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About Microservices, Containers and their Underestimated Impact on Network Performance

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Microservices are used to build complex applications composed of small, independent and highly decoupled processes. Recently, microservices are often mentioned in one breath with container technologies like Docker. That is why operating system virtualization experiences a renaissance in cloud computing. These approaches shall provide horizontally scalable, easily deployable systems and a high-performance alternative to hypervisors. Nevertheless, performance impacts of containers on top of hypervisors are hardly investigated. Furthermore, microservice frameworks often come along with software defined networks. This contribution presents benchmark results to quantify the impacts of container, software defined networking and encryption on network performance. Even containers, although postulated to be lightweight, show a noteworthy impact to network performance. These impacts can be minimized on several system layers. Some design recommendations for cloud deployed systems following the microservice architecture pattern are derived.

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About Microservices, Containers and their Underestimated Impact on Network Performance

  1. 1. About Microservices, Containers and their Underestimated Impact on Network Performance Nane Kratzke 1 Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems
  2. 2. The next 20 to 25 minutes are about ... • Avoiding Vendor Lock-in in Cloud Computing • Microservices, Containers and Container Clusters (like Mesos, Kubernetes, etc.) • Technical and performance impacts of above mentioned approaches • Minimizing these impacts on application, overlay network and infrastructure layer Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 2
  3. 3. Where do we come from ... Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 3 • Research about avoiding Cloud Vendor Lock-in • Small and medium sized companies • Analyzing public, private IaaS infrastructures • Analyzing container technologies like Docker • Container clusters might be the answer
  4. 4. Container Clusters Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 4 or similar container technologies
  5. 5. But you need similar machines ... Is that possible across different providers? Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 5 These instances show same similarity values and could be used for cross-provider container clusters deployed to AWS and GCE.
  6. 6. Some further Myths Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 6  Containers are lightweight (says Docker and IBM)  Software defined networking provides flexibility at reasonable performance impacts (hopefully, but we need it anyway)  Encryption must be a performance killer (otherwise everybody would encrypt)
  7. 7. Microservices Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 7 „The microservice architectural style is an approach to developing a single application as a suite of small services, each running in its own process and communicating with lightweight mechnisms, often an HTTP resource API.“ Martin Fowler
  8. 8. Reference Experiment Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 8 Experiment to measure reference network performance of REST-like HTTP-based communication protocols. Done with Amazon Web Services (region eu-west-1). All hosts m3.medium (1 core).
  9. 9. Impact of Containers Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 9 Experiment to measure container impact on network performance of REST-like HTTP-based communication protocols. All hosts m3.medium (1 core).
  10. 10. Impact of Software Defined Networks Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 10 Experiment to measure additional SDVN impact on network performance of REST-like HTTP-based communication protocols. All hosts m3.medium (1 core). SDVN solution: weave docker network
  11. 11. Impact of Encryption Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 11 Experiment to measure additional encryption impact on network performance of REST-like HTTP-based communication protocols. All hosts m3.medium (1 core). SDVN solution: weave docker network
  12. 12. Impact to Transfer Rates Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 12
  13. 13. Cross Regional Experiment Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 13 Just to get a better „feeling“ ...
  14. 14. Where to loose ... Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 14 Loss caused by containers Loss caused by SDN Loss caused by encryption
  15. 15. Finally, measured losses are caused by ... Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 15
  16. 16. Conclusion Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 16 Application layer: Overlay network layer: Infrastructure layer: • Reduce message sizes • Reduce messages • Smaller messages, smaller problems • Less messages, less problems • Encryption for small messages is almost for free • Do not containerize SDN routers • Deploy SDN routers directly on the host • Avoids Container losses of about 10% – 20% • Use multi core hosts • To minimize CPU contention of SDN router processes with application processes • Plan 1 core for the network! but have performance implications in mind ...
  17. 17. Acknowledgement • Stormy sailing: Free Aussie Stock, http://freeaussiestock.com/free/Queensland/mission_be ach/slides/mission_beach_sailing.htm • Stonehenge: Wikipedia, http://pt.wikipedia.org/wiki/Stonehenge • Microservices: Robert Morschel, http://www.soa- probe.com/2015/03/microservices-summary.html Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 17 This study was funded by German Federal Ministry of Education and Research (Project Cloud TRANSIT, 03FH021PX4). The author thanks Lübeck University (Institute of Telematics) and fat IT solution GmbH (Kiel) for their support of Cloud TRANSIT. The author also thanks Bryan Boreham of zett.io for checking our data of zett.io’s weave solution (which might show now better results than the analyzed first version of weave). Picture Reference
  18. 18. About Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 18 Nane Kratzke CoSA: http://cosa.fh-luebeck.de/en/contact/people/kratzke Blog: http://www.nkode.io Twitter: @NaneKratzke GooglePlus: +NaneKratzke LinkedIn: https://de.linkedin.com/in/nanekratzke GitHub: https://github.com/nkratzke ResearchGate: https://www.researchgate.net/profile/Nane_Kratzke SlideShare: http://de.slideshare.net/i21aneka

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