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MagicScaler: Uncertainty-aware, Predictive Autoscaling

Summary: MagicScaler fuses multi-scale attention with Gaussian process regression to produce demand forecasts with quantified uncertainty, capturing scale-sensitive temporal patterns. An uncertainty-aware scaler uses a stochastic-constraint loss to trade off running cost vs QoS risk, validated on Alibaba clusters with superior results. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13397
Venue
VLDB
Year
2023
Pagerank
6.9980354e-05
Overall Rank
3,950 | 72.91%
DOI
10.14778/3611540.3611566

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{pan_vldb23,
        title = {{MagicScaler: Uncertainty-aware, Predictive Autoscaling}},
        author = {Pan, Zhicheng and Wang, Yihang and Zhang, Yingying and Yang, Sean Bin and Cheng, Yunyao and Chen, Peng and Guo, Chenjuan and Wen, Qingsong and Tian, Xiduo and Dou, Yunliang and Zhou, Zhiqiang and Yang, Chengcheng and Zhou, Aoying and Yang, Bin},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {12},
        pages = {3808--3821},
        doi = {10.14778/3611540.3611566},
        url = {https://doi.org/10.14778/3611540.3611566},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 10 of 10 citing papers.

Rank Citing Paper Year Venue Pagerank
3,369 TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods 2024 VLDB 7.4706661e-05
7,825 RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems 2025 VLDB 5.5367884e-05
8,910 Vertically Autoscaling Monolithic Applications with CaaSPER: Scalable Container-as-a-Service Performance Enhanced Resizing Algorithm for the Cloud 2024 SIGMOD 5.3483178e-05
10,559 OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning 2026 VLDB 5.093636e-05
10,583 Resilience-Aware Elastic Scaling for Cloud-Native Online DL Training on Multi-Tenant GPU Clusters 2026 VLDB 5.093636e-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
10,827 A Systematic Study on Early Stopping Metrics in HPO and the Implications of Uncertainty 2025 VLDB 5.093636e-05
11,251 QCore: Data-Efficient, On-Device Continual Calibration for Quantized Models 2024 VLDB 5.093636e-05
11,291 OptScaler: A Collaborative Framework for Robust Autoscaling in the Cloud 2024 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

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

Rank Cited Paper Year Venue Pagerank
2,226 Moneyball: Proactive Auto-Scaling in Microsoft Azure SQL Database Serverless 2022 VLDB 8.9174082e-05
3,219 iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases 2019 VLDB 7.6283153e-05
3,320 Autoscaling Tiered Cloud Storage in Anna 2019 VLDB 7.5223482e-05
3,345 Effective Travel Time Estimation: When Historical Trajectories over Road Networks Matter 2020 SIGMOD 7.4975085e-05
3,861 RobustPeriod: Robust Time-Frequency Mining for Multiple Periodicity Detection 2021 SIGMOD 7.0666117e-05
4,424 Classical and Contemporary Approaches to Big Time Series Forecasting 2019 SIGMOD 6.7104881e-05
4,851 Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles 2022 VLDB 6.4803317e-05
5,129 AutoCTS: Automated Correlated Time Series Forecasting 2022 VLDB 6.3548172e-05
6,443 AutoCTS+: Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting 2023 SIGMOD 5.8775356e-05
11,402 LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation 2023 SIGMOD 5.093636e-05
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