Towards Cross-layer Monitoring of Cloud Workflows

Eric Kübler, Mirjam Minor

2015

Abstract

Prospective cloud management requires sophisticated monitoring capabilities. In this paper, we introduce a novel monitoring framework for cloud-based workflow systems called cWorkload. cWorkload integrates monitoring information from different layers of the cloud architecture. The paper puts its focus on the two-layer monitoring regarding the workflow layer and the PaaS layer. We present the layered monitoring architecture, an implementation of the two-layer cross-monitoring part, and an experimental evaluation with sample workflow data. Further, we discuss related work on cloud monitoring divided into one-layer, multi-layer, and cross-layer approaches. Our plans for future work on extending the implementation by further layers towards a cross-layer, prospective monitoring for prospective cloud management are described.

References

  1. Aceto, G., Botta, A., de Donato, W., and Pescap, A. (2013). Cloud monitoring: A survey. Computer Networks, 57(9):2093-2115.
  2. Alcaraz Calero, J. and Gutierrez Aguado, J. (2014). MonPaaS: An adaptive monitoring platform as a service for cloud computing infrastructures and services. IEEE Trans. on Services Computing, 8(1):65-78.
  3. Alhamazani, K., Ranjan, R., Mitra, K., Jayaraman, P., Huang, Z., Wang, L., and Rabhi, F. (2014). CLAMS: Cross-layer Multi-cloud Application Monitoring-asa-Service Framework. In 2014 IEEE Int. Conference on Services Computing (SCC), pages 283-290.
  4. Amazon (2014a). Amazon http://aws.amazon.com/, 12-19-14.
  5. Amazon (2014b). Cloudwatch. http://aws.amazon.com/ cloudwatch/, 12-18-14.
  6. Beloglazov, A., Abawajy, J., and Buyya, R. (2012). Energyaware resource allocation heuristics for efficient management of data centers for cloud computing. Future Generation Computer Systems, 28(5).
  7. ca technologies (2014). Nimsoft. http://www.ca.com/us/ opscenter/ca-unified-infrastructuremanagement.aspx, 12-11-14.
  8. Eucalyptus Systems (2014). https://www.eucalyptus.com/, 12-19-14.
  9. Grosskopf, A., Decker, G., and Weske, M. (2009). The Process: Business Process Modeling Using BPMN. Meghan Kiffer Pr.
  10. GroundWork (2014). http://www.gwos.com/features/, 12- 19-14.
  11. Hu, J., Gu, J., Sun, G., and Zhao, T. (2010). A scheduling strategy on load balancing of virtual machine resources in cloud computing environment. In 2010 Third Int. Symposium on Parallel Architectures, Algorithms and Programming (PAAP), pages 89-96.
  12. I.B.M. Corporation (2006). An architectural blueprint for autonomic computing. http://www03.ibm.com/autonomic/pdfs/AC Blueprint White Paper V7.pdf, 11-01-14.
  13. Kung, H. T., Lin, C.-K., and Vlah, D. (2011). CloudSense: continuous fine-grain cloud monitoring with compressive sensing. USENIX Hot-Cloud.
  14. LogicMonitor (2014). http://www.logicmonitor.com/, 12- 19-14.
  15. Manjrasoft (2014). Aneka. http://www.manjrasoft.com/, 12-18-14.
  16. Maurer, M., Brandic, I., and Sakellariou, R. (2013). Adaptive resource configuration for cloud infrastructure management. Future Generation Computer Systems, 29(2):472-487.
  17. Minor, M. and Schulte-Zurhausen, E. (2014). Towards process-oriented cloud management with case-based reasoning. In Proc. ICCBR 2014, LNCS 8766, pages 303 - 312. Springer.
  18. monitis (2014). http://www.monitis.com/, 12-19-14.
  19. Montes, J., Sánchez, A., Memishi, B., Pérez, M. S., and Antoniu, G. (2013). Gmone: A complete approach to cloud monitoring. Future Generation Computer Systems, 29(8):2026 - 2040.
  20. Nagios (2014). http://www.nagios.org/, 12-19-14.
  21. OpenNebula (2014). http://docs.opennebula.org/, 12-19-14.
  22. Palmieri, R., di Sanzo, P., Quaglia, F., Romano, P., Peluso, S., and Didona, D. (2012). Integrated monitoring of infrastructures and applications in cloud environments. In Euro-Par 2011, pages 45-53. Springer.
  23. Paraleap Technologies (2014). Azurewatch. http://www.paraleap.com/azurewatch, 12-19-14.
  24. Pousty, S. and Miller, K. (2014). Getting Started with OpenShift. ”O'Reilly Media, Inc.”.
  25. rackspace (2014). Cloudkick. http://www.rackspace.com/ cloud/monitoring/, 12-15-14.
  26. redhat (2014a). jbpm. http://www.jbpm.org/, 11-26-14.
  27. redhat (2014b). WildFly. http://www.wildfly.org/, 12-18- 14.
  28. Richter, M. M. and Weber, R. (2013). Case-Based Reasoning: A Textbook. Springer.
  29. Schulte-Zurhausen, E. and Minor, M. (2014). Task placement in a cloud with case based reasoning. In CLOSER 2014, pages 323 - 328, Barcelona, Spain. SciTePress.
  30. Singh, M. P. and Huhns, M. N. (2005). Service-oriented computing - semantics, processes, agents. Wiley.
  31. Unix Top (2014). http://www.unixtop.org/, 12-18-14.
  32. vmware (2014). http://www.vmware.com/products/ vrealize-hyperic/, 12-19-14.
  33. Workflow Management Coalition (1999). Glossary & terminology. 5-23-14.
Download


Paper Citation


in Harvard Style

Kübler E. and Minor M. (2015). Towards Cross-layer Monitoring of Cloud Workflows . In Proceedings of the 5th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-758-104-5, pages 389-396. DOI: 10.5220/0005434703890396


in Bibtex Style

@conference{closer15,
author={Eric Kübler and Mirjam Minor},
title={Towards Cross-layer Monitoring of Cloud Workflows},
booktitle={Proceedings of the 5th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2015},
pages={389-396},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005434703890396},
isbn={978-989-758-104-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - Towards Cross-layer Monitoring of Cloud Workflows
SN - 978-989-758-104-5
AU - Kübler E.
AU - Minor M.
PY - 2015
SP - 389
EP - 396
DO - 10.5220/0005434703890396