A Black-box Monitoring Approach to Measure Microservices Runtime Performance

Abstract

Microservices changed cloud computing by moving the applications’ complexity from one monolithic executable to thousands of network interactions between small components. Given the increasing deployment sizes, the architectural exploitation challenges, and the impact on data-centers’ power consumption, we need to efficiently track this complexity. Within this article, we propose a black-box monitoring approach to track microservices at scale, focusing on architectural metrics, power consumption, application performance, and network performance. The proposed approach is transparent w.r.t. the monitored applications, generates less overhead w.r.t. black-box approaches available in the state-of-the-art, and provides fine-grain accurate metrics.

References

1. Amedeo Asnaghi, M. Ferroni, and M. D. Santambrogio. 2016. DockerCap: A software-level power capping orchestrator for docker containers. In Proceedings of the Conference on Computational Science and Engineering (CSE’16) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC’16) and 15th International Symposium on Distributed Computing and Applications for Business Engineering (DCABES’16). IEEE, 90--97.
2. David H. Bailey, Eric Barszcz, John T. Barton, David S. Browning, Robert L. Carter, Leonardo Dagum, Rod A. Fatoohi, Paul O. Frederickson, Thomas A. Lasinski, Rob S. Schreiber, et al. 1991. The NAS parallel benchmarks. Int. J. Supercomput. Applic. 5, 3 (1991), 63--73.
3. BCC. 2020. BPF Compiler Collection (BCC). Retrieved from https://www.iovisor.org/technology/bcc.
4. Andrew Begel, Steven McCanne, and Susan L. Graham. 1999. BPF+: Exploiting global data-flow optimization in a generalized packet filter architecture. In ACM SIGCOMM Comput. Commun. Rev., Vol. 29. ACM, 123--134.
5. Frank Bellosa. 2000. The benefits of event: Driven energy accounting in power-sensitive systems. In Proceedings of the 9th ACM SIGOPS European Workshop: Beyond the PC: New Challenges for the Operating System. ACM, 37--42.
6. Rolando Brondolin, Matteo Ferroni, and Marco Santambrogio. 2019. Performance-aware load shedding for monitoring events in container based environments. ACM SIGBED Rev. 16, 3 (2019), 27--32.
7. Rolando Brondolin, Tommaso Sardelli, and Marco D. Santambrogio. 2018. DEEP-mon: Dynamic and energy efficient power monitoring for container-based infrastructures. In Proceedings of the IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW’18). IEEE, 676--684.
8. Brendan Burns, Brian Grant, David Oppenheimer, Eric Brewer, and John Wilkes. 2016. Borg, Omega, and Kubernetes. Queue 14, 1 (2016), 70--93.
9. Chia-Chen Chang, Shun-Ren Yang, En-Hau Yeh, Phone Lin, and Jeu-Yih Jeng. 2017. A Kubernetes-based monitoring platform for dynamic cloud resource provisioning. In Proceedings of the IEEE Global Communications Conference (GLOBECOM’17). IEEE, 1--6.
10. Marcello Cinque, Raffaele Della Corte, and Antonio Pecchia. 2019. Microservices monitoring with event logs and black box execution tracing. IEEE Trans. Serv. Comput. (2019).
11. Cncflandscape. 2020. CNCF Cloud Native Landscape. Retrieved from https://landscape.cncf.io.
12. Datadog [n.d.]. Datadog. Retrieved on July 2020 from https://www.datadoghq.com.
13. Arnaldo Carvalho De Melo. 2010. The new linux “perf” tools. In Slides from Linux Kongress, Vol. 18. 1--42.
14. Luca Deri, Maurizio Martinelli, and Alfredo Cardigliano. 2014. Realtime high-speed network traffic monitoring using ntopng. In Proceedings of the 28th Large Installation System Administration Conference (LISA’14). 78--88.
15. Luca Deri, Samuele Sabella, and Simone Mainardi. 2019. Combining system visibility and security using eBPF. In Proceedings of the Italian Conference on Cybersecurity.
16. Docker 2020. Docker. Retrieved from https://www.docker.com.
17. Matteo Ferroni, Juan A. Colmenares, Steven A. Hofmeyr, John D. Kubiatowicz, and Marco D. Santambrogio. 2018. Enabling power-awareness for the Xen hypervisor. ACM SIGBED Review 15, 1 (2018), 36--42.
18. Martin Fowler and James Lewis. 2014. Microservices—A definition of this new architectural term. Retrieved from http://martinfowler. com/articles/microservices.html.
19. Yu Gan, Yanqi Zhang, Dailun Cheng, Ankitha Shetty, Priyal Rathi, Nayan Katarki, Ariana Bruno, Justin Hu, Brian Ritchken, Brendon Jackson, et al. 2019. An open-source benchmark suite for microservices and their hardware-software implications for cloud 8 edge systems. In Proceedings of the 24th International Conference on Architectural Support for Programming Languages and Operating Systems. 3--18.
