XeXes

XeXes is a modular, open-source software framework designed to coordinate the execution of tasks across heterogeneous computing environments, including cloud, edge, and on-premises resources. The project emphasizes portability, scalability, and security, enabling developers to deploy workflows that span multiple backends without reimplementing logic for each platform.

XeXes was introduced in 2017 by a collective of researchers and developers affiliated with the TechLabs Consortium. The first public release followed in 2019, with ongoing community-driven development and governance. The project is released under a permissive license to encourage integration with third-party tools.

Its architecture centers on a lightweight core that provides scheduling and orchestration, plus pluggable backends for compute, storage, and networking. Core components include a task scheduler, an executor layer that runs tasks on target environments (containers, virtual machines, or bare metal), and a data manager that tracks lineage and locality. Adapters enable integration with cloud providers, Kubernetes clusters, HPC schedulers, and edge gateways.

XeXes supports distributed scheduling, dynamic resource estimation, fault tolerance through task retries and checkpointing, and policy-based governance for access control and quality of service. It offers APIs in multiple languages and a command-line interface for operators.

Common use cases include data processing pipelines, real-time analytics, scientific simulations, AI model training workflows, and orchestration of microservices across edge devices. By decoupling workflow logic from compute infrastructure, XeXes aims to improve resource utilization and reduce deployment friction.

Development is community-led with a steering council elected by contributors. The project uses an open development model, with transparent issue tracking and periodic releases. While adopted in research and some industry contexts, users note trade-offs in configuration complexity and the need for robust security configurations in multi-tenant environments. Related projects include Kubernetes, Apache Airflow, and Dask.