Skip to main content

OpenStack Cyborg

OpenStack Cyborg is an OpenStack service for lifecycle management and orchestration of hardware accelerators (infrastructure orchestration) such as GPUs, FPGAs, and other offload devices in cloud environments.

  • Management and orchestration of accelerator devices across an OpenStack cloud (infrastructure orchestration).
  • Discovery, inventory, and tracking of accelerator resources on compute hosts (infrastructure asset management).
  • Provisioning, allocation, and attachment of accelerators to virtual machines and workloads (resource scheduling and binding).
  • API-driven control plane for integrating accelerators into OpenStack services and workflows (cloud infrastructure Application Programming Interface (API)).
  • Plugin and driver model for different accelerator types and vendors (hardware integration framework).

More About OpenStack Cyborg

OpenStack Cyborg is an official OpenStack service focused on hardware accelerator management (infrastructure orchestration) within OpenStack-based clouds. It addresses the problem of discovering, organizing, and controlling heterogeneous accelerator resources such as GPUs, FPGAs, and other specialized devices so that they can be requested and consumed by workloads in a consistent way across an OpenStack deployment.

At its core, Cyborg provides a centralized service for discovery and inventory of accelerators (infrastructure asset management). It gathers information about accelerator devices attached to compute nodes, maintains metadata about their capabilities, and exposes this information through APIs. This enables operators and higher-level OpenStack services to understand which accelerator resources are available, where they reside, and how they can be allocated.

Cyborg exposes Representational State Transfer (REST) APIs (cloud infrastructure API) that allow other OpenStack components and external tooling to interact with accelerator resources. These APIs cover operations such as listing devices, querying properties, creating accelerator resources, and binding them to instances. Through these API interactions, accelerators can be associated with virtual machines and workloads managed by OpenStack, aligning accelerator lifecycle with compute lifecycle.

The project uses an extensible driver and plugin model (hardware integration framework) to support multiple accelerator technologies and vendors. Device-specific drivers handle low-level interactions with GPUs, FPGAs, and similar devices, while Cyborg presents a unified abstraction to the rest of the cloud platform. This design allows operators to integrate new accelerator types into an OpenStack environment while retaining a consistent control plane and API surface.

In enterprise and institutional environments, Cyborg is used in deployments where workloads depend on hardware offload capabilities, including data processing, Artificial Intelligence (AI) and Machine Learning (ML), and High performance computing (HPC) scenarios (infrastructure for accelerated computing). By integrating with the broader OpenStack ecosystem, Cyborg aligns accelerator allocation with existing scheduling, quota, and governance mechanisms, enabling operators to treat accelerators as first-class cloud resources alongside compute, storage, and networking.

From a directory and taxonomy perspective, OpenStack Cyborg fits within cloud infrastructure and virtualization management, specifically as an accelerator resource management and orchestration service for OpenStack-based private and public clouds. It targets technical stakeholders responsible for cloud platform engineering, infrastructure operations, and hardware lifecycle management where heterogeneous compute resources need a unified management layer.