CoMe4ACloud: An End-to-End Framework for Autonomic Cloud Systems

Zakarea Al-Shara 1, 2 Frederico Alvares 3 Hugo Bruneliere 2, 4 Jonathan Lejeune 5 Charles Prud 'Homme 6, 2 Thomas Ledoux 2, 1
1 STACK - Software Stack for Massively Geo-Distributed Infrastructures
Inria Rennes – Bretagne Atlantique , LS2N - Laboratoire des Sciences du Numérique de Nantes
4 NaoMod - NaoMod - Nantes Software Modeling Group
LS2N - Laboratoire des Sciences du Numérique de Nantes
5 DELYS - DistributEd aLgorithms and sYStems
LIP6 - Laboratoire d'Informatique de Paris 6, Inria de Paris
6 TASC - Théorie, Algorithmes et Systèmes en Contraintes
LS2N - Laboratoire des Sciences du Numérique de Nantes
Abstract : Autonomic Computing has largely contributed to the development of self-manageable Cloud services. It notably allows freeing Cloud administrators of the burden of manually managing varying-demand services, while still enforcing Service-Level Agreements (SLAs). All Cloud artifacts, regardless of the layer carrying them, share many common characteristics. Thus, it should be possible to specify, (re)configure and monitor any XaaS (Anything-as-a-Service) layer in an homogeneous way. To this end, the CoMe4ACloud approach proposes a generic model-based architecture for autonomic management of Cloud systems. We derive a generic unique Autono-mic Manager (AM) capable of managing any Cloud service, regardless of the layer. This AM is based on a constraint solver which aims at finding the optimal configuration for the modeled XaaS, i.e. the best balance between costs and revenues while meeting the constraints established by the SLA. We evaluate our approach in two different ways. Firstly, we analyze qualitatively the impact of the AM behaviour on the system configuration when a given series of events occurs. We show that the AM takes decisions in less than 10 seconds for several hundred nodes simulating vir-tual/physical machines. Secondly, we demonstrate the feasibility of the integration with real Cloud systems, such as Openstack, while still remaining generic. Finally, we discuss our approach according to the current state-of-the-art.
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Contributeur : Hugo Bruneliere <>
Soumis le : mardi 10 avril 2018 - 13:38:31
Dernière modification le : samedi 23 juin 2018 - 01:20:02

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Zakarea Al-Shara, Frederico Alvares, Hugo Bruneliere, Jonathan Lejeune, Charles Prud 'Homme, et al.. CoMe4ACloud: An End-to-End Framework for Autonomic Cloud Systems. Future Generation Computer Systems, Elsevier, In press, pp.1-37. 〈https://www.sciencedirect.com/science/article/pii/S0167739X17320605〉. 〈10.1016/j.future.2018.03.039〉. 〈hal-01762716〉

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