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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
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
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
Container Clusters
Prof. Dr. rer. nat. Nane Kratzke
Computer Science and Business Information Systems
4
or similar container
technologies
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.
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)
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
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).
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).
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
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
Impact to Transfer Rates
Prof. Dr. rer. nat. Nane Kratzke
Computer Science and Business Information Systems
12
Cross Regional Experiment
Prof. Dr. rer. nat. Nane Kratzke
Computer Science and Business Information Systems
13
Just to get a better
„feeling“ ...
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
Finally, measured losses are caused by ...
Prof. Dr. rer. nat. Nane Kratzke
Computer Science and Business Information Systems
15
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 ...
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
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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About Microservices, Containers and their Underestimated Impact on Network Performance

  • 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. 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. 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. Container Clusters Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 4 or similar container technologies
  • 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. 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. 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. 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. 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. 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. 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. Impact to Transfer Rates Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 12
  • 13. Cross Regional Experiment Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 13 Just to get a better „feeling“ ...
  • 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. Finally, measured losses are caused by ... Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 15
  • 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. 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. 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

Editor's Notes

  1. Good day everybody. My name is Nane Kratzke and I am a professor for computer science and business information systems at the luebeck university of applied sciences, germany. Today I would like to talk about cloud computing, vrtual labs and economical effects if both concepts are combined. This contribution has a little case history. Two years ago i became a professor and one of my first duties was to set up a lecture and corresponding practical course about web technologies. I turned out that my assigned educational budget was totally insuffiecent for that task – especially it was absolutely insufficent to equip a classical dedicated lab or a webtechnology purpose. So we searched for a solution and founda „sort-term“ solution by providing rented resources via amazon web services to our students. Nevertheless our inital intent was to establish a dedicated lab and therefore our plan was to proof that a classical dedicated lab is much more cost effective than a virtual one. In fact we proofed the exact opposite. We proofed that a virtual lab is much more cost effective than a dedicated one. A the very first moment that was a little bit frustrating because our dedicated lab became realy unlikely. This presentation is about this completely flopped proof. Nevertheless we found our results being worth reflected by others. And so we published them.
  2. So let us begin ....