Abstract
Given the complexity of contemporary applications, the varying goals and intents of their owners, and the availability of resources with fundamentally different characteristics and capabilities, the optimal deployment and execution of applications and their internal components is a rather challenging subject in the Cloud Continuum era. This includes the selection and the configuration of the resources to adequately cover the set technological and business requirements and constraints from the side of both application owners and resource providers. The aforementioned process is often and to a great extent, done manually and hence not optimally, with direct impact to the execution of an application and the usage or the available resources. In this work, we present the approach followed for the design and development of a Service Orchestrator equipped with AI techniques and the underlying multi-layered abstraction model enabling its functionality. These components were incorporated in a platform for infrastructure-agnostic deployment of data-intensive applications and tested in real-life scenarios.
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Notes
- 1.
OASIS TOSCA, https://www.oasis-open.org/committees/tosca/.
- 2.
O. N. Foundation, CORD platform, https://opennetworking.org/cord/.
- 3.
ETSI-hosted, Open Source MANO software stack, https://osm.etsi.org/.
- 4.
OpenAirInterface (OAI), https://openairinterface.org/.
- 5.
OpenWDL, Open Workflow Description Language (WDL), https://openwdl.org/.
- 6.
Prometheus, https://prometheus.io/.
- 7.
Kubernetes, https://kubernetes.io/.
- 8.
Kubernetes YAML Generator, https://k8syaml.com/.
- 9.
Alien 4 Cloud, https://alien4cloud.github.io/index.html.
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Acknowledgement
This work has been supported by the SERRANO EU project and partially funded by the EU’s Horizon 2020 research and innovation programme under grant agreement 101017168. This paper expresses the opinions of the authors and not necessarily those of the European Commission. The European Commission is not liable for any use that may be made of the information contained in this paper.
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Chondrogiannis, E. et al. (2023). Intent-Based AI-Enhanced Service Orchestration for Application Deployment and Execution in the Cloud Continuum. In: Papadopoulos, G.A., Rademacher, F., Soldani, J. (eds) Service-Oriented and Cloud Computing. ESOCC 2023. Lecture Notes in Computer Science, vol 14183. Springer, Cham. https://doi.org/10.1007/978-3-031-46235-1_17
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