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Introduction

Both Big Data analytics and Cloud Computing are in growing rapidly. We are observing a widespread adoption of solutions utilizing and combining these frameworks. One key field that the power of Big Data Analytics can be immensely beneficial for Cloud Computing is operational analytics. Cloud Computing enables deployments at scale that can adapt to changing demands.  Agile methods use these capabilities to build application and services that rapidly adapt to changing business conditions. With continuous integration and delivery, a cloud environment is very dynamic with changes at many levels. In such an environment, it is necessary to ensure the components and services are configured correctly and securely; the cloud is in a highly available, reliable and secure state; and the services in the cloud are functioning at their optimum levels. Massive amounts of data generated by an ever-increasing number of monitors for components in the IT stack need to be aggregated, analyzed, understood and responsive actions taken in real-time.

Even newer methods of ensuring availability, reliability and security through both manual and automated testing/configuration are being challenged with increase in scale and speed.  Agility demands that developers iterate in a fast pace and identify, diagnose, and, fix problems quickly and correctly. There has been extensive research and development to derive insights from operational data, for example, intelligent resource and security data collection, anomaly and performance variation detection, root cause analysis, configuration analysis, efficient cloud resource utilization, security/vulnerability analysis, etc. This workshop is an effort to bring practitioners together for sharing and validating ideas and finding new approaches for deriving insights from operational data.

Call for paper

Important date

2016-10-12
Draft paper submission deadline
2016-11-15
Final paper submission deadline

Submission Topics

Research Topics

  • Uses of Big Data analytics in cloud operations management

  • IT operation analytics

  • Data-driven cloud configuration analytics

  • Capturing, Filtering and Representing cloud operational data

  • Tools/ frameworks/ services for operational analytics in cloud

  • Learning/mining techniques for cloud operational analytics

  • Analytics feedback for continuous integration/deployment

  • Experiences/Challenges/Best Practices monitoring cloud deployments

  • Real time data collection and real time analytics in cloud operational management

  • Cost analysis of cloud operational monitoring and analytics

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Important Date
  • Conference Date

    Dec 05

    2016

    to

    Dec 08

    2016

  • Oct 12 2016

    Draft paper submission deadline

  • Nov 15 2016

    Final Paper Deadline

  • Dec 08 2016

    Registration deadline