Enabling predictable multi-region provisioning for fleets of spot instances
Enrique Molina-Giménez, Pedro Garcı́a-López, Javier Fabra · Journal of Cloud Computing Advances Systems and Applications · 2026
Abstract The major cloud providers offer their idle compute infrastructure through spot instances, discounted virtual machines that can be interrupted at any time. Although the range of spot instance types is broad, the possibilities expand even further due to factors such as variable discount rates, resource availability, and interruption probabilities, all of which vary by geographical region. In Amazon Web Services, spot-based applications, such as web services and batch processing, can take advantage of the EC2 Spot Service, which reduces operational complexity by providing mechanisms for fleet provisioning through allocation strategies. However, EC2 Spot Service for fleet provisioning has certain restrictions, which come with two key limitations: 1) the inability to query potential fleet prices without making actual reservations and 2) the restriction to a single predefined geographical region. This paper introduces a prediction-based approach for spot fleet provisioning based on monitoring across regions that preserves the capabilities of EC2 Spot Service while overcoming the mentioned constraints. Our solution removes the single-region restriction and predicts fleet prices before launch. We evaluate it on AWS across nine regions and two families of x86 instances, compute- and memory-optimized, for fleet sizes of up to 1,500 vCPUs. Our results show that this approach can exploit regional price differences of up to 80.5% for the same fleet, while maintaining prediction accuracy of 95.8% compared to the EC2 Spot Service. The architecture is designed to admit further instance families and cloud providers.