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Tech

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trends and cutting edge technologies

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Tech

  1. 1. Trends and Cutting Edge Technologies
  2. 2. 3rd Platform Transformation http://www.idc.com/prodserv/3rd-platform/ Cloud Big Data Mobile Social 4 Pillars
  3. 3. 1st Platform Mainframe, Mini-con & Terminal1951 UNIVAC 1964 IBM System/360 Millions of Users 1965 DEC PDP-8 1969 UNIX
  4. 4. 2nd Platform Hundreds of Millions of User 1983 TCP/IP 1984 PC/AT 5170 Mainframe, Mini-con & Terminal1951 UNIVAC 1964 IBM System/360 Millions of Users 1965 DEC PDP-8 1969 UNIX LAN/Internet, Client/Server & PC
  5. 5. 3rd Platform LAN/Internet, Client/Server & PC Mobile, Cloud, Big Data, Social & Mobile Devices Millions of Apps Billions of Users Trillions of Things 1991 Web 1998 Google 1994 Amazon 2004 Facebook 2014 HTML5 2015 HTTP/2 1983 TCP/IP 1984 PC/AT 5170 Mainframe, Mini-con & Terminal1951 UNIVAC 1964 IBM System/360 Millions of Users 1965 DEC PDP-8 1969 UNIX Hundreds of Millions of User
  6. 6. Keywords Modern Web Big data Cloud IoT DevOps
  7. 7. Modern-Web
  8. 8. Web 1.0 Web 2.0 Modern Web Web 1.0 (1989-2003) Simple HTTP & HTML Web 2.0 (2004-2010) Web 1.0 + Ajax & Web Services Modern-Web (2011-) Web 2.0 + HTML5, Mobile and Cloud
  9. 9. May 2011 How Web and Cloud Computing Will Drive Your IT Strategies?
  10. 10. Tim O'Reilly Web 2.0 is the Design Patterns and Business Models for the Next Generation of Software
  11. 11. HTML5+CSS3+JavaScript
  12. 12. JavaScript
  13. 13. History Netscape Navigator 2.0 Brendan Eich
  14. 14. 1997 ECMAScript (Ecma-262) was published http://www.ecma-international.org/publications/standards/Ecma- 262.htm European Computer Manufacturers Association
  15. 15. The trend of JavaScript is on the rise
  16. 16. Rank of Top Languages 2008-2015 http://venturebeat.com/2015/08/19/here-are-the-top-10-programming-languages-used-on-github/
  17. 17. RedMonk Programming Languages Ranking http://redmonk.com/sogrady/2016/02/19/language-rankings-1-16/
  18. 18. The 9 Most In-Demand Programming Languages of 2016 http://www.codingdojo.com/blog/9-most-in-demand-programming-languages-of-2016/
  19. 19. Developer Survey Results 2016 http://stackoverflow.com/research/developer-survey-2016
  20. 20. The Problems of Traditional Web Applications Server-push Client-pull Architecture
  21. 21. Polling with Ajax Asynchronous UPDATE JavaScript XMLHttpRequest
  22. 22. Long Polling with Comet UPDATE Keep open
  23. 23. HTML5 WebSocket RFC 6455 The WebSocket Protocol
  24. 24. The C10K Problem 10,000・・・
  25. 25. Thread Model スレッド スレッド スレッド リクエスト リクエスト リクエスト Webサーバー Multi Thread & Blocking I/O
  26. 26. Event Loop Model Single Thread & Non-blocking I/O イベント・キュー リクエスト リクエスト リクエスト Webサーバー イベント・ループ スレッド
  27. 27. SPA Single Page Application Traditional Web Application SPA Web Application • CRUD • View • CRUD • View
  28. 28. Package Manager MyProject Internet dependency
  29. 29. NPM https://www.npmjs.com/
  30. 30. Bower http://bower.io/ made by
  31. 31. Server-sideClient-side Bower Package Manager
  32. 32. Task Runner App Task Runner Plugin • Transpile • Checking code quality • Compiling templates • Combine / Concatenate • Minify / Compression • Running tests • etc… Automating Repetitive tasks Configuration Plugin Plugin
  33. 33. http://gruntjs.com/ http://gulpjs.com/ Gulp Task Runner
  34. 34. Unit Testing https://karma-runner.github.io/0.13/index.html http://jasmine.github.io/ https://qunitjs.com/
  35. 35. LAMP to MEAN Linux Apache MySQL PHP/Perl MongDB Express.js Angular.js Node.js
  36. 36. Cloud
  37. 37. History 1982 Stanford University "The Network is the Computer"
  38. 38. Eric Schmidt, Google 2006 "The network will truly be the computer" Today we live in the clouds.
  39. 39. http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf What is Cloud?
  40. 40. Three Service Models IaaS (Infrastructure as a Service) Server & OS PaaS (Platform as a Service) Middleware (DB, AP Server, …) SaaS (Software as a Service) Application
