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Axe: A Novel Approach for Generic, Flexible, and Comprehensive Monitoring and Adaptation of Cross-Cloud Applications

  • Jörg Domaschka
  • Daniel Seybold
  • Frank Griesinger
  • Daniel Baur
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 567)

Abstract

The vendor lock-in has been a major problem since cloud computing has evolved as on the one hand side hinders a quick transition between cloud providers and at the other hand side hinders an application deployment over various clouds at the same time (cross-cloud deployment). While the rise of cross-cloud deployment tools has to some extend limited the impact of vendor lock-in and given more freedom to operators, the fact that applications now are spread out over more than one cloud platform tremendously complicates matters: Either the operator has to interact with the interfaces of various cloud providers or he has to apply custom management tools. This is particularly true when it comes to the task of auto-scaling an application and adapting it to load changes. This paper introduces a novel approach to monitoring and adaptation management that is able to flexibly gather various monitoring data from virtual machines distributed across cloud providers, to dynamically aggregate the data in the cheapest possible manner, and finally, to evaluate the processed data in order to adapt the application according to user-defined rules.

Keywords

Virtual Machine Network Traffic Cloud Provider Component Instance Home Domain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement number 317715 (PaaSage) and from the European Community’s Framework Programme for Research and Innovation HORIZON 2020 (ICT-07-2014) under grant agreement number 644690 (CloudSocket).

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Jörg Domaschka
    • 1
  • Daniel Seybold
    • 1
  • Frank Griesinger
    • 1
  • Daniel Baur
    • 1
  1. 1.Institute of Information Resource ManagementUniversity of UlmUlmGermany

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