June 10, 2026
Most large research universities are essentially running two separate IT organizations. Research computing serves the scientific mission, HPC clusters, genomics pipelines, federal compliance requirements. Administrative IT serves the institutional mission, student systems, financial operations, HR platforms. Two teams, two vendor ecosystems, two security frameworks, two budgets.
For a long time, this felt like a reasonable way to organize things. Research computing has specialized needs. Administrative IT has different ones. Keep them separate and each team can focus on what they know.
That logic is getting expensive, and the compliance pressure now bearing down on research computing is making it urgent.
Running parallel stacks is costing more than anyone has measured
Two infrastructure ecosystems running side by side, each managing the same fundamental problems, containerized workloads, security controls, audit logging, access management, just doing it separately with their own tools, vendors, and teams.
The inefficiency compounds with every new cloud service adopted on either side, and the total cost never appears in a single line item, which is why it persists. When universities actually measure it, the per-seat infrastructure cost of running parallel stacks is significant, typically 35 to 50 percent more than a consolidated approach would require.
Here’s what’s possible instead: one platform that handles FERPA controls for student data and NIST 800-171 controls for federal research workloads. Both missions, one runtime. Research computing and administrative IT sharing infrastructure, and, sharing costs instead of duplicating them.
NSF and DoD are enforcing NIST 800-171 compliance for research involving Controlled Unclassified Information.
Most university IT environments weren’t designed to document 110 security controls across a hybrid cloud research infrastructure. The result is a compliance gap that’s either sitting in the last assessment or hasn’t been assessed at all. Either way, the risk is real, and the institutions caught unprepared aren’t small schools with limited resources. They’re major research universities that treated federal grant compliance as a research administration problem instead of an infrastructure one.
When the controls are built into the platform, when the runtime for research workloads maps directly to NIST 800-171 and CMMC Level 2, and the data fabric handles CUI access without requiring researchers to change their workflows, compliance becomes continuous rather than a per-grant documentation exercise. Universities that have done this have completed NIST 800-171 assessments without adding compliance staff, and without slowing down active research programs.
Researchers shouldn’t wait weeks to access their own data
A researcher needs data for a grant proposal; they submit a request. Weeks later, IT provisions the dataset. The proposal deadline has moved. The preliminary data that would have strengthened the application arrived too late to matter.
This can happen at research universities, and it is quietly costing institutions grant competitiveness in ways that are hard to quantify but easy to observe: proposals that go out without the best supporting data, publications that follow competitors, funding renewals that miss the window.
It’s not a staffing problem; it’s a data architecture problem. When researchers can access datasets, clinical trial data, and institutional analytics through a single interface, without a provisioning ticket, without waiting on IT, the dynamic changes completely. The three-week wait becomes same-day access and the proposal goes out with the best data. The preliminary analysis that should have been done last month actually gets done.
research data provisioning when architecture replaces ticketing
The research universities gaining ground on grant competitiveness aren’t the ones with the
largest IT budgets. They’re the ones that stopped making researchers wait on infrastructure.
