Seven lessons learned: Driving AWS Cloud adoption in research at Saint Louis University

Sometimes you need to pause and reflect to appreciate progress. For Shruthi Murthy, assistant director of the Research Computing Group (RCG) at Saint Louis University (SLU), a single phone call in Fall 2019 sparked what would become a comprehensive cloud transformation for the university’s research infrastructure. What began as a request to run a proof-of-concept notebook in HAQM Web Services (AWS) for a research project within the Department of Biochemistry and Molecular Biology at SLU has evolved into a robust cloud-based infrastructure supporting over $60 million in research grants across biomedicine, economics, computer science, engineering, and environmental science.

This five-year journey has transformed how SLU researchers approach computational challenges, while offering valuable lessons for other institutions looking to enhance their research capabilities through cloud computing.

The cloud journey begins

The initial project—building a proof-of-concept notebook running a Reinforcement Learning model—opened doors for SLU’s Research Information Technology (IT) team. Engaging with their AWS account team enabled exploration of how best to approach the project. Their conversations revealed opportunities beyond this single project, leading to the migration of SLU’s mission-critical Research Electronic Data Capture (REDCap) application to the cloud.

Initially deployed on-premises in 2007, their REDCap instance was eight versions out of date and less secure than desired. By moving REDCap to AWS, the team could:

Run the system in a secure environment
Enable single sign-on (SSO) through Okta
Enjoy a high-availability environment with less than 5 minutes of downtime per year
Continuously monitor the system with security checks (using AWS Web Application Firewall (WAF), AWS Security Hub, and HAQM GuardDuty)
Employ routine backups

Today the team’s AWS-hosted REDCap instance serves more than 600 surveys and 10,000 survey-takers per year.

This successful migration built the team’s cloud skills, earned researchers’ trust and established a strong partnership with AWS—setting the stage for broader cloud adoption.

Key strategies for driving cloud adoption in research

SLU’s journey from supporting a single researcher to enabling a university-wide cloud-powered research ecosystem didn’t happen overnight. Here are seven key strategies that helped drive this transformation:

1) Prioritize high-impact projects

Start with cloud initiatives that solve critical researcher pain points, ensuring immediate and visible returns on investment (ROI). The REDCap migration exemplifies this approach—by moving an outdated, on-premises system to AWS, SLU delivered long-awaited security, accessibility, and functionality improvements. This transition provided hundreds of researchers with seamless SSO access, modernized features, and enhanced automation.

“The move to the cloud has enabled us to properly secure REDCap and update it to the latest version, unlocking powerful features like External Modules and automated workflows,” said Irene Ryan, Data Manager at the AHEAD Institute at SLU.

2) Engage research leadership early

Building strong relationships with research lab leaders and principal investigators (PIs) is key to accelerating cloud adoption. Their buy-in encourages broader institutional support and innovation. SLU’s approach integrated security, cost controls, and observability tools from the outset, creating a framework that researchers could trust and replicate across projects.

3) Leverage AWS expertise for acceleration

Partnering with AWS provided SLU with technical expertise, cost-optimization strategies, and funding opportunities that helped scale research projects efficiently. Working with AWS specialists allowed researchers to streamline workflows and reduce processing time, significantly enhancing research outcomes.

“Thanks to the collaboration between SLU’s Research Computing Group and AWS, my work on the human virome project progressed smoothly. Running experiments in AWS was faster and more efficient,” remarked Dr. Xiaofeng Fan, associate professor in the Division of Gastroenterology & Hepatology at the SLU Liver Center.

4) Make cloud resources easily accessible

To encourage adoption, researchers need clear entry points to cloud-based resources. SLU participates in Research Resources Week, a university-wide event where research support teams—including research computing, grants, and patents offices—offer workshops, consulting sessions, and hands-on training to help researchers kickstart their cloud journey.

“RCG’s presentations during Research Resources Week helped researchers across SLU’s St. Louis and Madrid campuses understand available cloud resources and how to integrate them into their work,” noted Joe Lampe, program coordinator in the Office of the Vice President for Research at SLU.

5) Provide hands-on training to bridge the skills gap

Cloud adoption isn’t just about infrastructure—it requires upskilling researchers to take full advantage of cloud tools. SLU hosts Artificial Intelligence (AI) and Machine Learning (ML) Immersion Days, Data Analytics Bootcamps, and gamified “Jam” sessions where AWS experts and SLU’s research computing group offers interactive training to help researchers apply cloud technologies to real-world problems.

6) Foster a cloud community of practice

Expanding cloud adoption beyond SLU, the Research Computing Group has organized multi-institutional workshops involving researchers and IT professionals from neighboring universities. These sessions have helped create a broader cloud community in the St. Louis region, encouraging interdisciplinary collaboration and scalable research practices.

7) Communicate through familiar channels

To keep researchers informed, SLU distributes a biweekly newsletter highlighting new cloud tools, consulting opportunities, and training events. Additionally, Science Showcase sessions feature researcher success stories, demonstrating real-world impact and inspiring more faculty to explore cloud-based research.

Scaling research innovation with cloud

SLU’s cloud journey is far from over. The Research Computing Group continues to expand cloud capabilities, empowering researchers with cutting-edge technologies that accelerate discovery and collaboration. Looking ahead, SLU is focusing on:

AI-driven research infrastructure: Integrating AI and ML tools into cloud workflows to enable faster data processing, predictive analytics, and real-time insights for biomedical, environmental, and computational studies.

Secure research enclaves (SRE) for collaboration: Establishing federated, secure cloud-based research environments that allow SLU researchers to securely collaborate with peers at other institutions while meeting strict compliance and data privacy standards.

Optimized cost management and sustainability: Implementing automated cost controls and intelligent scaling strategies—so that cloud resources can remain accessible and cost-efficient while minimizing environmental impact.

By continuously innovating and refining cloud strategies, SLU is not just modernizing research infrastructure, it is also shaping the future of data-driven discovery.

SLU continues to expand its cloud research capabilities and help researchers on their cloud journeys by unlocking new opportunities to push the boundaries of knowledge. Organizations that apply the lessons highlighted in this post will accelerate their own research initiatives and cloud journeys, ultimately advancing the pace and impact of scientific discovery.

Contact your AWS representative today to schedule a consultation and begin your cloud journey and drive adoption among researchers.

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