Recent improvements in hardware and software have enabled a paradigm shift in satellite computing, moving from purpose-built satellites running a single application to platforms capable of executing and even receiving new workloads on orbit. This evolution has allowed image processing to migrate from ground stations to single- or multi-node satellite clusters, with only processed results transmitted, significantly reducing end-to-end latency. This paper proposes ORCHIDE, an orchestration solution built on cloud-native technologies such as Kubernetes and Argo, purpose built for space edge computing. A key capability of ORCHIDE is its support for unikernels—minimal, single-application virtual machines—alongside containers. Compared to traditional containerized deployments, unikernels substantially reduce CPU and memory footprint, achieve short boot times, and produce smaller binary images. ORCHIDE further enables unikernel workloads to leverage heterogeneous accelerator hardware, including FPGAs, through a dedicated accelerator management library. We describe the system architecture, the scheduling model, and the minimum target hardware required for deployment. Three clusters of varying topology were used to evaluate ORCHIDE, demonstrating that it operates effectively on both single- and multi-node heterogeneous configurations. Preliminary results show the ORCHIDE platform being able to run in heterogeneous and single-node environments with as low as 4 cores and 8 GB of memory, offering potential users the flexibility to compose satellite hardware to best match their mission requirements.
Weisz et al. (Tue,) studied this question.