Work

Challenges in VM Scheduling and Placement: Insights from a Real-World SAP Cloud Dataset

Year: 2025

Type: conference-paper

Abstract: 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.

DOI: 10.1145/3744969.3748437

Authors: Arno Uhlig, Iris Braun, Matthias Wählisch

Institution: Technische Universität Dresden

Language: English

Topic: Cloud Computing and Resource Management

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Funders: European Commission, Bundesministerium für Wirtschaft und Energie, NextGenerationEU

Award: Open Reference Architecture

OpenAlex ID: W4414109948

FWCI:

Cites: 8

Cited by:

Related to: 10