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FLUX - Crash Course in Cloud 2.0


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Presentation on the current state of cloud computing and the role that open source, containers and microservices are playing in the cloud.

Presented to Florida Linux Users Exchange on April 9th, 2015

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FLUX - Crash Course in Cloud 2.0

  1. 1. Florida Linux User Exchange April 2015 Mark Hinkle Senior Director Open Source Solutions @mrhinkle
  2. 2. Slides Can be Viewed and Downloaded at: Copyright Mark R. Hinkle, available under the CCbySA license some rights reserved 2015
  3. 3. Walking before you run
  4. 4. Inspired by Simon Wardley
  5. 5. 0 0.5 1 1.5 2 2.5 3 3.5 4 Amazon Azure Google Rackspace Revenue (in Billions) Source: Company data, Evercore Group LLC, Research. Azure based on MSFT comments about a $1 billion rev run rate in May 2013. Google based on estimate by TBR (Technology Business Research)
  6. 6. Company Revenue Annual Growth Amazon $962 million 49% Microsoft $370 164% IBM $259 86% Salesforce $203 38% Google $169 47% Source: Synergy Research Group
  7. 7. “Citrix CloudStack 3 Brings the Power of Amazon-Style Clouds to Customers of All Sizes” Citrix Press Release, February 12, 2012 “AWS And Eucalyptus To Make It Easier For Customers To Migrate Applications Between On-Premises Environments And The Cloud” Eucalyptus Press Release, March 22, 2012 “HP Cloud Compute undercuts Amazon, too” Tech Target, December 12, 2012
  8. 8. H/T: Adrian Cockcroft
  9. 9.
  10. 10. Public PrivateHybrid
  11. 11. zzz Public Cloud • Global Footprint • Massive Scale • Extreme Velocity Vendors Advantages Challenges • Stability • Security • Privacy • End-to-End Network • Security & SLA • App QOS • SI Capabilities • Enterprise Trust • SMB Channel Managed Cloud SP/SI Cloud • Higher price than Public Cloud • Limited services capabilities • Agility • Stack lock-in • Not always best of breed for whole stack
  12. 12. Compute (Containers, KVM, Xen Project) Distirbuted Storage (Ceph, Gluster) Networking (Open Daylight) Orchestration – OpenStack, Apache CloudStack Docker Apache Mesos Kubernetes Platform-as-a-Service – CloudFoundry, OpenShift, Gigaspaces
  13. 13. Containers compared to Hardware Virtualization • Different file formats for virtual machines (VMware uses vmdk file format, Xen and Hyper- V use VHD, KVM uses Raw or QCOW2) • Guest images may be “processor architecture” bound • VMware and Xen can manage SCSI devices, but KVM cannot • KVM and Xen can use virtio drivers but not VMware • VMware uses a proprietary agent inside the guest OS (VMware tools) which does not work with Xen or KVM • Yada, Yada, Yada
  14. 14. • Lightweight Linux execution environment • Static application composition • Reliable deployment • Unit of resource isolation • Execution isolation • Multi-tenancy without heavyweight VMs
  15. 15. • Rapid deployment • Ease-of-use • Portability • Provenance • Reusable Code • Open Source • Configurable Layers • Reproducible • Version-Controlled The Flux Capacitor Of Cloud Computing
  16. 16. Legacy - Node First Development App +SO bundled machine images Fragile, tightly couple apps and little resource fungability. Low resource efficiency Containers Hermetically sealed deployment units Efficient isolation and resource use. Clustering Declarative app model Agile, decoupled architecture Smart (Machine Learning Enhanced) Active Management New World - Cluster First Development Radically enhanced developer productivity: snap together systems. Radically reduced operations overhead: deploy, run, update effortlessly Operational specialization: cluster/infra ops separate from app ops
  17. 17. • Security??? • Binary Management (Repos) • Resource tracking and separation • Networking across clouds/hosts • Container consistency (Multiple container sources) • Many other problems with rapidly deployable, highly portable, easily used technologies