20. Yu Gan, Yanqi Zhang, Kelvin Hu, Dailun Cheng, Yuan He, Meghna Pancholi, and Christina Delimitrou. 2019. Seer: Leveraging big data to navigate the complexity of performance debugging in cloud microservices. In Proceedings of the 24th International Conference on Architectural Support for Programming Languages and Operating Systems. 19--33.
21. Emir Imamagic and Dobrisa Dobrenic. 2007. Grid infrastructure monitoring system based on Nagios. In Proceedings of the Workshop on Grid Monitoring. ACM, 23--28.
22. Edward D. Lazowska, John Zahorjan, G. Scott Graham, and Kenneth C. Sevcik. 1984. Quantitative System Performance: Computer System Analysis Using Queueing Network Models. Prentice-Hall, Inc.
23. Dimosthenis Masouros, Sotirios Xydis, and Dimitrios Soudris. 2020. Rusty: Runtime interference-aware predictive monitoring for modern multi-tenant systems. IEEE Trans. Parallel Distrib. Syst. 32, 1 (2020), 184--198.
24. Matthew L. Massie, Brent N. Chun, and David E. Culler. 2004. The ganglia distributed monitoring system: Design, implementation, and experience. Parallel Comput. 30, 7 (2004), 817--840.
25. Charles Masson, Jee E. Rim, and Homin K Lee. 2019. DDSketch: A fast and fully-mergeable quantile sketch with relative-error guarantees. Proc. VLDB Endow. 12, 12 (2019), 2195--2205.
26. Benjamin Mayer and Rainer Weinreich. 2017. A dashboard for microservice monitoring and management. In Proceedings of the IEEE International Conference on Software Architecture Workshops (ICSAW’17). IEEE, 66--69.
27. Steven McCanne and Van Jacobson. 1993. The BSD packet filter: A new architecture for user-level packet capture. In Proceedings of the USENIX Winter Conference, Vol. 93.
28. Farnaz Moradi, Christofer Flinta, Andreas Johnsson, and Catalin Meirosu. 2017. Conmon: An automated container based network performance monitoring system. In Proceedings of the IFIP/IEEE Symposium on Integrated Network and Service Management (IM’17). IEEE, 54--62.
29. Philip J. Mucci, Shirley Browne, Christine Deane, and George Ho. 1999. PAPI: A portable interface to hardware performance counters. In Proceedings of the Department of Defense HPCMP Users Group Conference, Vol. 710.
30. Barak Naveh et al. 2008. JGraphT. Retrieved from http://jgrapht. sourceforge. net.
31. Newrelic [n.d.]. NewRelic. Retrieved on July 2020 from https://newrelic.com.
32. Ayman Noor, Devki Nandan Jha, Karan Mitra, Prem Prakash Jayaraman, Arthur Souza, Rajiv Ranjan, and Schahram Dustdar. 2019. A framework for monitoring microservice-oriented cloud applications in heterogeneous virtualization environments. In Proceedings of the IEEE 12th International Conference on Cloud Computing (CLOUD’19). IEEE, 156--163.
33. Fábio Pina, Jaime Correia, Ricardo Filipe, Filipe Araujo, and Jorge Cardroom. 2018. Nonintrusive monitoring of microservice-based systems. In Proceedings of the IEEE 17th International Symposium on Network Computing and Applications (NCA’18). IEEE, 1--8.
34. Sareh Fotuhi Piraghaj, Amir Vahid Dastjerdi, Rodrigo N. Calheiros, and Rajkumar Buyya. 2015. A framework and algorithm for energy efficient container consolidation in cloud data centers. In Proceedings of the IEEE International Conference on Data Science and Data Intensive Systems (DSDIS’15). IEEE, 368--375.
35. Prometheus [n.d.]. Prometheus. Retrieved on July 2020 from https://prometheus.io.
36. Efraim Rotem, Alon Naveh, Avinash Ananthakrishnan, Eliezer Weissmann, and Doron Rajwan. 2012. Power-management architecture of the Intel microarchitecture code-named Sandy Bridge. IEEE Micro 32, 2 (Mar. 2012), 20--27. DOI:https://doi.org/10.1109/MM.2012.12.
37. Kai Shen, Arrvindh Shriraman, Sandhya Dwarkadas, Xiao Zhang, and Zhuan Chen. 2013. Power containers: An OS facility for fine-grained power and energy management on multicore servers. ACM SIGPLAN Not., Vol. 48. ACM, 65--76.
38. sysdig [n.d.]. Sysdig. Retrieved on July 2020 from https://sysdig.com.
39. tcpdump [n.d.]. Tcpdump. Retrieved on July 2020 from http://www.tcpdump.org.
40. weavescope [n.d.]. Weave scope. Retrieved on July 2020 from https://www.weave.works/oss/scope/.
41. Yan Zhai, Xiao Zhang, Stephane Eranian, Lingjia Tang, and Jason Mars. 2014. HaPPy: Hyperthread-aware power profiling dynamically. In Proceedings of the USENIX Annual Technical Conference. 211--217.

Index Terms

• Hardware

  • Power and energy

• Networks

  • Network services

    • Cloud computing

• Software and its engineering

  • Software organization and properties

    • Contextual software domains

      • Operating systems

        • Process management

          • Monitors