita Agarwal (Microsoft)
- 6. Rana Alotaibi (Microsoft)
- 7. Jesús Camacho-Rodríguez (Microsoft)
- 8. Bibin Chundatt (Microsoft)
- 9. Andrew Chung (Microsoft)
- 10. Niharika Dutta (Microsoft)
- 11. Andrew Fogarty (Microsoft)
- 12. Anja Gruenheid (Microsoft)
- 13. Brandon Haynes (Microsoft)
- 14. Matteo Interlandi (Microsoft)
- 15. Minu Iyer (Microsoft)
- 16. Nick Jurgens (Microsoft)
- 17. Sumeet Khushalani (Microsoft)
- 18. Brian Kroth (Microsoft)
- 19. Manoj Kumar (Microsoft)
- 20. Jyoti Leeka (Microsoft)
- 21. Sergiy Matusevych (Microsoft)
- 22. Minni Mittal (Microsoft)
- 23. Andreas Mueller (Microsoft)
- 24. Kartheek Muthyala (Microsoft)
- 25. Harsha Nagulapalli (Microsoft)
- 26. Yoonjae Park (Microsoft)
- 27. Hiren Patel (Microsoft)
- 28. Anna Pavlenko (Microsoft)
- 29. Olga Poppe (Microsoft)
- 30. Santhosh Ravindran (Microsoft)
- 31. Karla Saur (Microsoft)
- 32. Rathijit Sen (Microsoft)
- 33. Steve Suh (Microsoft)
- 34. Arijit Tarafdar (Microsoft)
- 35. Kunal Waghray (Microsoft)
- 36. Demin Wang (Microsoft)
- 37. Carlo Curino (Microsoft)
- 38. Raghu Ramakrishnan (Microsoft)
BibTeX Citation
@inproceedings{zhu_sigmod23,
title = {{Towards Building Autonomous Data Services on Azure}},
author = {Zhu, Yiwen and Tian, Yuanyuan and Cahoon, Joyce and Krishnan, Subru and Agarwal, Ankita and Alotaibi, Rana and Camacho-Rodríguez, Jesús and Chundatt, Bibin and Chung, Andrew and Dutta, Niharika and Fogarty, Andrew and Gruenheid, Anja and Haynes, Brandon and Interlandi, Matteo and Iyer, Minu and Jurgens, Nick and Khushalani, Sumeet and Kroth, Brian and Kumar, Manoj and Leeka, Jyoti and Matusevych, Sergiy and Mittal, Minni and Mueller, Andreas and Muthyala, Kartheek and Nagulapalli, Harsha and Park, Yoonjae and Patel, Hiren and Pavlenko, Anna and Poppe, Olga and Ravindran, Santhosh and Saur, Karla and Sen, Rathijit and Suh, Steve and Tarafdar, Arijit and Waghray, Kunal and Wang, Demin and Curino, Carlo and Ramakrishnan, Raghu},
series = {{SIGMOD} '23},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3555041.3589674},
url = {https://dl.acm.org/doi/10.1145/3555041.3589674},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,327 | Breaking It Down: An In-depth Study of Index Advisors | 2024 | VLDB | 5.9124005e-05 |
| 7,686 | TDSQL: Tencent Distributed Database System | 2024 | VLDB | 5.5676271e-05 |
| 8,861 | Optimizing the cloud? Don't train models. Build oracles! | 2024 | CIDR | 5.355716e-05 |
| 8,984 | Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems | 2024 | VLDB | 5.3395569e-05 |
| 9,257 | MLOS in Action: Bridging the Gap Between Experimentation and Auto-Tuning in the Cloud | 2024 | VLDB | 5.2972217e-05 |
| 9,771 | Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment | 2025 | SIGMOD | 5.2209769e-05 |
| 11,180 | Lorentz: Learned SKU Recommendation Using Profile Data (DMDS) | 2024 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 26 of 26 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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