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What the cloud has to do with a burning house?

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Cloud native applications can create enormous business growth and value in a very short amount of time. Take Instagram as one example company. It took only two years to get a net asset value of 1 billion USD. However, cloud-native applications are often characterized by a highly implicit technological dependency on hosting cloud infrastructures. What happens if you are forced to leave your cloud service provider? What happens if your cloud is burning? The project Cloud TRANSIT investigates how to design cloud-native applications and services to reduce technological dependencies on underlying cloud infrastructures.

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What the cloud has to do with a burning house?

  1. 1. Prof. Dr. Nane Kratzke What to do if your cloud is burning? Well, be prepared ...
  2. 2. ESCAPE ROUTE (aka Agenda) 2 Burning cloud? What does that mean? How long is your escape route in cloud computing? Who takes care for escape routes in cloud computing? How can escape routes look like in cloud computing? Why to take the risk?
  3. 3. What is your major whish in a burning house?
  4. 4. Get out! Fast ...
  5. 5. Was ist ihr sehnlichster Wunsch brennenden Haus? However, there remains one question ...
  6. 6. How to convince these both to get in, just to get you out?
  7. 7. It is simple. They got a promise: „If something happens, we will get you out, what ever it takes!“
  8. 8. Cloud TRANSIT (a research project to get you out of a cloud) 8 • There are a lot of approaches to get into a cloud. • But almost no (pragmatic) approaches exist to leave a cloud or move between clouds. • But: If you know how to get out, you are more willing to take the risk to go in.
  9. 9. What does it mean? My cloud is burning ... Prof. Dr. rer. nat. Nane Kratzke Praktische Informatik und betriebliche Informationssysteme 9 • Provider is insolvent ... • Provider rises prices ... • Provider reduces resource limits ... • Provider terminates your contract ... • Provider has availability problems ... • Changing laws (data protection) ... • Other governance/compliance reasons (data hosted on US territory, NSA?) There are a lot of (hardly predictable) reasons to leave a cloud service provider.
  10. 10. ESCAPE ROUTE (Agenda) 10 Burning cloud? What does that mean? How long is your escape route in cloud computing? Who takes care for escape routes in cloud computing? How can escape routes look like in cloud computing? Why to take the risk?
  11. 11. Example: Instagram Prof. Dr. rer. nat. Nane Kratzke Praktische Informatik und betriebliche Informationssysteme 11 • Worldwide social network for image sharing • 20 employees • Hosted by Amazon Web Services • Net asset value of 1 Bill. USD (that paid Facebook) • No noteworthy IT assets or datacenters (just 20 laptops) Years It took only
  12. 12. Example: Instagram Prof. Dr. rer. nat. Nane Kratzke Praktische Informatik und betriebliche Informationssysteme 12 • Approximately 1 year for analysis and • development of toolings (especially IP Collision Handling) • About 4 to 8 weeks for all migration steps (inlcuding severe outages) Question: How long does it take to transfer all Instagram services and data into Facebook datacenters? ??? This was no ad-hoc transfer! This was a major project.
  13. 13. So, your escape route can be long, ... ... lonely, cumbersome and far away from any data highway.
  14. 14. ESCAPE ROUTE (Agenda) 14 Burning cloud? What does that mean? How long is your escape route in cloud computing? Who takes care for escape routes in cloud computing? How can escape routes look like in cloud computing? Why to take the risk?
  15. 15. Did you know ... More than 95% of all enterprises are small enterprises? Prof. Dr. rer. nat. Nane Kratzke Praktische Informatik und betriebliche Informationssysteme 15 micro enterprises small enterprises medium enterprises large enterprises Category Employees Turnover Micro enterprises < 10 < 2 Mio. € Small enterprises < 50 < 10 Mio. € Medium enterprises < 250 < 50 Mio. € Large enterprises >= 250 >= 50 Mio. € Distribution of ICT enterprises in the European Union (2014), EUSTAT
  16. 16. Current Cloud Computing Research ... Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 16 • Has often implicit assumptions: • Arbitrary companies with • large IT-staffs providing the capability to handle • arbitrary complexity of tools and methods. • These “Super Tankers“ do not have to be afraid of inconviences like vendor lock-in. They are big enough to solve the problem ...
  17. 17. Our target group is different ... Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 17 • Small sailing boat vs. Supertanker (weather) • Small and medium sized enterprises (SME) • 1 person IT-staffs • Public and private cloud computing • We analyze • Container technologies (like Docker) • Container cluster (like Kubernetes, Swarm, Mesos)
  18. 18. According to that .... Cloud fire protection for (not just) small enterprises (that means 95% of all enterprises) looks like that ... Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 18
  19. 19. ESCAPE ROUTE (Agenda) 19 Burning cloud? What does that mean? How long is your escape route in cloud computing? Who takes care for escape routes in cloud computing? How can escape routes look like in cloud computing? Why to take the risk?
  20. 20. Good News ... Prof. Dr. rer. nat. Nane Kratzke Praktische Informatik und betriebliche Informationssysteme 20 2006 2 cloud services reflected by cloud standards 2016 11 cloud services reflected by cloud standards 5 times more standardization than 10 years before !!! Example:
  21. 21. But ... Prof. Dr. rer. nat. Nane Kratzke Praktische Informatik und betriebliche Informationssysteme 21 2 2 2 4 6 7 7 7 7 11 11 1 1 2 4 7 10 14 21 26 42 44 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Relation of considered services considered by CIMI, OCCI, CDMI, OVF, OCI, TOSCA not considered The relation of services reflected by cloud standards to cloud services not reflected by cloud standards decreased over the last 10 years! Analyzed using over 2300 offical release notes of Amazon Web Services (AWS). Data for other providers like Google, Azure, Rackspace, etc. not presented. Basic conclusions for these providers are the same. Cloud-native applications are vulnerable for vendor lock-in. That is especially true for SMEs.
