CloudFormer: An Attention-based Performance Prediction for Public Clouds with Unknown Workload

ArXi:2509.03394v2 Announce Type: replace-cross Cloud platforms are increasingly relied upon to host diverse, resource-intensive workloads due to their scalability, flexibility, and cost-efficiency. In multi-tenant cloud environments, virtual machines are consolidated on shared physical servers to improve resource utilization. While virtualization guarantees resource partitioning for CPU, memory, and storage, it cannot ensure performance isolation.