FAQs and Help

Frequently Asked Questions

1. Why would I use AWS instead of local servers or a traditional HPC cluster?

AWS provides on-demand computing, storage, analytics, and AI services that can scale up or down based on research needs. It is especially useful for projects with fluctuating compute requirements, large datasets, external collaborations, or grant-funded research that needs rapid deployment. Common CUIMC use cases include genomics, imaging analysis, machine learning, and burst HPC workloads.

A general rule is:

  • Use C2B2 HPC for traditional, sustained high-performance computing workloads that fit well within existing cluster resources.
  • Use AWS when you need rapid scaling, specialized cloud services, external collaboration, AI/ML platforms, disaster recovery, or temporary compute capacity that would exceed local resources.

2. How do I request an AWS account at CUIMC?

AWS accounts are provisioned through CUIMC Cloud IT and are managed within CUIMC's AWS environment. Researchers submit a request through the ServiceNow cloud services process, which helps ensure proper billing, security, and compliance controls are in place from the start.

3. Can I store HIPAA-protected or sensitive research data in AWS?

Yes, provided the environment is configured appropriately. CUIMC maintains a Business Associate Agreement (BAA) with AWS and operates AWS infrastructure designed for HIPAA-compliant workloads. Researchers must disclose planned use of PHI during account setup and follow applicable CUIMC security requirements. 

4. What AWS services are most commonly used by CUIMC researchers?

The most frequently used services include:

  • Amazon EC2 for virtual compute resources
  • Amazon S3 for scalable storage and archiving
  • AWS ParallelCluster for HPC workloads
  • Amazon SageMaker for machine learning and AI

These services support a broad range of biomedical and translational research workflows.

5. How are AWS costs billed and managed?

AWS operates on a pay-as-you-go model. CUIMC centrally manages billing and allocates charges to the chart string associated with the AWS account or project. CUIMC researchers may also benefit from institutional discounts and NIH STRIDES pricing programs where applicable.

6. Can AWS costs be included in grant proposals?

Yes. Cloud infrastructure costs are increasingly common in NIH and other sponsored research proposals. Research IT can assist investigators with estimating cloud expenses and incorporating those costs into grant budgets. AWS research credits may also be available for eligible projects.

7. Are AWS cloud credits available for my research project?

Possibly. Researchers may be eligible for AWS Cloud Credits for Research or other AWS-sponsored programs that support proof-of-concept studies, data analysis, cloud migration efforts, and development of research tools. Eligibility depends on the project and funding program requirements.

8. How do I move large datasets into or out of AWS?

Several options are available depending on the size and urgency of the transfer. Common approaches include AWS DataSync, Globus, direct network transfer, and AWS Snowball for very large datasets. Research IT can help determine the most efficient approach for your project.

9. Can AWS support AI and machine learning projects?

Yes. AWS offers a range of AI and ML services, including Amazon SageMaker and other managed AI platforms. Researchers commonly use these services for image analysis, biomarker discovery, predictive modeling, natural language processing, and other data-intensive research applications.

10. What support is available if I am new to AWS?

CUIMC Cloud and Research IT provide consultation, onboarding assistance, architecture guidance, training opportunities, cost optimization advice, and troubleshooting support. Researchers can engage cloud specialists early in their project planning process to help design secure and efficient environments.

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