Scaling Teaching Across Computational Subjects at University of Zurich
One course environment, not 145 individual setups
Every student works in the same browser-based environment, reducing setup and support overhead.
Compute matched to each course’s needs
Courses can move between lighter compute, T4, A10-class and H100 resources without rebuilding the teaching environment.
Controlled resource use, and predictable as cohorts grow
Per-student limits and automatic shutdown keep GPU-backed teaching governed at cohort scale.
Reproducibility without platform dependence
Course environments are captured as Snapshots, immutable, versioned records of code, dependencies and configuration together, and can be exported as Docker images for full portability. The environment remains portable instead of becoming inseparable from the infrastructure on which the course ran.
DEPLOYMENT OVERVIEW
During the 2025–2026 deployment, University of Zurich courses ran on a combination of the Nuvolos sovereign EU bare-metal fabric, dedicated EU-hosted compute and storage, and Nuvolos-managed standby GPU capacity (currently hosted on Microsoft Azure). Nuvolos provided the governed workspace across these resources, giving teaching teams consistent, reproducible environments while compute could be matched to the requirements of each course.
For additional capacity, Nuvolos-managed standby accelerators provide guaranteed capacity at scheduled times. The same governed workspace can extend to SWITCH Cloud Compute and, in beta, to multi-cloud capacity through OCRE (Open Clouds for Research Environments).
"Six courses, cohorts from 11 to 145 students, very different compute requirements, one environment and one resource-management model covered all of it. We evaluated the alternatives and chose to continue with Nuvolos."
The Unbroken Line of Science
Nuvolos keeps the line of science unbroken from first data to a re-runnable Snapshot, in one governed workspace.
WHAT CHANGED FOR TEACHING
A reusable workflow for teaching computational subjects
01.
One course environment, not 145 individual setups
Nuvolos gives every student the same browser-based course environment, defined once by the teaching team. Instead of troubleshooting individual machines, instructors maintain one reproducible reference setup.
02.
Compute tailored to each course
Courses can move between lighter compute, T4, A10-class and H100 resources without rebuilding the teaching environment. Instructors can design exercises around the computational task rather than around the hardware available on student devices.
03.
Controlled and predictable resource use, as cohorts grow
Per-student credit quotas, Resource Pool wallets and automatic shutdown of inactive sessions allow GPU-backed teaching to remain governed at cohort level. Intensive workloads can be enabled without leaving resource use open-ended.
04.
Reproducibility without platform dependence
Course environments are captured as Snapshots, immutable, versioned records of code, dependencies and configuration together, and can be exported as Docker images for full portability. The environment remains portable instead of becoming inseparable from the infrastructure on which the course ran.
One governed workspace across institution-controlled and elastic compute
The University of Zurich deployment demonstrates the separation between the governed workspace and the underlying infrastructure. During 2025–2026, teaching workloads ran on the Nuvolos sovereign EU bare-metal fabric and Nuvolos-managed standby GPU capacity (currently Azure-hosted). Nuvolos kept the user workspace and course environments consistent across those resources.
DEPLOYMENT ARCHITECTURE
01.
One workspace, flexible infrastructure
Nuvolos separates the governed workspace from the underlying infrastructure. Institutions retain infrastructure choice and control over where workloads run, while course environments remain reproducible and portable across infrastructure.
02.
Elastic accelerators and supplementary capacity
Nuvolos-managed standby GPUs provide guaranteed capacity at scheduled times, such as weekly course sessions, rather than relying on GPU availability in an institution’s own cloud account.. Beyond the sovereign core, workloads can burst to SWITCH Cloud Compute, the OpenStack-managed fabric of the Swiss national research and education network — live today — or, in beta, to Azure, AWS, GCP and Alibaba Cloud in an institution's own tenancy via the OCRE framework (Open Clouds for Research Environments). Institutional agreements include a pooled Burst Allowance covering orchestration of CPU workloads on bring-your-own capacity. These options integrate without changing the Nuvolos workspace model.
03.
Resource governance
Compute can be allocated through course, and user-level controls. Per-student credit quotas, Resource Pool wallets, fractional GPU sizes and automatic shutdown of inactive sessions provide mechanisms for governing expensive accelerators at cohort scale. GPU Slicing adds up to eight isolated workloads per physical device with a provider-independent control plane. Because every run is captured in an immutable Snapshot, this governance doubles as an unbroken, re-runnable record.
04.
Reproducibility and Versioning
Course environments are captured as Snapshots, immutable records of the full software stack used for teaching, and can be exported as Docker images. Data egress from the Nuvolos sovereign core is free of charge. For academics, this supports reproducibility. For IT, it provides portability and an explicit exit path.
05.
How Nuvolos works with existing infrastructure
Nuvolos is a governed workspace that can complement existing institutional compute rather than requiring every course to create a separate infrastructure service. The same workspace model can span institution-controlled resources, customer cloud tenancies and managed standby capacity as requirements change.
