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Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation

Summary: Seagull is a production Azure infrastructure that turns per-server telemetry into validated, continuously monitored 24-hour load forecasts with model fallback and alerting. It uses predictions to schedule PostgreSQL/MySQL backups during low-load periods, reducing customer interference across regions. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12529
Venue
VLDB
Year
2021
Pagerank
5.7764885e-05
Overall Rank
6,781 | 53.48%
DOI
10.14778/3425879.3425886

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{poppe_vldb21,
        title = {{Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation}},
        author = {Poppe, Olga and Amuneke, Tayo and Banda, Dalitso and De, Aritra and Green, Ari and Knoertzer, Manon and Nosakhare, Ehi and Rajendran, Karthik and Shankargouda, Deepak and Wang, Meina and Au, Alan and Curino, Carlo and Guo, Qun and Jindal, Alekh and Kalhan, Ajay and Oslake, Morgan and Parchani, Sonia and Ramani, Vijay and Sellappan, Raj and Sen, Saikat and Shrotri, Sheetal and Srinivasan, Soundararajan and Xia, Ping and Xu, Shize and Yang, Alicia and Zhu, Yiwen},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {2},
        pages = {154--162},
        doi = {10.14778/3425879.3425886},
        url = {https://doi.org/10.14778/3425879.3425886},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 14 of 14 citing papers.

Rank Citing Paper Year Venue Pagerank
2,226 Moneyball: Proactive Auto-Scaling in Microsoft Azure SQL Database Serverless 2022 VLDB 8.9174082e-05
2,651 Magpie: Python at Speed and Scale using Cloud Backends 2021 CIDR 8.2918086e-05
6,518 Tenant Placement in Over-subscribed Database-as-a-Service Clusters 2022 VLDB 5.8538324e-05
7,661 Machine Learning for Cloud Data Systems: the Progress so far and the Path Forward 2021 VLDB 5.5736026e-05
7,846 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 5.5331459e-05
8,193 Towards Building Autonomous Data Services on Azure 2023 SIGMOD 5.4696038e-05
8,783 Tiresias: Enabling Predictive Autonomous Storage and Indexing 2022 VLDB 5.3740362e-05
9,008 Making Data Clouds Smarter at Keebo: Automated Warehouse Optimization using Data Learning 2023 SIGMOD 5.3335632e-05
10,686 ABase: the Multi-Tenant NoSQL Serverless Database for Diverse and Dynamic Workloads in Large-scale Cloud Environments 2025 SIGMOD 5.093636e-05
10,695 Oceanus: Enable SLO-Aware Vertical Autoscaling for Cloud-Native Streaming Services in Tencent 2025 SIGMOD 5.093636e-05
11,150 Proactive Resume and Pause of Resources for Microsoft Azure SQL Database Serverless 2024 SIGMOD 5.093636e-05
11,180 Lorentz: Learned SKU Recommendation Using Profile Data (DMDS) 2024 SIGMOD 5.093636e-05
11,222 Intelligent Pooling: Proactive Resource Provisioning in Large-scale Cloud Service 2024 VLDB 5.093636e-05
11,685 Toto - Benchmarking the Efficiency of a Cloud Service 2021 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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