CAMCEADHUB (CASU-IRIS) is CamCEAD's cloud-based scientific analysis platform for CASU users, giving researchers on-demand computational resources and streamlined access to data without needing to manage their own infrastructure.

CAMCEADHUB platform welcome screen

What CAMCEADHUB provides

Built on cloud principles, CAMCEADHUB gives scientists a self-service dashboard for launching and managing their own compute environments, running data-processing pipelines, and tracking jobs — all backed by dedicated storage and compute infrastructure.

On-demand compute resourcesJupyter, RStudio & VS Code environmentsRemote desktop accessS3-compatible data storage
CAMCEADHUB user access model
How users reach CAMCEADHUB's interactive environments, notebooks and storage, running across a Kubernetes cluster on IRIS.

Key features

  • Interactive environments — JupyterLab notebooks, RStudio, Visual Studio Code and full remote desktop sessions, launched on request.
  • Flexible server sizes — choose from Default, Medium or Large server instances (with optional GPU acceleration) sized to the task at hand.
  • Pipelines & batch jobs — submit and monitor long-running data-processing jobs from the dashboard.
  • Data access — S3-compatible storage and remote data access for moving data in and out of the platform.
CAMCEADHUB server selection screen
Choosing a server size — Default, Medium or Large — before launching an environment.
CAMCEADHUB user JupyterLab instance
A running user instance, with Python, RStudio, VS Code and desktop environments available from the launcher.

Hosted on IRIS

Unlike CamCEAD's other cloud platforms, CAMCEADHUB runs on IRIS — the UK's e-Infrastructure for Research and Innovation for STFC — rather than on CamCEAD's own hardware. For the 2026 allocation, the platform has access to 1,980 VCPUs, alongside dedicated GPUs, several terabytes of RAM and multiple petabytes of storage, distributed across a Kubernetes cluster of master and compute nodes.

Getting started

Access is by registration and administrator approval. Once logged in, the dashboard shows a summary of storage usage, running Jupyter servers and job status, with links to every part of the platform.