Supporting operations, developers, researchers, and teachers alike

Accelerated development with self-service

 Self-service tools built into Red Hat OpenShift means developers no longer need to wait for the IT unit to manually provision and configure VMs according to each project’s needs. Developers and researchers are a lot less dependent on IT and can get moving with their projects sooner on the application platform, and the IT unit has more time available to support projects in other ways

“We can create a namespace in Red Hat OpenShift in a few minutes. They can then install their collecting application, and they are good to go,” said Schenström, highlighting how the marine biology department can now create research vessels. “Previously, we would set up a VM, configure it according to the project’s needs, talk with the networking people, and set the ports for communicating with all the sensors—and that would have taken a few days, a week, or even more.”

The namespaces integrate with the university’s Active Directory for credentials and roles. Once they are created, developers can deploy whatever applications they need in any environment. Future plans include using Red Hat OpenShift to provide more self-service so developers can create namespaces themselves

Onboarded developers and students in minutes 

The university has also recently started using OpenShift Dev Spaces, a collaborative Kubernetesnative solution for rapid application development. OpenShift Dev Spaces delivers consistent developer environments on Red Hat OpenShift, allowing anyone with a browser to contribute code in under 2 minutes. 

“OpenShift Dev Spaces allows us to onboard developers within minutes,” said Schenström. “We like how it provides developers—whether in our IT unit or more widely across individual departments—with a consistent, secure, and zero-configuration development environment.”

Allowed VMs and containers to run side-by-side 

The trusted environment Schenström and his team are building for sensitive research projects uses OpenShift Virtualization to allow VMs to run alongside containers on the same platform, simplifying management and improving time to production.

“We use OpenShift Virtualization to run Windows infrastructure—the Active Directory Controllers and remote updates, for instance—on VMs in Red Hat OpenShift,” said Schenström. “We then deploy a virtual Windows server with remote desktop services to create an isolated bubble for each research team.”

Provided a multiuser solution for teaching 

The university has a lot of projects using the Jupyter Notebook. The School of Business, Economics, and Law has been using the multiuser version (JupyterHub) to support 3 courses with up to 160 students each since 2021.

“JupyterHub allows a smaller number of teachers to teach and support a greater number of students. We can easily enter students’ servers to help and support,” said Mari Paananen, Associate Professor at the University of Gothenburg.

JupyterHub means students do not need to install software on their computers, which can cause installation problems and waste around 20% of the allocated teaching time. “It levels the playing field among students, as they all have access to the same processing power, regardless of the capacity of their own computer, and provides students with instant access to the same data from a shared folder,” said Paananen.

Expanding data science use cases with hybrid cloud

The University of Gothenburg is expanding use cases for the Red Hat application platform, including for data science projects. “We have users who want to use graphics processing units (GPUs) for AI, ML, and, in the future, high-performance computing (HPC) projects,” said Schenström, explaining how projects buying physical servers with dedicated GPUs and then IT managing those servers is not resource effective. “We would like to provide a data science platform based on Red Hat OpenShift with shared access to GPU and CPU resources. We are looking at hybrid cloud for those compute-heavy applications,” said Schenström. “The auto-scaling provided by public cloud environments will help us manage costs.”

The University of Gothenburg uses Open Data Hub, an open source AI platform designed for the hybrid cloud, to provide their data scientists with a Jupyter-as-a-service collaborative environment for use cases like a chatbot for Alzheimer’s research. They are also considering OpenShift AI, Red Hat’s commercial product based on Open Data Hub, which provides a flexible, scalable MLOps platform that gives teams the tools they need to build, deploy, and manage AI-enabled applications.

Plans for the future include containerizing legacy applications, including internally developed Windows applications. “We can now modernize our legacy Windows applications and get rid of some of our legacy physical servers,” said Schenström. OpenShift Virtualization makes containerizing .NET applications straightforward. Windows developers write their applications as they normally would, but instead of deploying onto a Windows server, they deploy to Red Hat OpenShift.

“Red Hat OpenShift is critical to our future success,” said Kindstrand. “It frees up our IT unit, allows projects to progress faster, and we can onboard new developers fast. We are excited about containerizing our .NET applications and expanding our Red Hat OpenShift use cases to include AI, ML, and HPC projects.”