  22. 22. Cloud-native Applications Cloud native applications are often characterized by a highly implicit technological dependency on hosting cloud infrastructures. The project Cloud TRANSIT investigates how to design cloud-native applications and services to reduce technological dependencies on underlying cloud infrastructures. DEFINITION: A cloud-native application is a (micro)service-based, elastic and horizontal scalable application where each self-contained deployment unit of that application is designed according to cloud-focused software design patterns and operated on a self-service agile elastic platform.
  23. 23. The Cloud-Native Reference Model (ClouNS) Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 23
  24. 24. Popular Container-based Cluster Platforms ... Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 24 Docker Swarm Swarm Mode (since Docker 1.12) Clones Kubernetes-like control processes but integrates them in just one component. Secure by default (control and data plane). Hides operation complexity. Google Control processes that continuously drive current state of container based applications towards a defined desired state. Makes Google‘s experience of running large scale production workloads available as open source. Mesosphere Apache Mesos based datacenter operating system for fine grained resource allocation. Frameworks to operate containers and data services. Datacenter focused. Mesos operates successfully large scale datacenters since years (Twitter, Netflix, ...) Practitioners ask for simple solutions (elastic platforms) ...
  25. 25. Avoid Vendor Lock-In using already existing Container-Technologies Prof. Dr. rer. nat. Nane Kratzke Praktische Informatik und betriebliche Informationssysteme 25 Operate application on current provider. Scale cluster into prospective provider. Shutdown nodes on current provider. Cluster reschedules lost container. Migration finished. Pets Cattle It is all about pets vs. cattle! http://www.theregister.co.uk/2013/03/18/servers_pets_or_cattle_cern/
  26. 26. ESCAPE ROUTE (Agenda) 26 Burning cloud? What does that mean? How long is your escape route in cloud computing? Who takes care for escape routes in cloud computing? How can escape routes look like in cloud computing? Why to take the risk?
  27. 27. Prof. Dr. rer. nat. Nane Kratzke Praktische Informatik und betriebliche Informationssysteme 27 Kostenassoziativät New Business Models e.g. cost associativity e.g. unpredictable workloads
  28. 28. Berkley View of Cloud Computing, 2009: Cost associativity in Cloud Computing 28 It cost the same to operate ... ... 720 machines for one hour or one machine for 720 hours.
  29. 29. We are afraid of peak loads, but why? 29 „In other words, even if cloud services cost, say, twice as much, a pure cloud solution makes sense for those demand curves where the peak-to-average ratio is two-to-one or higher.“ Weinman, Mathematical Proof of the Inevitability of Cloud Computing, 2011 http://www.joeweinman.com/Resources/Joe_Weinman_Inevitability_Of_Cloud.pdf
  30. 30. Analyzed use case • Web technology lecture/practical course for computer science students (bachelor) in summer 2011 and summer/winter 2012. • Projects: Development of web information systems (Drupal based) • All groups were assigned cloud service accounts provided by Amazon Web Services (AWS). • Analysis of billing as well as usage data provided by AWS. Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 30
  31. 31. Usage Analysis 31 Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 13 14 15 16 17 18 19 20 21 22 23 24 25 Average Box Usage Maximum Box Usage in an hour (A) Maximum and Average Box Usage Calendar Week UsedServerBoxes 01020304050 Training Project 24x7 Migration
  32. 32. Average to Peak Ratio per week 32 Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 13 14 15 16 17 18 19 20 21 22 23 24 25 Calendar Week 0 14 16 18 20 22 24 0.00.20.40.60.81.0 (C) Average Box to Maximum Box Ratio according to Weinman Calendar Week AvgtoMaxBoxUsageRatio Cloud computing is economical reasonable Cloud computing might be reasonable Cloud computing is economical not reasonable
  33. 33. Economical Decision Analysis A four step process to decide for or against cloud based virtual labs Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 33 A cloud based solution provides a more than 25 times cost advantage. The measured ATP ratio of 0.035 means in fact a 1/0.035 == 28.57 times cost advantage. This means for the presented use case: Compared to necessary investment efforts for a classical dedicated system implementation.
  34. 34. Why this big cost advantage? Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 34 13 14 15 16 17 18 19 20 21 22 23 24 25 Average Box Usage Maximum Box Usage in an hour (A) Maximum and Average Box Usage Calendar Week UsedServerBoxes 01020304050 How to dimensionize the data center? Hmm, peak load ... peak load average load And the delta? Measures the overdimension of a data center
  35. 35. ESCAPE ROUTE (Agenda) 35 Burning cloud? What does that mean? How long is your escape route in cloud computing? Who takes care for escape routes in cloud computing? How can escape routes look like in cloud computing? Why to take the risk?
  36. 36. Summary • You want to adopt cloud computing? • Think about your escape strategy FIRST! • Support research focussing small and medium sized enterprises (it does not cost sooo much) • That supports 95% of all enterprises • (and not only 5% supertankers) • New (maybe disruptive?) business models ... • Cost associativity • Cost advantages for non-static of unpredictable workloads
  37. 37. Acknowledgement • All Pictures taken from Pixabay.com (CC0 Licence) Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 37 Our research is funded by German Federal Ministry of Education and Research (Project Cloud TRANSIT, 03FH021PX4). We thank fat IT solution GmbH (Kiel) for their support of Cloud TRANSIT. Picture Reference Presentation URL
  38. 38. About Prof. Dr. rer. nat. Nane Kratzke Computer Science and Business Information Systems 38 CoSA: https://cosa.fh-luebeck.de/en/contact/people/n-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 Prof. Dr. rer. nat. Nane Kratzke

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