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The New Open Distributed Application Architecture


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The platform for developing and running modern workloads has changed. This new platform brings together the open source innovation being driven in containers and container packaging, in distributed resource management and orchestration, and in DevOps toolchains and processes to deploy infrastructure and management optimized for the new class of distributed application that is becoming the norm.

In this session, Red Hat's Gordon Haff discusses the key trends coming together to change IT infrastructure and the applications that will run on it. These include:

Container-based platforms designed for modern application development and deployment

The ability to design microservices-based applications using modular and reusable parts

The orchestration of distributed components

Data integration with mobile and Internet-of-Things services

Iterative development, testing, and deployment using Platform-as-a-Service and integrated continuous delivery systems

Published in: Technology
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The New Open Distributed Application Architecture

  1. 1. The New Distributed Application Infrastructure Gordon Haff @ghaff Technology Evangelist Red Hat
  2. 2. About me • Red Hat Technology Evangelist • Twitter: @ghaff • Google+: Gordon Haff • Flickr: bitmason • Email: • Blog: • Author: Computing Next • Formerly: Illuminata(industry analyst)Data General (minicomputers/Unix/NUMA/etc.)
  3. 3. This is all very new 2007 2011 2013 2014 2006
  4. 4. A common thread is open source innovation And the principles and practices associated with it
  5. 5. Computing as puntuated equilibria • Rapidly changing environment • Open source innovation and recombinations • Intersecting trends • Hard to predict
  6. 6. Traditional infrastructure & apps Server, storage, & networking hardware Operating system Application & dependencies Application & dependencies Application & dependencies
  7. 7. (One of) the problems Server, storage, & networking hardware Operating system Application & dependencies Application & dependencies Application & dependencies
  8. 8. Enter hardware virtualization Server, storage, & networking hardware with CPU, memory, I/O virtualization assists Hypervisor (or other partitioning methods) Application & dependencies Application & dependencies Application & dependencies Operating system Operating system Operating system
  9. 9. What’s changed really? • Application components still installed within OS • Applications still long- lived & stateful • Applications still “pets”
  10. 10. Which was sort of the point • Improved server utilization reduced CAPEX • Without (at least initially) much impact on operational model 2006
  11. 11. The discontinuity hits • “Software is eating the world” • Digital transformation needed: – More effective software delivery – Reimagined componentized architectures – Scale – Pervasive sensors & access
  12. 12. Better faster software with DevOps
  13. 13. DevOps applies open source tools, principles, and practices with: • CULTURE of collaboration valuing openness and transparency • AUTOMATION of process from development through ongoing operations • An evolving PLATFORM that optimizes for flexible, dynamic workloads
  14. 14. Toward an “ant” model for apps • Stateless (often) • “Small” components • Expose an API • Replacable cogs • Portable across hybrid infrastructures
  15. 15. Signs you might need microservices • Having trouble coordinating function teams like DBAs and UI engineers • Brittle apps. Minor changes cause major breakage • Your process is bogged down by big deployments • Different teams keep reinventing the wheel (in gratuitously different ways) • Hard to experiment
  16. 16. On the other hand • Architectural effort • Service boundaries • Communication overhead • Do you need it?
  17. 17. DevOps + “Cloud” = Industrialize
  18. 18. What does this factory look like?
  19. 19. From servers to resource pools • Software- defined “everything” • Dynamic resource pool • May be provided by public cloud Virtualized pool of IaaS resources “Commodity” server “Commodity” server “Commodity” server Operating system Operating system Operating system Operating system Software-defined storage Software-defined networking/NFV
  20. 20. OpenStack: Software-defined infrastructure Linux
  21. 21. Containers: Isolation within OS • OS-level virtualization • Originally BSD jails • Then Solaris zones • OS kernel manages isolation, resource use, and security • Namespaces, SELinux, Cgroups in Linux Operating system instance Application & dependencies Application & dependencies Resource pool
  22. 22. Making containers useful & portable • Standard packaging format • Ecosystem App composition specification • Optimized operating system foundation Lightweight, immutable OS for running containers Application & dependencies Application & dependencies Resource pool Container packaging for image-based deployment
  23. 23. Key areas of container standards Open source communities working to drive
  24. 24. Managing at scale as a single entity Lightweight, immutable OS for running containers Application & dependencies Application & dependencies Resource pool Container packaging/API for image-based deployment Resource management Orchestration
  25. 25. Everyone is scaling • Not just unicorns and mammoths • Three main use cases: – Large scale workloads – Diverse workloads – Complex resource management • Grid computing: It lives!
  26. 26. PaaS is one integration point
  27. 27. Source: DevOps, Open Source and Business Agility: Lessons learned from early adopters, June 2015
  28. 28. Needs for integrating with existing IT 96% see open source as an enabler of cloud native integration and conventional app modernization. Source: Red Hat Modernization Strategies Survey IDC September 2015 Structured & unstructured data integration Business process automation Model-driven process management Enterprise service bus & APIs
  29. 29. Data integration services
  30. 30. Some open questions • Role of hardware virtualization • On-premise vs. public cloud trends • Monoliths vs. Microservices • The post-NIST service model • When/where/how is data useful?
  31. 31. How evenly distributed will the future be? The future is already here—it's just not very evenly distributed. William Gibson
  32. 32. Credits Fractal: Creative Commons license Punctuated equilibrium:University of California atBerkeley Mainframe:"IBM 704 mainframe"by Lawrence Livermore National Laboratory.Licensed under Attribution via Commons - Ants: Flickr Creative Commons license Meteor, galaxy: NASA Datacenter:Google Dogs: Flickr Creative Commons license Aircraft factory: Flickr/cc, programming:Esti Alvarez cc license Auto factory: CopyrightTesla Tower: Daniel Pratts CC/flickr Frog: Kathy CC/Flickr Coupling graphic:PWC Buildings:CC/Flickr
  33. 33. Thank you!