Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
166 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
42 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Automated Probe Life-Cycle Management for Monitoring-as-a-Service (2309.11870v1)

Published 21 Sep 2023 in cs.DC, cs.SY, and eess.SY

Abstract: Cloud services must be continuously monitored to guarantee that misbehaviors can be timely revealed, compensated, and fixed. While simple applications can be easily monitored and controlled, monitoring non-trivial cloud systems with dynamic behavior requires the operators to be able to rapidly adapt the set of collected indicators. Although the currently available monitoring frameworks are equipped with a rich set of probes to virtually collect any indicator, they do not provide the automation capabilities required to quickly and easily change (i.e., deploy and undeploy) the probes used to monitor a target system. Indeed, changing the collected indicators beyond standard platform-level indicators can be an error-prone and expensive process, which often requires manual intervention. This paper presents a Monitoring-as-a-Service framework that provides the capability to automatically deploy and undeploy arbitrary probes based on a user-provided set of indicators to be collected. The life-cycle of the probes is fully governed by the framework, including the detection and resolution of the erroneous states at deployment time. The framework can be used jointly with existing monitoring technologies, without requiring the adoption of a specific probing technology. We experimented our framework with cloud systems based on containers and virtual machines, obtaining evidence of the efficiency and effectiveness of the proposed solution.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (35)
  1. hostingtribunal.com. (2020) 25 must-know cloud computing statistics in 2020. https://hostingtribunal.com/blog/cloud-computing-statistics/. [Online; accessed 28-April-2021].
  2. A. J. Ferrer, J. M. Marquès, and J. Jorba, “Towards the decentralised cloud: Survey on approaches and challenges for mobile, ad hoc, and edge computing,” ACM Computing Surveys, vol. 51, no. 6, 2019.
  3. L. Romano, D. D. Mari, Z. Jerzak, and C. Fetzer, “A Novel Approach to QoS Monitoring in the Cloud,” in 2011 First International Conference on Data Compression, Communications and Processing, Jun. 2011, pp. 45–51.
  4. P. Cedillo, J. Jimenez-Gomez, S. Abrahao, and E. Insfran, “Towards a Monitoring Middleware for Cloud Services,” in 2015 IEEE International Conference on Services Computing, 2015, pp. 451–458.
  5. A. Shatnawi, M. Orrú, M. Mobilio, O. Riganelli, and L. Mariani, “CloudHealth: A Model-Driven Approach to Watch the Health of Cloud Services,” in Proceedings of the 1st International Workshop on Software Health (SoHeal 2018).   ACM/IEEE, 2018, pp. 40–47.
  6. C. Wang, K. Schwan, V. Talwar, G. Eisenhauer, L. Hu, and M. Wolf, “A Flexible Architecture Integrating Monitoring and Analytics for Managing Large-scale Data Centers,” in Proceedings of the 8th ACM International Conference on Autonomic Computing, ser. ICAC ’11.   ACM, 2011, pp. 141–150.
  7. M. Kutare, K. Schwan, G. Eisenhauer, V. Talwar, C. Wang, and M. Wolf, “Monalytics: online monitoring and analytics for managing large scale data centers,” in In ICAC ’10: Proceeding of the 7th international conference on Autonomic computing.   ACM, 2010, pp. 141–150.
  8. The Linux Foundation. (2021) Kubernetes. [Online; accessed 26-April-2022]. [Online]. Available: https://kubernetes.io/
  9. Elasticsearch BV. (2021) The Elastic Stack. https://www.elastic.co/elastic-stack. [Online; accessed 26-April-2022].
  10. The Linux Foundation. (2021) Prometheus. https://prometheus.io/. [Online; accessed 26-April-2022].
  11. Red Hat, Inc. (2021) How Ansible Works. https://www.ansible.com/overview/how-ansible-works. [Online; accessed 26-April-2022].
  12. Puppet. (2021) Puppet. https://puppet.com. [Online; accessed 26-April-2022].
  13. D. Trihinas, G. Pallis, and M. D. Dikaiakos, “Jcatascopia: Monitoring elastically adaptive applications in the cloud,” in 2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing.   IEEE, 2014, pp. 226–235.
