Introduction to Cloud Computing
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1 Introduction to Cloud Overview and Introduction , spring st Lecture, Jan 12 th Majd F. Sakr Introduction to Cloud
2 Why take ? Because you re cool! Because we re cool! Gain real world experience and learn new tools Emerging technology New programming model Could be the future of computing? Running application on very large data sets Introduction to Cloud 2
3 Introduction to Cloud
4 Syllabus: Course Purpose Introduce you to the basics of the emerging cloud computing paradigm learn how this paradigm came about understand its enabling technologies understand the computer systems constraints, tradeoffs and techniques in setting up and using the cloud Teach you how to implement algorithms in the cloud gain competence in Hadoop/MapReduce as a programming model for distributed processing of large datasets. understand how different algorithms can be implemented and executed in the Hadoop framework. gain competence in evaluating the performance and identifying bottlenecks when mapping applications to the cloud Introduction to Cloud 4
5 Syllabus: Target Audience Juniors & Seniors Pre requisites: Other equivalent courses Introduction to Cloud
6 Syllabus: Instructor Majd F. Sakr Office Hours: Tuesday 3 5pm Welcome when my office door is open By appointment TA: Suhail Rehman Office Hours: To be decided NOW By appointment Introduction to Cloud
7 Syllabus: Course Components What are we trying to answer? What is Cloud? Why Cloud? What are its challenges and opportunities? How does Cloud work? Introduction to Cloud
8 Time Syllabus: Course Components Now I know what Cloud is End of week two Introduction to Cloud
9 Syllabus: Course Components Now I know what Cloud is Parallel Processing End of week two Now I appreciate why Cloud is important End of week five Distributed Systems Time Introduction to Cloud
10 Syllabus: Course Components Now I know what Cloud is Parallel Processing End of week two Now I appreciate why Cloud is important Now I really understand how Cloud works Functional Programming Algorithms Used by Parallelized by A programming model Map/Reduce End of week five Apache s implementation Storage HDFS Hadoop DFS Hadoop Cluster Distributed Systems Virtualization Time End of week eight Introduction to Cloud
11 Syllabus: Course Components Parallel Processing Cloud HDFS DFS Hadoop Cluster Distributed Systems Storage Map/Reduce Functional Programming Algorithms Used by Parallelized by A programming model Apache s implementation Hadoop Virtualization Introduction to Cloud
12 Syllabus: Course Components Now I can play with Introduction to Cloud
13 Syllabus: Text Books Primary Book: Tom White, Hadoop: The Definitive Guide, O'Reilly Media, Reference Books Tanenbaum and van Steen, Distributed Systems: Principles and Paradigms, Pearson, Jean Dollimore, Tim Kindberg, George Coulouris, Distributed Systems: Concepts and Design, Fourth Edition, Addison Wesley, Randal E. Bryant and David R. O'Hallaron, Computer Systems: A Programmer's Perspective, Prentice Hall, Patterson and Hennessy, Computer Organization and Design: The Hardware/Software Interface, Fourth Edition, Morgan Kaufmann/Elsvier. Jason Venner, Pro Hadoop, Apress, Introduction to Cloud
14 Syllabus: Projects Five assignments 2 weeks per assignment Technical papers and case studies Short write up In class presentations and discussions Four Projects: 4 5 weeks per project Final project includes a paper and presentation Introduction to Cloud
15 Syllabus: Exam Now I know what Cloud is Parallel Processing End of week two Now I appreciate why Cloud is important Now I really understand how Cloud works Functional Programming Algorithms Used by Parallelized by A programming model Map/Reduce End of week five Apache s implementation Storage HDFS Hadoop DFS Hadoop Cluster Distributed Systems Virtualization Time End of week eight End of week NINE ONLY EXAM Introduction to Cloud
16 Syllabus: Grading Attendance/Participation 10% Assignments 15% Projects 60% Project 1: 10% Project 2: 10% Project 3: 15% Project 4: 25% Exam 15% Introduction to Cloud
17 Final Thoughts Introduction to Cloud
18 What Paradigms Are There? Introduction to Cloud
19 Existing Paradigms Introduction to Cloud Carnegie Mellon Grid Super Utility Cluster Pervasive Cloud Mobile Personal Reconfigurable Parallel Distributed Ubiquitous Autonomic
20 Introduction to Cloud Carnegie Mellon Grid Super Utility Cluster Pervasive Cloud Mobile Existing Paradigms Personal Reconfigurable Parallel Distributed Ubiquitous Autonomic
21 Personal Personal computing system Local software installation, maintenance Local system maintenance Customizable to user needs Very low utilization High up front cost Introduction to Cloud
22 Introduction to Cloud Carnegie Mellon Grid Super Utility Cluster Pervasive Cloud Mobile Existing Paradigms Personal Reconfigurable Parallel Distributed Ubiquitous Autonomic
23 Reconfigurable Field Programmable Gate Arrays (FPGAs) Reprogrammable Hardware Can exploit embarrassingly parallel code Slow programming time (ms) Power hungry Introduction to Cloud
24 Introduction to Cloud Carnegie Mellon Grid Super Utility Cluster Pervasive Cloud Mobile Existing Paradigms Personal Reconfigurable Parallel Distributed Ubiquitous Autonomic
