Towards multi-tenant and interoperable monitoring of virtual machines in cloud

The advent of Cloud Computing introduced new challenges in various computer science fields and disciplines, monitoring being one of them. Due to the multi-tenant nature of Cloud environment, its size and use of massive virtualization, the current monitoring solutions are approaching their limits. Unlike some other approaches, focusing on data integration, aggregation, and abstraction, our work focuses on a virtual machine representing the primary source of monitoring information. In this paper, we propose requirements for the producer of monitoring information addressing existing issues related to monitoring data representation, storage, processing and distribution. As a proof-of-concept, conforming to these requirements, prototype of event-based monitoring daemon is presented in detail. The resulting solution allows multiple users to consume monitoring information in an extensible data format without impairing interoperability.

[1]  Jin Shao,et al.  A Runtime Model Based Monitoring Approach for Cloud , 2010, 2010 IEEE 3rd International Conference on Cloud Computing.

[2]  Huamin Yang,et al.  Analysis of the Efficiency of Data Transmission Format Based on Ajax Applications , 2011, 2011 International Conference of Information Technology, Computer Engineering and Management Sciences.

[3]  José A. B. Fortes,et al.  Sky Computing , 2009, IEEE Internet Computing.

[4]  Dana Petcu,et al.  Portable Cloud applications - From theory to practice , 2013, Future Gener. Comput. Syst..

[5]  P. Mell,et al.  The NIST Definition of Cloud Computing , 2011 .

[6]  Jon Stearley,et al.  Bridging the Gaps: Joining Information Sources with Splunk , 2010, SLAML.

[7]  Rizos Sakellariou,et al.  A taxonomy of grid monitoring systems , 2005, Future Gener. Comput. Syst..

[8]  Bernd Grobauer,et al.  Towards incident handling in the cloud: challenges and approaches , 2010, CCSW '10.

[9]  Marcos K. Aguilera,et al.  Matching events in a content-based subscription system , 1999, PODC '99.

[10]  Evangelos E. Milios,et al.  Storage and retrieval of system log events using a structured schema based on message type transformation , 2011, SAC '11.

[11]  Bu-Sung Lee,et al.  Towards Achieving Accountability, Auditability and Trust in Cloud Computing , 2011, ACC.

[12]  Carlos Rodrigues,et al.  Mobile Application Webservice Performance Analysis: Restful Services with JSON and XML , 2011, CENTERIS.

[13]  David E. Culler,et al.  The ganglia distributed monitoring system: design, implementation, and experience , 2004, Parallel Comput..

[14]  PetcuDana,et al.  Portable Cloud applications-From theory to practice , 2013 .

[15]  Nico d'Heureuse,et al.  Towards holistic multi-tenant monitoring for virtual data centers , 2010, 2010 IEEE/IFIP Network Operations and Management Symposium Workshops.

[16]  Ruth A. Aydt,et al.  A Grid Monitoring Architecture , 2002 .

[17]  Jonathan M. Spring,et al.  Monitoring Cloud Computing by Layer, Part 2 , 2011, IEEE Security & Privacy.

[18]  Konrad Slind,et al.  Monitoring distributed systems , 1987, TOCS.

[19]  Mladen A. Vouk,et al.  Abstracting log lines to log event types for mining software system logs , 2010, 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010).

[20]  Lionel Brunie,et al.  Evaluating the Robustness of Publish/Subscribe Systems , 2011, 2011 International Conference on P2P, Parallel, Grid, Cloud and Internet Computing.

[21]  Yong Zhao,et al.  Cloud Computing and Grid Computing 360-Degree Compared , 2008, GCE 2008.

[22]  Jonathan M. Spring,et al.  Monitoring Cloud Computing by Layer, Part 1 , 2011, IEEE Security & Privacy.

[23]  Salvatore Venticinque,et al.  Architecturing a Sky Computing Platform , 2010, ServiceWave Workshops.