Resource allocation in distributed environments remains a key challenge. In this study, we analyze VM scheduling and placement in the SAP cloud platform, the infrastructure behind the world’s largest enterprise resource planning provider. Using observability data from approximately 1,800 hypervisors and 48,000 VMs over a 30-day period, we identify inefficiencies in workload management. Unlike existing datasets, our dataset provides fine-grained time series of fully virtualized, enterprise-grade workloads, including long-running, memory-intensive SAP HANA instances as well as general-purpose VMs.