Description

CloudBank Classroom is a cloud-hosted, small-scale JupyterHub designed for teaching, built on an open-source interactive computing stack (Python, R, JupyterLab, and related libraries). It provides each learner with a modest allocation of persistent storage, memory, and CPUs as well as seamless authentication through their university’s identity management system, allowing them to log in with existing campus credentials. The environment comes preconfigured with widely used data science tools, enabling students to run code, analyze data, and complete assignments directly in the browser without local setup. Instructors can easily distribute materials, manage assignments, and support learners through integrated tools like nbgitpuller and grading extensions. By removing technical barriers, ensuring equity of access, and offering a consistent, reproducible workflow, the JupyterHub lowers the cost of teaching with data while remaining scalable to support classes of varying sizes. GPUs are expected to be available in the platform by fall 2026.

Resource ID
3739
Global Resource ID
cloudbank-classroom.access-ci.org
Resource Type
Compute
Latest Status
production
Latest Status Begin
Project Affiliation
ACCESS
Organization Name
CloudBank
Organization URL
https://www.cloudbank.org
Organization Logo URL
https://cider.access-ci.org/public/resource_providers/962/logo
Raw Data URL
https://operations-api.access-ci.org/wh2/cider/v1/cider_resource_id/3739/
RP Description

CloudBank Classroom is a cloud-hosted JupyterHub for teaching. Students work in the browser with persistent storage and pre-installed tools, including JupyterLab, RStudio, and VSCode, with support for Python, R, and C++. Instructors can load assignments into student environments via nbgitpuller and use grading extensions such as Otter Grader. Available to U.S.-based educators through an Explore ACCESS allocation. See the CloudBank Classroom website for more information. 

Each cloud provider offers comprehensive online user documentation for their particular system resources and services. 

Support Links
CloudBank Classroom User Guide
CloudBank Catalog of Resource Capabilitites
Educational Resource
MFA Required
On
File Transfer Text

Each cloud provider offers comprehensive online user documentation for their particular system resources and services. Learn more about different  and their capabilities in the CloudBank Catalog.

Storage Text

All CloudBank service providers offer their own set of internal and external storage. View the CloudBank Catalog for more information.

Jobs Information

CloudBank does not have job queues in the traditional sense, instead it provides users with free credits they can use on any of the following cloud resources.

Amazon Web Services:
AWS enables researchers to analyze massive data pipelines, store petabytes of data, and advance research with transformative technologies collaboratively and securely. Researchers can access HPC and AI/ML optimized compute across over 900 generally available instances with Amazon EC2, high performance storage services designed for AI/ML and simulation, end to end model training and deployment with Amazon SageMaker Unified Studio, quantum computers and circuit simulators with Amazon Braket, and foundation models from leading AI companies to build and scale generative AI applications and agents with Amazon Bedrock.

Google Cloud:
Cloud is uniquely positioned to empower researchers tackling complex, data-intensive projects. Its full-stack AI infrastructure, including advanced Gemini models, is optimized for performance, offering elastic compute resources like GPUs and TPUs. Researchers benefit from BigQuery for fast, serverless analytics, Cloud Storage for scalable object storage, and Vertex AI for building and deploying machine learning models. This comprehensive environment, further supported by Cloud Functions for event-driven computing and Google Quantum AI for cutting-edge research, is purpose-built to accelerate scientific discovery.

IBM Cloud:
IBM Cloud emphasizes hybrid cloud solutions and quantum computing, appealing to researchers in fields like cryptography, materials science, and complex systems modeling. It offers IBM Cloud Object Storage for reliable data archiving, IBM Watson Studio for collaborative data science workflows, IBM Cloud Functions for serverless task execution, Red Hat OpenShift on IBM Cloud for managing containerized applications, and IBM Quantum for open access to quantum systems and tools for algorithm development.

Microsoft Azure:
Microsoft Azure delivers a versatile cloud platform with strengths in data management, scalable computing, integrated analytics, and AI for science offerings. For data storage, researchers can use Blob Storage and Data Lake for secure, scalable storage of large datasets. Integrated analytics offerings include Synapse or Stream Analytics, Databricks, and Data Lake Analytics for big-data workloads. AI offerings include the AI Foundry model catalog, OpenAI Service, and AI Search for intelligent retrieval. Researchers can also benefit from agentic AI for Science offerings including multi-agent orchestration via AI Foundry, libraries like AutoGen for complex R&D workflows, and the Microsoft Discovery platform for scientific workflow automation for literature mining, hypothesis generation, and simulation. Together, these offerings accelerate research with secure, scalable, and AI-driven solutions.


Oracle Cloud Infrastructure (estimated 2026):
Oracle Cloud Infrastructure (OCI) for Research Computing provides high-performance, scalable, and cost-effective cloud solutions tailored to the needs of academic, scientific, and industrial research. OCI supports compute-intensive workloads with powerful bare metal and GPU instances, high-throughput networking, and flexible storage options, making it ideal for simulations, data analysis, AI/ML training, and genomics. Researchers benefit from secure, compliant infrastructure, open standards, and integration with popular open-source tools.