CloudBank is a service-based platform that enables access to commercial cloud resources. It offers two modalities: Research and Classroom. CloudBank Research provides a flexible, multi-cloud infrastructure. Supported cloud platforms include:
- Amazon Web Services (AWS)
- Google Cloud
- IBM Cloud
- Microsoft Azure
U.S.-based researchers can request access to CloudBank through the ACCESS program. Follow the steps below to begin.
Request access to CloudBank Research through ACCESS
Use one or more of the supported cloud providers’ cost calculators to estimate your expenses. These estimates will serve as your initial cloud selection. You can add additional cloud accounts from any supported provider at any time.
List of CloudBank supported clouds and cloud calculator URLs
View Cost Estimate Best Practices
Need help getting started? Watch our Cloud 101 videos to learn more about commercial cloud resources.
Questions about estimating costs? Email us at help@cloudbank.org for assistance.
Create an ACCESS account and submit a request for cloud funding. Allocation types and available funding amounts are listed below:
| ACCESS Allocation Type | Dollars Available |
|---|---|
| Explore | Up to $10,000 per year |
| Discover | Up to $37,500 per year |
| Accelerate or Maximize | Up to $75,000 per year |
For detailed instructions on creating an ACCESS account, choosing a project type, and submitting your request, visit:
ACCESS: Get Your First Project
Once your ACCESS allocation is approved, you'll need to exchange your credits for CloudBank dollars.
In your exchange request, include your estimated cloud usage based on the calculators you used in Step 1.
For step-by-step instructions on completing the exchange, visit:
ACCESS: How to Exchange Credits
After your exchange is approved, you’ll receive an automated email with onboarding instructions. If you do not receive the email within 24 hours, please check your spam or junk folder. If it's not there, notify help@cloudbank.org. Log into the CloudBank portal using your ACCESS-CI credentials.
As part of onboarding, you’ll need to:
- Review the onboarding materials
- Electronically sign to confirm you’ve reviewed the materials
- Specify a monthly budget for your cloud usage
- List any existing cloud accounts you'd like to import into CloudBank in the notes section. Let us know whether these accounts are part of an organization/payer or are currently billed to a credit card. We’ll follow up with further instructions after reviewing your submission.
CloudBank will review your onboarding information and follow up with any questions. Once approved, your allocation will be activated and your cloud accounts will be created.
Need help logging in?
How to Log into the CloudBank Portal
Managing your project involves tasks in both the ACCESS portal and the CloudBank portal. ACCESS handles project membership and allocation settings, while CloudBank manages cloud account permissions, account access, and detailed cost reporting.
User Management and Other ACCESS Allocation Tasks
Users are centrally managed through the ACCESS portal. PIs, co-PIs, and Allocation Managers can add team members to their ACCESS project to share resources.
For instructions on managing users and other allocation tasks, visit:
ACCESS: How To Manage Your Project
CloudBank Account Management
While users are added via ACCESS, permissions for which users can access specific cloud accounts must be configured in the CloudBank portal.
For instructions on managing account permissions and other CloudBank-specific tasks, visit:
CloudBank User Guide
Commercial clouds supported by CloudBank
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
Google 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.
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.
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.