  14. Hewlett-Packard Enterprise Development LP. (2021) Monasca - an OpenStack Community project. https://monasca.io/. [Online; accessed 26-April-2022].
  15. K. Fatema, V. C. Emeakaroha, P. D. Healy, J. P. Morrison, and T. Lynn, “A survey of cloud monitoring tools: Taxonomy, capabilities and objectives,” Journal of Parallel and Distributed Computing, vol. 74, no. 10, pp. 2918 – 2933, 2014. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S0743731514001099
  16. G. Aceto, A. Botta, W. de Donato, and A. Pescapè, “Cloud monitoring: A survey,” Computer Networks, vol. 57, no. 9, pp. 2093–2115, 2013.
  17. A. Tundo, M. Mobilio, M. Orrù, O. Riganelli, M. Guzmàn, and L. Mariani, “Varys: An agnostic model-driven monitoring-as-a-service framework for the cloud,” in Proceedings of the 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), tool demo, 2019.
  18. B. Burns and D. Oppenheimer, “Design patterns for container-based distributed systems,” in Proceedings of the 8th USENIX Conference on Hot Topics in Cloud Computing.   USENIX Association, 2016, pp. 108–113.
  19. The Apache Software Foundation. (2021) Apache Kafka. https://kafka.apache.org/. [Online; accessed 26-April-2022].
  20. MongoDB, Inc. (2021) MongoDB. https://www.mongodb.com/. [Online; accessed 26-April-2022].
  21. Salvatore Sanfilippo and contributors. (2021) Redis.io. https://redis.io/. [Online; accessed 26-April-2022].
  22. Elasticsearch BV. (2021) Beats: Data Shippers for Elasticsearch. https://www.elastic.co/beats/. [Online; accessed 26-April-2022].
  23. ——. (2021) Elasticsearch: RESTful, Distributed Search & Analytics. https://www.elastic.co/elasticsearch/. [Online; accessed 26-April-2022].
  24. S. Meng and L. Liu, “Enhanced monitoring-as-a-service for effective cloud management,” IEEE Transactions on Computers, vol. 62, no. 9, pp. 1705–1720, 2013.
  25. Y. Duan, G. Fu, N. Zhou, X. Sun, N. C. Narendra, and B. Hu, “Everything as a Service (XaaS) on the Cloud: Origins, Current and Future Trends,” in 2015 IEEE 8th International Conference on Cloud Computing, 2015, pp. 621–628.
  26. J. M. A. Calero and J. G. Aguado, “Monpaas: an adaptive monitoring platformas a service for cloud computing infrastructures and services,” IEEE Transactions on Services Computing, vol. 8, no. 1, pp. 65–78, 2014.
  27. Amazon Web Services, Inc. (2021) CloudWatch. https://aws.amazon.com/cloudwatch/. [Online; accessed 26-April-2022].
  28. Google. (2021) Cloud monitoring | google cloud. https://cloud.google.com/monitoring. [Online; accessed 26-April-2022].
  29. Zabbix LLC. (2021) Zabbix features overview. https://www.zabbix.com/features. [Online; accessed 26-April-2022].
  30. K. Alhamazani, R. Ranjan, K. Mitra, P. P. Jayaraman, Z. Huang, L. Wang, and F. Rabhi, “Clams: Cross-layer multi-cloud application monitoring-as-a-service framework,” in 2014 IEEE International Conference on Services Computing, 2014, pp. 283–290.
  31. K. Alhamazani, R. Ranjan, P. Prakash Jayaraman, K. Mitra, C. Liu, F. Rabhi, D. Georgakopoulos, and L. Wang, “Cross-layer multi-cloud real-time application qos monitoring and benchmarking as-a-service framework,” IEEE Transactions on Cloud Computing, vol. 7, no. 1, pp. 48–61, 2019.
  32. M. Smit, B. Simmons, and M. Litoiu, “Distributed, application-level monitoring for heterogeneous clouds using stream processing,” Future Gener. Comput. Syst., vol. 29, no. 8, 2013.
  33. V. Colombo, A. Tundo, M. Ciavotta, and L. Mariani, “Towards Self-Adaptive Peer-to-Peer Monitoring for Fog Environments,” in Proceedings of the 17th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), 2022.
  34. A. Ciuffoletti, “Application level interface for a cloud monitoring service,” Computer Standards & Interfaces, vol. 46, pp. 15 – 22, 2016.
  35. M. Anisetti, C. A. Ardagna, E. Damiani, and F. Gaudenzi, “A semi-automatic and trustworthy scheme for continuous cloud service certification,” IEEE Transactions on Services Computing, vol. 13, no. 1, pp. 30–43, 2017.
Citations (6)

Summary

We haven't generated a summary for this paper yet.