Guardado en:
| Autores principales: | , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2512.09917 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866915666771050496 |
|---|---|
| author | Jaikar, A. Diamond, J. Tiradani, A. Harrison, B. |
| author_facet | Jaikar, A. Diamond, J. Tiradani, A. Harrison, B. |
| contents | As particle accelerator control systems evolve in complexity and scale, the need for responsive, scalable, and cost-effective computational infrastructure becomes increasingly critical. Function-as-a-Service (FaaS) offers an alternative to traditional monolithic architecture by enabling event-driven execution, automatic scaling, and fine-grained resource utilization. This paper explores the applicability and performance of FaaS frameworks in the context of a modern particle accelerator control system, with the objective of evaluating their suitability for short lived and triggered workloads. In this paper, we evaluate prominent open-source FaaS platforms in executing functional logic, triggers, and diagnostics routines. Evaluation metrics consist of cold-start latency, scalability, performance, integration with other open-source tools like Kafka. Experimental workloads were designed to simulate real-world control tasks when implemented as stateless FaaS functions. These workloads were benchmarked under various invocation loads and network conditions. Self-hosted FaaS platforms, when deployed within accelerator networks, offer greater control over execution environment, better integration with legacy systems, and support for real-time guarantees when paired with message queues. Based on lessons learned and evaluation metrics, this paper describes reliability of the FaaS framework for the Accelerator Control Systems (ACS). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_09917 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Evaluating Function-as-a-Service (FaaS) frameworks for the Accelerator Control System Jaikar, A. Diamond, J. Tiradani, A. Harrison, B. Accelerator Physics As particle accelerator control systems evolve in complexity and scale, the need for responsive, scalable, and cost-effective computational infrastructure becomes increasingly critical. Function-as-a-Service (FaaS) offers an alternative to traditional monolithic architecture by enabling event-driven execution, automatic scaling, and fine-grained resource utilization. This paper explores the applicability and performance of FaaS frameworks in the context of a modern particle accelerator control system, with the objective of evaluating their suitability for short lived and triggered workloads. In this paper, we evaluate prominent open-source FaaS platforms in executing functional logic, triggers, and diagnostics routines. Evaluation metrics consist of cold-start latency, scalability, performance, integration with other open-source tools like Kafka. Experimental workloads were designed to simulate real-world control tasks when implemented as stateless FaaS functions. These workloads were benchmarked under various invocation loads and network conditions. Self-hosted FaaS platforms, when deployed within accelerator networks, offer greater control over execution environment, better integration with legacy systems, and support for real-time guarantees when paired with message queues. Based on lessons learned and evaluation metrics, this paper describes reliability of the FaaS framework for the Accelerator Control Systems (ACS). |
| title | Evaluating Function-as-a-Service (FaaS) frameworks for the Accelerator Control System |
| topic | Accelerator Physics |
| url | https://arxiv.org/abs/2512.09917 |