XaaS - Everything as a Service, pl. Kubernetes alapú adatcsatorna optimalizálása (XaaS - Everything as a Service, i.e. optimizing Kubernetes based data pipeline)
Ipari partner: Robert Bosch Ltd
Profile an extensive, already existing Kubernetes-based data pipeline from memory consumption and runtime perspective in order to define break-even points between using functions (e.g. Azure Functions, Azure Logic App) instead of using a dockerized environment on Kubernetes. As a bases for this investigation, the Kubernetes based (Argo workflow) data pipeline enables data-driven development in Advanced Driver-Assistance System (ADAS) development, involving generative AI, Neural Networks, vector database, metadata-database and many more.
Required skills:
- Python
- Kubernetes
- Docker
- Azure Function, Azure Logic Apps (optional)
Profile an extensive, already existing Kubernetes-based data pipeline from memory consumption and runtime perspective in order to define break-even points between using functions (e.g. Azure Functions, Azure Logic App) instead of using a dockerized environment on Kubernetes. As a bases for this investigation, the Kubernetes based (Argo workflow) data pipeline enables data-driven development in Advanced Driver-Assistance System (ADAS) development, involving generative AI, Neural Networks, vector database, metadata-database and many more.
Required skills:
- Python
- Kubernetes
- Docker
- Azure Function, Azure Logic Apps (optional)
Kulcsszavak: cloud, Azure Functions, data engineering, XaaS, scalable systems, Kubernetes, data pipeline, ADAS
Department of Telecommunications and Articicial Intelligence (TMIT) Budapest University of Technology and Economics (BME) H-1117, Budapest, Magyar tudósok krt. 2, HUNGARY tel: +36 (1) 463-2448; fax: +36 (1) 463-3107 email: titkarsag@tmit.bme.hu