Cloud Resources Management Support
Past New Requirement Updated
- Agency
-
Centers for Medicare and Medicaid Services
Department of Health and Human Services
- Solicitation expected
- Estimated value
- $13,000,000 to $20,000,000
- Set-aside
- No set-aside
Forecast facts
- Anticipated award
- NAICS code
- 541513 Computer Facilities Management Services
- Points of contact
-
- Ben Stidham benjamin.stidham1@cms.hhs.gov
- Shawn Hunter shawn.hunter@cms.hhs.gov
Forecast details come from HHS's procurement forecast. Agencies' dates and values are estimates.
About this forecast
The Centers for Medicare and Medicaid Services (CMS) is forecasting a new requirement for cloud resources management support for the Marketplace Information Technology Group's cloud computing portfolio. The contract will focus on managing Application Development Organizations' cloud resource requests, securing resources, monitoring utilization, and ensuring optimal cloud resource allocation with future demand prediction. The estimated solicitation release is scheduled for July 1, 2025, with an anticipated contract award date of October 1, 2025.
This opportunity falls under the Computer Facilities Management Services NAICS code 541513 and does not have a specific set-aside designation. Key points of contact for this procurement are Ben Stidham (benjamin.stidham1@cms.hhs.gov) and Shawn Hunter (shawn.hunter@cms.hhs.gov), both from the Centers for Medicare & Medicaid Services. While specific award values and detailed performance location were not provided in the forecast, the contract appears to be focused on comprehensive cloud resource management and support for the agency's technology infrastructure.
Forecast text
The purpose is to provide cloud resources management support for the Marketplace Information Technology Group's cloud computing portfolio and related functions. Manage MITG's Application Development Organizations (ADOs') requests for cloud resources, participate in the process of securing the requested cloud resources, monitor the utilization of cloud resources, and ensure optimal use of allocated cloud resources as well as predicting future demand.
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