  18. 18. Container Cluster Management – Scheduler Kubernetes builds on top of Docker to construct a clustered container scheduling service. Kubernetes enables users to ask a cluster to run a set of containers. The system will automatically pick worker nodes to run those containers on, which we think of more as "scheduling" than "orchestration” To learn more please visit: for Shipmaster
  19. 19. A design pattern in which software/application components provide services to other software/application components via a protocol, typically over a network and in a loosely-coupled way. SOA Definition circa 1995
  20. 20. microservices(n) - Loosely coupled service oriented architecture with bounded contexts If every service has to be updated at the same time it’s not loosely coupled If you have to know too much about surrounding services you don’t have a bounded context.
  21. 21. • Microservices can be introduced quickly • Leave old services in production until time to clean-up • Allows for faster speed of innovation • Code pushes are only additive so no legacy issues
  22. 22. Rocket ?
  23. 23. NetflixBlog-
  24. 24. Alex Williams (the New Stack) : Looking out at 2015, what are some of the issues that will be more complex in this distributed infrastructure world for customers – what are some of the top ones you see? Mitchell Hashimoto(Hashicorp) - Number one is service proliferation, where your data center just becomes more and more services. Number two is, inherently becoming multi-data-center and highly-distributed at a much earlier stage. With things like Docker, where you can run things in much smaller units, it becomes a lot easier to start running a lot more services. As a result, we have a management problem, an orchestration problem, and distributed system problems in there. Source:
  25. 25. Cloud 2.0 Where Awesome Starts
  26. 26. …the future of technological innovation is not stealing limited resources away from one another, but creating new resources — and new opportunities to create new resources — together in a rich ecosystem. Allison Randal Open Source Hacker Former OSCON Program Chair @allisonrandal Open Source Isn’t a Zero-Sum Game
  27. 27. How can you tell if they’re Legit • Code Velocity • Committers • Committer Reputation • User-driven or Vendor-Driven Innovation • User Activity • Corporate Support* • Reputation of Foundation*
  28. 28. Visualizing Community Activity
  29. 29. Innovate Develop what doesn’t exist to address your needs Leverage Leverage the growing base of high-quality open source software Commoditize Shift non-differentiating tech to reliable services or sources Simon Wardley – Open Source as a weapon
  30. 30. • Declarative > Imperative – State desired results, let the system actuate • Control loops: Observe, rectify, repeat • Simple > complex: Do as little as possible • Modularity: Components, interfaces & plugins • Legacy compatible: Requiring apps to change is a non-starter • Network-centeric – IP addresses are cheap • Non grouping - Labels are the only groups • Cattle > pets: Manager your workload in Bulk • Open > closed: Open Source, standards, REST, JSON, etc. Courtesy: Craig Mcluckie Google Linux Collab Summit
  31. 31. • Massively Scalable • Secure • Competitive Prices • Distributed Applications • Proliferation of Microservices coming
  32. 32. • Cloud Tenets (Rapid Elasticity, Metered, Self-Service, Pooling, Broad Network) • Hosted on User Selected Hardware • Tailored to just what you need • Unlikely to have as many zones as public • Next evolution of cloud isn’t all-in-on, it’s federation of cloud services (no silos)
  33. 33. • Minimum Viable Cloud • Network Quality of Service* • Application Management * • Service Level Differentiation* • Developer Environments* • Advanced Security* • Continuous Integration* • Developer Environments *
  34. 34. And I work on open source at Citrix. Thank You
  35. 35. • Pattern: Microservices Architecture • Gilt’s Kevin Scaldeferri on Enabling Micro-service Architectures with Scala(Video) • Heroku Blog - Why Microservices Matter • Microservices Example – Azure Biz Talk • Video: Integrating to Microservices by Adrian Cockcroft • Distributed Systems for Fun and Profit