1. CLOUD COMPUTING ARCHITECTURES & APPLICATIONS LECTURERS LAZAR KIRCHEV, PhD ILIYAN NENOV KRUM BAKALSKY 21 March, 2011 LECTURE #6 ARCHITECTURE OF CLOUD APPLICATIONS. CLOUD COMPUTING USE CASE SCENARIOS.

2. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications2 OUTLINE Examples for cloud applications Specifics of cloud applications’ architecture Use case scenarios Customer scenarios Developer requirements Security scenarios Conclusion

3. Architecture of Cloud Applications

4. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications4 Examples for cloud applications  Processing pipelines – document, image, video processing, indexing, data mining  Batch processing – back office applications, log analysis, nightly builds, automated testing, business analytics  Websites – used only during the day, or for particular event, or particular part of the year  Scalable web applications, search engines, mapping engines

5. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications5 Application programming interfaces  Levels of APIs  Level 1 – The wire: At this level, the developer writes directly to the wire format of the request  Level 2 – Language-Specific Toolkits: Developers at this level use a language specific toolkit  Level 3 – Service-Specific Toolkits: The developer uses a higher-level toolkit to work with a particular service  Level 4 – Service-Neutral Toolkits: A developer working at this level uses a common interface to multiple cloud computing providers  Categories of APIs  Category 1 – Ordinary Programming  Category 2 – Deployment: APIs to deploy applications to the cloud  Category 3 – Cloud Services: APIs to work with cloud services  Category 4 – Image and Infrastructure Management: API to manage VM images and infrastructure  Category 5 – Internal Interfaces: APIs for the internal interfaces between parts of the cloud infrastructure

6. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications6 Developer roles  Client Application developer – writes cloud-based client applications for end users  Application developer – writes traditional applications that use the cloud  Deployers – package, deploy and maintain applications that use the cloud  Administrators – work with applications at multiple levels, including deployment and infrastructure management  Cloud Providers – work with the infrastructure beneath their cloud offerings

7. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications7 Specifics of cloud applications’ architecture  Consists of components, scalable on their own  Each component implements a service interface, responsible for its own scalability  Loosely coupled components  If one fails, the others continue  Ensure resilience  Automatic failure recovery

8. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications8 Specifics of cloud applications’ architecture  Use parallelism  Distribute tasks on multiple machines  Multithreaded requests  Effective aggregation of results, calculated in parallel  Use on-demand resources  Achieves best cost-effectiveness

9. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications9 Specifics of cloud application’ architecture  Cloud application example – GrepTheWeb  Searching in web data using a regular expression language  Based on Amazon Web Services  Amazon S3 for storage  Amazon SQS for asynchronous messaging  Amazon SimpleDB for intermediate results  Amazon EC2 for running Hadoop  Hadoop for distributed processing  Implements the discussed architectural characteristics

10. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications10 Use Case Scenarios

11. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications11 End user to cloud  End users access applications running on the cloud  Requirements – identity, open client, security, SLAs

12. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications12 Enterprise to cloud to end user  Customers and employees access applications on the public cloud  Requirements – identity, open client, federated identity, location awareness, metering and monitoring, management and governance, security, common file format for VMs, common APIs for cloud storage and middleware, data and application federation, SLAs and benchmark, lifecycle management

13. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications13 Enterprise to cloud  Cloud applications integrated with internal IT capabilities  Requirements – in addition to the requirements for the enterprise to cloud to end user scenario, deployment, industry-specific standards and protocols

14. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications14 Enterprise to cloud to enterprise  Cloud applications running in the public cloud and interoperating with partner applications  Requirements – as for enterprise to cloud scenario, plus transactions and concurrency and interoperability

15. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications15 Private cloud  A cloud hosted by an organization inside that organization’s firewall  Requirements – open client, metering and monitoring, management and governance, security, deployment, interoperability, a common VM format, SLAs.  Does not require – identity, federated identity, location awareness, transactions, industry standards, common APIs for cloud middleware and lifecycle management

16. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications16 Changing cloud vendors  An organization using cloud services switches cloud providers or work with additional providers  Requirements – open client, location awareness, security, SLAs, a common file format for VMs, common APIs for cloud storage and middleware  Change SaaS vendors – industry specific standards  Change middleware vendors – industry- specific standards, common APIs for cloud middleware  Changing cloud storage vendors – common API for cloud storage  Changing VM hosts – common format for VMs

17. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications17 Hybrid cloud  Multiple clouds work together, coordinated by a cloud broker that federates data, applications, user identity, security and other details  Requirements – all previous requirements, except transactions and concurrency

18. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications18 Customer scenarios  Payroll Processing (Enterprise to Cloud)  Processing time reduced  Hardware requirements reduced  Elasticity enabled for future expansion  Logistics & Project Management (Enterprise to Cloud to End User)  Processing time reduced  Manual tasks eliminated  Development environment updated and streamlined

19. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications19 Customer scenarios  Central Government (Private Cloud)  IT expertise consolidated  Hardware requirements reduced  Local Government (Hybrid Cloud)  IT expertise consolidated  Hardware requirements reduced  Astronomic Data Processing (Enterprise to Cloud to End User)  Hardware expenses greatly reduced (processing power and storage)  Energy costs greatly reduced  Administration simplified

20. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications20 Development requirements  Caching  Centralized logging  Databases  Identity Management  Messaging – Point-to-Point  Messaging – Publish-Subscribe  Raw Compute / Job Processing  Session Management  Service Discovery  SLAs  Storage

21. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications21 Security scenarios  Regulations  Security Controls  Asset Management  Cryptography  Data / Storage Security  Endpoint Security  Event Auditing and Reporting  Identity, Roles, Access Control and Attributes  Network Security  Security Policies  Service Automation  Workload and Service Management

22. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications22 Security scenarios  Security Federation Patterns  Trust  Identity Management  Access Management  Single Sign-On / Sign-Off  Audit and Compliance  Configuration Management

23. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications23 Conclusion  Cloud applications should follow some architectural patterns in order to be appropriate for working in a cloud environment  Basic real world use cases for cloud applications

24. END OF LECTURE #6

25. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications25 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.

26. 2011 Sofia University “Sv. Kliment Ohridski” > Faculty of Mathematics and Informatics > Cloud Computing Architecture and Applications26 Headline area Drawing area White space The Grid