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CEP-Based SLO Evaluation

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Advances in Service-Oriented and Cloud Computing (ESOCC 2017)

Abstract

Modern service-based applications (SBAs) operate in highly dynamic environments where both underlying resources and the application demand can be constantly changing which external SBA components might fail. Thus, they need to be rapidly modified to address such changes. Such a rapid updating should be performed across multiple levels to better deal, in an orchestrated and globally-consistent manner, with the current problematic situation. First of all, this means that a fast and scalable event generation and detection mechanism should exist to rapidly trigger the adaptation workflow to be performed. Such a mechanism needs to handle all kinds of events occurring at different abstraction levels and to compose them so as to detect more advanced situations. To this end, this paper introduces a new complex event processing framework able to realise the respective features mentioned (processing speed, scalability) and have the flexibility to capture and sense any kind of event or event combination occurring in the SBA system. Such a framework is wrapped in the form of a REST service enabling to manage the event patterns that need to be rapidly detected. It is also well connected to other main components of the SBA management system, via a publish-subscribe mechanism, including monitoring and the adaptation engines.

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Notes

  1. 1.

    www.cloudsocket.eu.

  2. 2.

    http://www.espertech.com/esper/.

  3. 3.

    https://paasage.ercim.eu/.

  4. 4.

    zeromq.org.

  5. 5.

    https://eclipse.org/cdo/.

  6. 6.

    http://jersey.github.io/.

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Acknowledgments

This work is supported by CloudSocket project that has been funded within the European Commission’s H2020 Program under contract number 644690.

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Correspondence to Chrysostomos Zeginis .

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Kritikos, K., Zeginis, C., Paravoliasis, A., Plexousakis, D. (2018). CEP-Based SLO Evaluation. In: Mann, Z., Stolz, V. (eds) Advances in Service-Oriented and Cloud Computing. ESOCC 2017. Communications in Computer and Information Science, vol 824. Springer, Cham. https://doi.org/10.1007/978-3-319-79090-9_2

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  • DOI: https://doi.org/10.1007/978-3-319-79090-9_2

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  • Online ISBN: 978-3-319-79090-9

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