1. CLOUD COMPUTING ARCHITECTURES & APPLICATIONS LECTURERS DR. LAZAR KIRCHEV ILIYAN NENOV KRUM BAKALSKY 28 March, 2011 LECTURE #5 DEFINITION AND TAXONOMY OF CLOUD COMPUTING. CLOUD ARCHITECTURES.

2. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications2 Agenda What is Cloud Computing Basic Models and Essential Characteristics  Service Models  Deployment Models  Essential Characteristics Taxonomy

3. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications3 What is Cloud Computing Definition: Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. Definition by the U.S. Government's National Institute of Standards and Technology In short: Computing as utility. Alternative: YouTube:com >> cloud computing YouTube:com >> cloud computing

4. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications4 Fixed Costs Variable Costs Economics of Cloud Computing costs users Variable Costs Traditional IT Cloud Computing Fixed Cost: e.g hardware, rent, bank guarantee … Variable Cost: e.g operations, electricity consumption, throughput…  Fixed costs work like entry barrier for the business  Variable costs scale with the growth (consumption)

5. Basic Models and Essential Characteristics

6. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications6 Amazon EC2 RackSpace Verizon T-Systems Akamai GoGrid IaaS Google App Engine Heroku MS Windows Azure Force.com PaaS Google Apps SalesForce.com SAP ByDesign Citrix Sugar CRM SaaS Basic Models > Service Models Compute App. Framework Business Logic

7. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications7 Basic Models > Deployment Models Security Costs Community Cloud Private Cloud Hybrid Cloud Public Cloud L H H Applications for Business Services Core Mission Applications Internal Agency Web Portals Office Automation and Productivity Tools Application Development and Testing Communications (wikis, Blogs, Web Sites) Citizen Engagement (e.g. e-Government) Data Dissemination (e..g Data.gov)

8. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications8 Basic Models > Essential Characteristics On-demand self services Broad network access Resource pooling Rapid elasticity Measured Service This requires the architecture to consider high levels of automation This requires the architecture to rely on open standards and technologies. This requires high levels of abstractions on the architecture This requires the architecture to consider sophisticated monitoring and event driven behavior. This require the architecture to consider high levels of transparency on the resource utilization.

9. Taxonomy

10. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications10 Taxonomy > General Terms Interoperability Portability Integration Service Level Agreement (SLA) Federation Broker Multi-Tenancy Cloud bursting Policy Governance Application Programming Interface (API)

11. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications11 Major Roles and Activities Service Consumer Service Provider Service Developer Open Standards Role Base UIs SLA Service Creation Service Publishing Service Analytics Security Management Reporting Billing Metering Provision Monitor SLA Hardware Software Kernel Virtualization IaaS PaaS SaaS

12. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications12 What is SLA? A set of services the provider will deliver A complete, specific definition of each service The responsibilities of the provider and the consumer A set of metrics to determine whether the provider is delivering the service An auditing mechanism to monitor the service The remedies available to the consumer and provider if the terms of the SLA are not met How the SLA will change over time

13. Summary

14. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications14 Summary Cloud computing is a model for enabling computing as utility There are four types of clouds depending on the cost and level of publicity All cloud types share same characteristics and taxonomy Cloud application = software as a service + SLA

15. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications15 The information in this document is compiled using varous public sources, freely available in internet. These sources include:  http://www.scribd.com/doc/17929394/Cloud-Computing-Use-Cases-Whitepaperhttp://www.scribd.com/doc/17929394/Cloud-Computing-Use-Cases-Whitepaper  http://www.enisa.europa.eu/act/rm/files/deliverables/cloud-computing-risk-assessmenthttp://www.enisa.europa.eu/act/rm/files/deliverables/cloud-computing-risk-assessment  http://code.google.com/edu/parallel/index.html http://code.google.com/edu/parallel/index.html  Google: Cluster Computing and MapReduce: http://code.google.com/edu/submissions/mapreduce-minilecture/listing.htmlhttp://code.google.com/edu/submissions/mapreduce-minilecture/listing.html  Google Course: MapReduce in a Week http://code.google.com/edu/submissions/mapreduce/listing.htmlhttp://code.google.com/edu/submissions/mapreduce/listing.html  Intensive MapReduce course at MIT http://mr.iap.2008.googlepages.comhttp://mr.iap.2008.googlepages.com  Hadoop Virtual Image Documentation http://code.google.com/edu/parallel/tools/hadoopvm/index.htmlhttp://code.google.com/edu/parallel/tools/hadoopvm/index.html  http://www.umiacs.umd.edu/~jimmylin/cloud-computinghttp://www.umiacs.umd.edu/~jimmylin/cloud-computing  Colby Ranger, Ramanan Raghuraman, Arun Penmetsa, Gary Bradski, Christos Kozyrakis,  Evaluating MapReduce for Multi-core and Multiprocessor Systems, http://csl.stanford.edu/~christos/publications/2007.cmp_mapreduce.hpca.pdfhttp://csl.stanford.edu/~christos/publications/2007.cmp_mapreduce.hpca.pdf  http://www.dbms2.com/2008/08/26/why-mapreduce-matters-to-sql-data-warehousinghttp://www.dbms2.com/2008/08/26/why-mapreduce-matters-to-sql-data-warehousing  Bingsheng He, Wenbin Fang, Qiong Luo, Mars: A MapReduce Framework on Graphics Processors http://www.cse.ust.hk/catalac/users/saven/GPGPU/MapReduce/PACT08/171.pdfhttp://www.cse.ust.hk/catalac/users/saven/GPGPU/MapReduce/PACT08/171.pdf  Hung-chih Yang, Ali Dasdan, Map-reduce-merge: simplified relational data processing on large clusters http://portal.acm.org/citation.cfm?doid=1247480.1247602http://portal.acm.org/citation.cfm?doid=1247480.1247602  Foto N. Afrati, Jeffrey D. Ullman, A New Computation Model for Rack-Based Computing http://infolab.stanford.edu/~ullman/pub/mapred.pdfhttp://infolab.stanford.edu/~ullman/pub/mapred.pdf  Ralf Lammel, Google’s MapReduce Programming Model Revisite http://www.cs.vu.nl/~ralf/MapReduce/paper.pdfhttp://www.cs.vu.nl/~ralf/MapReduce/paper.pdf  http://www.baselinemag.com/c/a/Infrastructure/How-Google-Works-1http://www.baselinemag.com/c/a/Infrastructure/How-Google-Works-1  Joe Hellerstein, Parallel Programming in the Age of Big Data http://gigaom.com/2008/11/09/mapreduce-leads-the-way-for-parallel-programminghttp://gigaom.com/2008/11/09/mapreduce-leads-the-way-for-parallel-programming  Jeffrey Dean and Sanjay Ghemawat, MapReduce: Simplified Data Processing on Large Clusters https://sites.google.com/a/colgate.edu/cloudintro/Homehttps://sites.google.com/a/colgate.edu/cloudintro/Home © 2011 COPYRIGHTS DISCLAIMER The information in this document is proprietary to Sofia University “Sv. Kliment Ohridski” (called THE UNIVERSITY bellow) http://uni-sofia.bg THE UNIVERSITY assumes no responsibility for errors or omissions in this document. THE UNIVERSITY does not warrant the accuracy or completeness of the information, text, graphics, links, or other items contained within this material. This document is provided without a warranty of any kind, either express or implied, including but not limited to the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. This document is used only for educational purposes related to the masters programs of THE UNIVERSITY, Faculty of Mathematics and Informatics. This document is compiled using various public sources freely available in internet or offered by SAP AG. This document is not used directly or indirectly for any type of commercial use. http://fmi.uni-sofia.bg THE UNIVERSITY shall have no liability for damages of any kind including without limitation direct, special, indirect, or consequential damages that may result from the use of these materials. This limitation shall not apply in cases of intent or gross negligence. The statutory liability for personal injury and defective products is not affected. THE UNIVERSITY has no control over the information that you may access through the use of hot links contained in these materials and does not endorse your use of third-party Web pages nor provide any warranty whatsoever relating to third-party Web pages.

16. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications16 Headline area Drawing area White space The Grid