Red Hat’s partnership with General Motors was announced in May 2022 to support GM’s Ultifi software platform with Red Hat’s in-vehicle operating system. The “edge to data center and back” idea describes a proposed way to distribute computing: a vehicle handles immediate work, nearby edge infrastructure can support some latency-sensitive tasks, and selected data can travel to centralized cloud or data-center systems for heavier processing. Updated software or machine-learning models can then move back toward vehicles. The sources establish an announced architecture and later Red Hat product milestones—not verified GM production deployment or measured savings.
What GM and Red Hat announced
On May 10, 2022, GM and Red Hat announced a collaboration to advance software-defined vehicles. Red Hat’s contribution was centered on its In-Vehicle Operating System, a Linux foundation intended to support GM’s Ultifi platform. The two products are distinct: Ultifi is GM’s vehicle software platform; Red Hat’s operating system is a software foundation intended to support it.
At the time, GM described Ultifi as separating application software from vehicle hardware and offering APIs for software development. The announcement envisioned over-the-air delivery of software-defined features, apps, and services, as well as access for authorized third-party developers subject to GM security, safety, and privacy requirements. Those were platform plans described in 2022, not confirmation of current availability. GM and Red Hat’s announcement said the integrated software was expected to support infotainment, advanced driver-assistance systems (ADAS), body control, and connectivity.
GM vice president of Software Defined Vehicle and Operating System Scott Miller said at the announcement: “General Motors is now a platform company and working with Red Hat is a critical element in advancing our Ultifi software development.”
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What “edge to data center and back” means
The phrase describes where different parts of a connected-car workload could run, rather than one continuous task that must always be online. In a May 16, 2022 interview, Red Hat executive Matt Hicks described vehicle data moving through edge locations toward more centralized public or private clouds. For example, a vehicle can act on locally collected data; selected data might be sent back for machine-learning model training; and a revised model could then be delivered toward the edge. Centralized infrastructure can also be relevant to vehicle software updates. Data Center Knowledge’s interview with Hicks presents this as an architecture discussion, not a report of a measured GM deployment.
| Compute location | Role in the proposed flow | Key consideration |
|---|---|---|
| Vehicle | Runs software close to vehicle systems and can act on locally available data. | Immediate operation must not depend on a cloud connection; safety-critical functions need applicable safety assurance. |
| Nearby network edge | Can provide computing closer to the vehicle than a distant centralized facility for selected workloads. | Latency and network coverage matter. Hicks cited 5–10 ms as a possible 5G latency range in this context; it was an interview-era estimate, not a measured GM result. |
| Centralized public or private cloud/data center | Can support heavier tasks such as model training and coordination of software updates. | Data must be transmitted, and the task can be affected by connectivity gaps or delays. |
| Return path to vehicles or edge | Updated models or software can be delivered outward after centralized work. | Delivery does not itself establish that an update is suitable for every vehicle or safety function. |
Hicks also described Red Hat’s automotive operating system as a pared-down version of its RHEL server distribution, with the interview reporting a reduction from about 4,000 packages to about 200. Those are figures in the 2022 article, not a current package-count specification. Hicks summarized the broader shift this way: “The merger of physical machines and software is happening right now, and the ability to innovate across traditional boundaries is critical.”
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Why split work across the vehicle, edge, and cloud?
Keep immediate work close to the vehicle
A function that must respond promptly cannot sensibly rely on a long trip to a distant data center and back. Local processing also matters when network service is unavailable. The 2022 interview raised low-latency use and rural connectivity gaps as design concerns; it did not specify which GM functions would run at each location.
Use centralized resources for heavier work
Training or improving machine-learning models can require processing beyond what is practical to do in an individual vehicle. The proposed pattern is to send selected information for that work and return an updated model. The sources do not identify specific data fields, retention rules, or the exact workloads GM would centralize.
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Treat safety as a separate requirement
Infotainment and connectivity were among the announced application areas, alongside ADAS and body control. These functions do not all carry the same safety consequences. The 2022 announcement described functional safety as a development goal, but the presence of a software platform or cloud connection alone does not certify an individual application or vehicle system.
What the collaboration was intended to improve
GM and Red Hat said the integrated software was expected to promote software reuse and consolidation, faster development cycles, continuous functional-safety certification, and potential new services or revenue streams. These were announced aims, not published results. The release quoted SBD Automotive’s Alex Oyler saying “nearly half” of automakers’ software-development costs were dedicated to maintenance and triage; that is an attributed industry estimate, not a GM-specific measure, and the release did not provide the underlying study.
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The available cited sources do not establish GM-specific cost reductions, faster development measured in production, the number of deployed vehicles, customer adoption, or production update frequency. They should not be inferred from the collaboration announcement.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What later Red Hat updates establish—and what they do not
- May 24, 2023: Red Hat executive Francis Chow said Red Hat and GM were continuing to develop next-generation platforms for GM software-defined vehicles and methods for functionally safe platforms and applications. This is Red Hat’s account of ongoing work, not independent evidence of deployment.
- May 20, 2025: Red Hat announced that its In-Vehicle Operating System had achieved ISO 26262 Edition 2:2018 ASIL-B Safety Element out-of-Context (SEooC) certification, with full release slated for Q3 2025. This is a Red Hat product milestone. It does not show that GM deployed the operating system in production, or that every GM vehicle, subsystem, or application is certified. See Red Hat’s certification announcement.
Red Hat also described a broader automotive partner ecosystem in 2025, and it announced a separate software-defined vehicle collaboration with Deloitte in 2024. Neither item establishes Deloitte’s participation in the GM agreement or makes every ecosystem partner part of GM’s platform work.
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What readers should take away
The partnership is best understood as an infrastructure and software-foundation story: GM’s Ultifi platform and Red Hat’s in-vehicle Linux were intended to support software-defined vehicles, while the edge/cloud concept explains how some processing could be distributed beyond the car. The architecture is plausible as a design pattern, but the available sources do not demonstrate that the proposed flow became a production GM system or quantify its benefits.
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