Demonstration of the OPTIMIS Toolkit for Cloud Service Provisioning

Badía, Rosa M.; Compagnucci, Marcelo Corrales; Dimitrakos, Theo; Djemame, Karim; Elmroth, Erik; Ferrer, Ana Juan; Forgó, Nikolaus; Guitart, Jordi; Hernández, F.; Hudzia, Benoît; Kipp, Alexander; Konstanteli, Kleopatra; Kousiouris, George; Nair, Srijith K.; Sharif, Tabassum; Sheridan, Craig; Sirvent, Raül; Tordsson, Johan; Varvarigou, Theodora; Wesner, Stefan; Ziegler, Wolfgang; Zsigri, Csilla

doi:10.1007/978-3-642-24755-2_40

Cited by 4 publications

(2 citation statements)

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“…The risk assessment approach using Cost and PoF has been applied in the context of the EU Framework 7 project OPTIMIS (Badia et al, 2011). The Cost impacts were added to the Risk Assessment process via the Risk Inventory.…”

Section: Discussionmentioning

confidence: 99%

Cost and Risk Aware Support for Cloud SLAs

Jiang

Kirkham

Byrne

et al. 2013

Proceedings of the 3rd International Conference on Cloud Computing and Services Science

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Automated control of Cloud Service Level Agreements (SLA) is typically focused on Quality of Service (QoS) management and monitoring of the Cloud Infrastructure in-line with the SLA. Using risk assessments to bridge the needs of the Service Provider and Infrastructure Provider is one way in which the management of the whole Cloud SLA life-cycle can be achieved automatically. In this paper we adapt the QoS based risk approach and combine it with business orientated goal monitoring to improve the business input into the management of SLA from both a Cloud IP and SP perspective. We demonstrate this approach using probability of failure QoS risk linked to economic modelling of cost from the business goals of a SP.

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Section: Discussionmentioning

confidence: 99%

Cost and Risk Aware Support for Cloud SLAs

Jiang

Kirkham

Byrne

et al. 2013

Proceedings of the 3rd International Conference on Cloud Computing and Services Science

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“…OPTIMUS is a toolset presented in [35]. It facilitates the implementation of both cloud federation and multi-cloud.…”

Section: B Federated Cloud Approachesmentioning

confidence: 99%

FEDARGOS-V1: A Monitoring Architecture for Federated Cloud Computing Infrastructures

et al. 2022

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resources. Specifically, monitoring provides the means of knowing the status and availability of the physical resources and services within the cloud infrastructure. This results in making ''monitoring of resources'' one of the key aspects of the cloud resource management taxonomy. However, managing the resources in a secure and scalable manner is not easy, particularly when considering a federated cloud environment. A federated cloud is used and shared by many multi-cloud tenants and at various cloud software stack levels. As a result, there is a need to reconcile all the tenants' diverse monitoring requirements. To cover all aspects relating to the monitoring of resources in a federated cloud environment, we present the FEDerated Architecture for Resource manaGement and mOnitoring in cloudS Version 1.0 (FEDARGOS-V1), a cloud resource monitoring architecture for federated cloud infrastructures. The architecture focuses mainly on the ability to access information while monitoring services for early identification of resource constraints within short time intervals in federated cloud platforms. The monitoring architecture was deployed in a real-time OpenStack-based FEDerated GENomic (FEDGEN) cloud testbed. We present experimental results in order to evaluate our design and compare it both qualitatively and quantitatively to a number of existing Cloud monitoring systems that are similar to ours. The architecture provided here can be deployed in private or public federated cloud infrastructures for faster and more scalable resource monitoring.

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