Introduction to Cloud Computing

Introduction to Cloud Computing

7 minute read

Introduction to Cloud Computing

This introduction to Cloud Computing covers all aspects of the field drawing on industry and academic advances. It makes use of analyses from the Gartner group on future Industry trends. The presentation is broken into 21 parts starting with a survey of all the material covered. Note this first part is A while the substance of the talk is in parts B to U.

Introduction - Part A {#s:cloud-fundamentals-a}

  • Parts B to D define cloud computing, its key concepts and how it is situated in the data center space
  • The next part E reviews virtualization technologies comparing containers and hypervisors
  • Part F is the first on Gartner’s Hypecycles and especially those for emerging technologies in 2017 and 2016
  • Part G is the second on Gartner’s Hypecycles with Emerging Technologies hypecycles and the Priority matrix at selected times 2008-2015
  • Parts H and I cover Cloud Infrastructure with Comments on trends in the data center and its technologies and the Gartner hypecycle and priority matrix on Infrastructure Strategies and Compute Infrastructure
  • Part J covers Cloud Software with HPC-ABDS(High Performance Computing enhanced Apache Big Data Stack) with over 350 software packages and how to use each of its 21 layers
  • Part K is first on Cloud Applications covering those from industry and commercial usage patterns from NIST
  • Part L is second on Cloud Applications covering those from science where area called cyberinfrastructure; we look at the science usage pattern from NIST
  • Part M is third on Cloud Applications covering the characterization of applications using the NIST approach.
  • Part N covers Clouds and Parallel Computing and compares Big Data and Simulations
  • Part O covers Cloud storage: Cloud data approaches: Repositories, File Systems, Data lakes
  • Part P covers HPC and Clouds with The Branscomb Pyramid and Supercomputers versus clouds
  • Part Q compares Data Analytics with Simulation with application and software implications
  • Part R compares Jobs from Computer Engineering, Clouds, Design and Data Science/Engineering
  • Part S covers the Future with Gartner cloud computing hypecycle and priority matrix, Hyperscale computing, Serverless and FaaS, Cloud Native and Microservices
  • Part T covers Security and Blockchain
  • Part U covers fault-tolerance

This lecture describes the contents of the following 20 parts (B to U).

Introduction - Part B - Defining Clouds I {#s:cloud-fundamentals-b}

B: Defining Clouds I

  • Basic definition of cloud and two very simple examples of why virtualization is important.
  • How clouds are situated wrt HPC and supercomputers
  • Why multicore chips are important
  • Typical data center

Introduction - Part C - Defining Clouds II {#s:cloud-fundamentals-c}

C: Defining Clouds II

  • Service-oriented architectures: Software services as Message-linked computing capabilities
  • The different aaS’s: Network, Infrastructure, Platform, Software
  • The amazing services that Amazon AWS and Microsoft Azure have
  • Initial Gartner comments on clouds (they are now the norm) and evolution of servers; serverless and microservices

Introduction - Part D - Defining Clouds III {#s:cloud-fundamentals-d}

D: Defining Clouds III

  • Cloud Market Share
  • How important are they?
  • How much money do they make?

Introduction - Part E - Virtualization {#s:cloud-fundamentals-e}

E: Virtualization

  • Virtualization Technologies, Hypervisors and the different approaches
  • KVM Xen, Docker and Openstack
  • Several web resources are listed

Introduction - Part F - Technology Hypecycle I {#s:cloud-fundamentals-f}

F:Technology Hypecycle I

  • Gartner’s Hypecycles and especially that for emerging technologies in 2017 and 2016
  • The phases of hypecycles
  • Priority Matrix with benefits and adoption time
  • Today clouds have got through the cycle (they have emerged) but features like blockchain, serverless and machine learning are on cycle
  • Hypecycle and Priority Matrix for Data Center Infrastructure 2017

Introduction - Part G - Technology Hypecycle II {#s:cloud-fundamentals-g}

G: Technology Hypecycle II

  • Emerging Technologies hypecycles and Priority matrix at selected times 2008-2015
  • Clouds star from 2008 to today
  • They are mixed up with transformational and disruptive changes
  • The route to Digital Business (2015)

Introduction - Part H - IaaS I {#s:cloud-fundamentals-h}

H: Cloud Infrastructure I

  • Comments on trends in the data center and its technologies
  • Clouds physically across the world
  • Green computing and fraction of world’s computing ecosystem in clouds

Introduction - Part I - IaaS II {#s:cloud-fundamentals-i}

I: Cloud Infrastructure II

  • Gartner hypecycle and priority matrix on Infrastructure Strategies and Compute Infrastructure
  • Containers compared to virtual machines
  • The emergence of artificial intelligence as a dominant force

Introduction - Part J - Cloud Software {#s:cloud-fundamentals-j}

J: Cloud Software

  • HPC-ABDS(High Performance Computing enhanced Apache Big Data Stack) with over 350 software packages and how to use each of 21 layers
  • Google’s software innovations
  • MapReduce in pictures
  • Cloud and HPC software stacks compared
  • Components need to support cloud/distributed system programming
  • Single Program/Instruction Multiple Data SIMD SPMD

Introduction - Part K - Applications I {#s:cloud-fundamentals-k}

K: Cloud Applications I

  • Big Data in Industry/Social media; a lot of best examples have NOT been updated so some slides old but still make the correct points
  • Some of the business usage patterns from NIST

Introduction - Part L - Applications II {#s:cloud-fundamentals-l}

L: Cloud Applications II

  • Clouds in science where area called cyberinfrastructure;
  • The science usage pattern from NIST
  • Artificial Intelligence from Gartner

Introduction - Part M - Applications III {#s:cloud-fundamentals-m}

M: Cloud Applications III

  • Characterize Applications using NIST approach
  • Internet of Things
  • Different types of MapReduce

Introduction - Part N - Parallelism {#s:cloud-fundamentals-n}

N: Clouds and Parallel Computing

  • Parallel Computing in general
  • Big Data and Simulations Compared
  • What is hard to do?

Introduction - Part O - Storage {#s:cloud-fundamentals-o}

O: Cloud Storage

  • Cloud data approaches
  • Repositories, File Systems, Data lakes

Introduction - Part P - HPC in the Cloud {#s:cloud-fundamentals-p}

P: HPC and Clouds

  • The Branscomb Pyramid
  • Supercomputers versus clouds
  • Science Computing Environments

Introduction - Part Q - Analytics and Simulation {#s:cloud-fundamentals-q}

Q: Comparison of Data Analytics with Simulation

  • Structure of different applications for simulations and Big Data
  • Software implications
  • Languages

Introduction - Part R - Jobs {#s:cloud-fundamentals-r}

R: Availability of Jobs in different areas

  • Computer Engineering
  • Clouds
  • Design
  • Data Science/Engineering

Introduction - Part S - The Future {#s:cloud-fundamentals-s}

S: The Future

  • Gartner cloud computing hypecycle and priority matrix highlights:

    • Hyperscale computing
    • Serverless and FaaS
    • Cloud Native
    • Microservices

Introduction - Part T - Security {#s:cloud-fundamentals-t}

T: Security

  • CIO Perspective
  • Blockchain

Introduction - Part U - Fault Tolerance {#s:cloud-fundamentals-u}

U: Fault Tolerance

  • S3 Fault Tolerance
  • Application Requirements

© 2018 GitHub, Inc. Terms Privacy Security Status Help Contact GitHub Pricing API Training Blog About Press h to open a hovercard with more details.

Last modified June 17, 2021 : add aliasses (6b7beab5)