🎉 Paper Accepted at SBBD 2026! 🎉

🎉 Paper Accepted at SBBD 2026! 🎉

We are happy to share that our paper, "Personalized Service Level Agreements for Machine Learning Training using k-Skyband Queries", has been accepted at SBBD 2026 (Brazilian Symposium on Databases).

Training Machine Learning models in cloud environments involves important trade-offs between execution time, financial cost, energy consumption, and carbon emissions. Choosing the right infrastructure and resource configuration is often challenging, especially for large-scale ML workloads.

In this paper, we introduce an approach that extends the concept of Personalized Service Level Agreements (PSLAs) to Machine Learning training workflows.

By using provenance data and k-Skyband queries, our method automatically identifies resource configurations that represent different trade-offs between performance, cost, and sustainability, helping users make more informed decisions before launching training jobs.

This research was conducted as part of Gustavo Alexandre PhD at the Federal Fluminense University (UFF), within the UFFeScience Research Group. Gustavo is advised by Prof. Daniel de Oliveira and Prof. Yuri Frota. We also thank Prof. Marcos Bedo for his valuable collaboration and contributions to the paper.

Looking forward to presenting our results at SBBD 2026 and discussing future directions for sustainable and data-driven Machine Learning infrastructure management.

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