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Applied Architectures

Learn how architectural principles address complex problems in commercial systems, using examples like Google, REST, peer-to-peer, and cloud computing. Understand fallacies of distributed systems and the benefits of REST style.

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Applied Architectures

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  1. Applied Architectures Eunyoung Hwang

  2. Objectives • How principles have been used to solve challenging problems • How architecture can be used to explain and analyze common commercial systems

  3. Outline • Distributed Network-based Applications • Limitations • REST • Commercial Internet Scale Applications: Google • Decentralized Architecture • Grid Computing • Cloud Computing • Peer-2-Peer: Napster, Grutella, Skype

  4. Fallacies of Distributed Systems Viewpoint • The network is reliable • Latency is zero • Bandwidth is infinite • The network is secure • Topology does not change • There is one administrator • Transport cost is zero • The network is homogeneous

  5. WWW Architecture • World Wide Web is distributed, decentralized, hypermedia application.

  6. Representational State Transfer (REST) Style • A set of constraints based on WWW architectural style User agent Origin Server Request Proxies Gateways Response C C C C Intermediaries

  7. Process View of a REST-based Architecture

  8. Derivation of REST

  9. REST (cont.) • Constraints • Client-server • Context-free (stateless) • Cache • Code on demand • Layered • Uniform Interface • Benefits • Efficiency • Scalability • User perceived performance

  10. Commercial Internet-Scale Applications • Google strategy • Simpler storage system offering fewer features • Data Storage and manipulation • A high fault-tolerant platform • Cost effective manner • Google design • Google distributed file system (GFS) • MapReduce

  11. Google File System Architecture

  12. MapReduce • Large-scale data processing • Map • Take input key/value pair, generate a set of intermediate pair • Reduce • Merge all intermediate values associated with the same intermediate key Map (k1, v1) -> list(k2, v2) Reduce (k2, list(v2)) -> list(v2) • E.g., word frequency • map (URL, contents) -> set of (word, 1) • Reduce (word, 1) -> set of (word, sum)

  13. MapReduce Execution Flow

  14. MapReduce (cont.) • Architecture Provides • Automatic parallelization & distribution • Fault tolerance • Walker failure • Master failure

  15. Decentralized Architecture • Networked applications where there are multiple authorities • Not a new idea • E.g., web sites, international postal mail • Designing challenges

  16. Grid Computing • Coordinated resource sharing and computation in a decentralized environment • Technologies that allow consumers to obtain computing power on demand • Starts with large-scale federated resources • Issues • Interoperability • Security

  17. Grid Architecture

  18. Globus Grid Architecture (recovered)

  19. Cloud Computing • A key computing platform for sharing resources • A specialized distributed computing paradigm • Massively scalable • Different level of service • Driven by economies of scale • Dynamically configured and delivered on demand • What makes Cloud Computing interesting now? • Not a new concept!

  20. Cloud Computing

  21. Three level Services by Cloud Computing • Infrastructure as a Service(IaaS) • Amazon EC2 • Platform as a Service (PaaS) • Google App Engine • Software as a Service (Saas) • Salesforce

  22. Grid vsCloud Computing

  23. Peer-to-Peer: LL

  24. Napster • Hybrid client-server/P2P

  25. Gnutella • Pure decentralized P2P

  26. Skype • Overlayed P2P

  27. Review • Distributed Network-based Applications • REST • - Google: GFS, MapReduce • Decentralized Architecture • - Grid Computing • - Cloud Computing • - Peer-2-Peer: Napster, Grutella, Skype

  28. References • Principled Design of The Modern Web Architecture. • Fielding, Roy T., and Richard N. Taylor. • Cloud Computing and Grid Computing 360-Degree Compared. • Foster, Ian, and Zhao Yong. • MapReduce: Simplied Data Processing on Large Clusters • Dean, Jeffrey, and Sanjay Ghemawat. • The Google File System. • Ghemawat, Sanjay, Howard Gobioff, and Shun-Tak Leung

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