25 Autonomic Motivation: rapidly growing complexity of integrating, managing and operating computer systems introduced by IBM in 2001 Inspired by Human ANS Self management includes: self configuration organization protection governing recovery healing autonomy Complex yet self-managing adaptation optimization diagnosis of faults Introduction to Cloud
26 Introduction to Cloud Carnegie Mellon Grid Super Utility Cluster Pervasive Cloud Mobile Existing Paradigms Personal Reconfigurable Parallel Distributed Ubiquitous Autonomic
27 Mobile You can use computing technology on the move Since 1990s Intermittent connectivity Limited Bandwidth Mobile device maturity Introduction to Cloud
28 Introduction to Cloud Carnegie Mellon Grid Super Utility Cluster Pervasive Cloud Mobile Existing Paradigms Personal Reconfigurable Parallel Distributed Ubiquitous Autonomic
29 Utility Water, gas, and electricity are provided to every home and business as commodity services You get connected to the utility companies public infrastructure You get these utility services on demand And you pay as you use Utility is doing same for computing resources (processing power, bandwidth, data storage, and enterprise software services) Thought of by 1960s but re surfaced late 90s If computers of the kind I have advocated become the computers of the future, then computing may someday be organized as a public utility just as the telephone system is a public utility... The computer utility could become the basis of a new and important industry. John McCarthy, MIT Centennial in Introduction to Cloud
30 Introduction to Cloud Carnegie Mellon Grid Super Utility Cluster Pervasive Cloud Mobile Existing Paradigms Personal Reconfigurable Parallel Distributed Ubiquitous Autonomic
31 Existing Paradigms Blue Group Super Grid Cluster Parallel Distributed Introduction to Cloud
32 Blue Group Distributed Using distributed systems to solve large problems. Distributed System: multiple autonomous computers connected through a communication network The system has a distributed memory where each processor has its private memory. Information exchanged using communication models, ex: MPI Introduction to Cloud
33 Blue Group Distributed Cluster : Characteristics: tightly coupled computers single system image Centralized Job management & scheduling system Better performance and availability and more costeffectiveness over single computer with same capabilities Since 1987 Grid : According to Gartner, "a grid is a collection of resources owned by multiple organizations that is coordinated to allow them to solve a common problem." Characteristics: loosely coupled no Single System Image distributed Job Management & scheduling Originated early 1990s Introduction to Cloud
34 What is Parallel Calculations of large problems are divided into smaller parts and carried out simultaneously/concurrently on different processors. instructions Problem.. CPU time instructions.. CPU Problem.... CPU CPU Introduction to Cloud time
35 Parallel All have access to a shared memory that is used to exchange information between processors Shared Memory Uniform Access (UASM) Non-Uniform Access (NUASM) Hybrid Distributed-Shared Memory Introduction to Cloud Source:
36 Blue Group Super Thousands of processors Used for compute intensive problems Days instead of Years!!! introduced in the 1960s Introduction to Cloud
37 Blue Group Parallel Super Cluster Could be Grid Distributed Introduction to Cloud
38 Introduction to Cloud Carnegie Mellon Grid Super Utility Cluster Pervasive Cloud Mobile Existing Paradigms Personal Reconfigurable Parallel Distributed Ubiquitous Autonomic
39 Existing Paradigms Green Group Ubiquitous Pervasive Introduction to Cloud
40 Green Group Ubiquitous= seeming to be in all places Pervasive= present or noticeable in every part of a thing or place Information processing engaged in everyday s activities and objects. Term used since 1980s Different models but same vision: Small, inexpensive, robust devices distributed throughout everyday s life Introduction to Cloud
41 Introduction to Cloud Carnegie Mellon Grid Super Utility Cluster Pervasive Cloud Mobile Existing Paradigms Personal Reconfigurable Parallel Distributed Ubiquitous Autonomic
42 Existing Paradigms How about cloud computing? Cloud Introduction to Cloud
43 Introduction to Cloud Carnegie Mellon Grid Super Utility Cluster Pervasive Cloud Mobile Existing Paradigms How about cloud computing? Reconfigurable Parallel Personal Distributed Ubiquitous Autonomic
44 Think of it this way Banking Introduction to Cloud
45 Think of it this way Power/ heat/electricity/water supply to your home Before Now Introduction to Cloud
46 Think of it this way Transportation Which one should you pick? Should you buy/rent? Introduction to Cloud
47 Cloud Think of it as Internet Computation done over the internet Enabled through: High Bandwidth and High Speed Internet Utility Virtualization Introduction to Cloud
48 Cloud Services Three basic services: Software as a Service (SAAS) model Apps through browser Platform as a Service (PAAS) model Delivery of a computing platform for custom software development as a service Infrastructure as a Service (IAAS) model Deliver of computer infrastructure as a service XAAS, the list continues to grow Introduction to Cloud
49 Interesting Videos SaaS: ure=related Virtualization: e=related Cloud : Introduction to Cloud
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