  41. 41. IaaS Platforms • Amazon Web Services • Microsoft Azure • Salesforce1 Platform • IBM Softlayer • Google Cloud Platform • etc…
  42. 42. PaaS Platforms • Google App Engine • Heroku • RedHat OpenShift • IBM Bluemix • Oracle Java Cloud Services
  43. 43. Deployment Models Public Cloud Private Cloud Community Cloud Hybrid Cloud
  44. 44. 2015: State of the Cloud Report 93% of respondents are using clouds Public Cloud Only Private Cloud Only 30% 5%58% Public & Private
  45. 45. Cloud Infrastructure Revenue Growth 1,500 1,000 500 AWS IBM Google AWS Google IBM Microsoft Salesforce Q1 2014 Q1 2015 Microsoft Salesforce ($m)
  46. 46. The Case Example (1) EC2 Kinesis DWHStream data Redshift BI Tools Visualization Filtering
  47. 47. The Case Example (2) Kinesis DynamoDB Redshift API LINE
  48. 48. Open Cloud Platform https://cloudstack.apache.org/ https://www.openstack.org/
  49. 49. Virtualization
  50. 50. PhysicalVirtual ClusteringVirtualization VM (Virtual Machine)
  51. 51. Type A: Host OS Physical Machine Host OS H/W Application Virtual Machine VMM (Virtual Machine Monitor) Virtual HW Guest OS Application Virtual Machine Application Virtual HW Guest OS Application Application
  52. 52. Type B: Hypervisor Physical Machine H/W Virtual Machine Hypervisor Virtual HW Guest OS Application Virtual Machine Application Virtual HW Guest OS Application Application Micro Kernel Virtual Machine
  53. 53. Type B: Hypervisor Physical Machine H/W Virtual Machine Hypervisor Virtual HW Guest OS Application Virtual Machine Application Virtual HW Guest OS Application Application Monolithic Kernel
  54. 54. Hypervisor Products Monolithic Kernel Micro Kernel
  55. 55. Big data
  56. 56. Trends Oct, 2012 Big data Expo 2012
  57. 57. The 4 V's of Big Data
  58. 58. Growth of the Digital Universe Zeta byte
  59. 59. How big is the Volume? 2.5EB/day 1,000, 000, 000, 000, 000, 000, 000 KMGTPEZ Blue-ray 1 Billion 1TB 10,000 250,000
  60. 60. What is Variety?
  61. 61. 100TB/day 30PB/day 30TB/day 500TB/day 3 billion 3 billion
  62. 62. “Big data really is about having insights and making an impact on your business. If you aren't taking advantage of the data you're collecting, then you just have a pile of data, you don't have big data.” Big data is Facebook
  63. 63. The Problems 1TB 2-3 hours read
  64. 64. Scale Up The simplest solution
  65. 65. but… Performance Cost
  66. 66. Scale Out ・・・ The Best Solution
  67. 67. Apache Hadoop A framework for the Distributed processing http://hadoop.apache.org/
  68. 68. MapReduce X1 Y1 Z1 X2 Y2 Z2 X3 Y3 Z3 X1 X2 X3 Y1 Y2 Y3 Z1 Z2 Z3 X Y Z Map Reduce
  69. 69. Hadoop MapReduce Map Phase Reduce PhaseInput Output Shuffle & Sort Key Value
  70. 70. Key-Value & MapReduce Map Phase Reduce Phase K1 V1 K2 LIST K2 V2 LIST V2 LIST K3 V3 Shuffle & Sort
  71. 71. Ex: Word Count To Be Or Not To Be 1 1 1 1 1 1 Be Or To To Be Not 1 1 1 1 1 1 Be Or Not To 1 1 1 1 Map ReduceShuffle & Sort Input text To Be Or Not To Be Be Or Not To 2 1 1 2 1 1 Output
  72. 72. Apache Spark On Memory Stream Computing Spark SQL Spark Streaming MLib GraphX Spark Core Spark http://spark.apache.org/ Data
  73. 73. NoSQL NoSQL Meetup Group (San Francisco : 2009-06) NoSQL EAST (Atlanta : 2009-10) http://www.meetup.com/SFNoSQL / https://nosqleast.com/2009/
  74. 74. Trends https://blogs.the451group.com/information_management/?s=nosql https://www.javacodegeeks.com/2014/09/nosql-job-trends-august- 2014.html
  75. 75. IoT
  76. 76. What is IoT?
  77. 77. The Growth of IoT 2020
  78. 78. Raspberry PI Intel Edison Intel Curie
  79. 79. Facebook's 10-year Roadmap https://developers.facebook.com/videos F8 2016 12 Apr. Drone, AI, VR/AR
  80. 80. DevOps
  81. 81. What is DevOps? Dev Ops Developer & Operations a culture, movement or practice emphasizes the collaboration and communication automating the process of software delivery and changes
  82. 82. 10+ Deploys Per Day: Dev and Ops Cooperation at Flickr http://www.slideshare.net/jallspaw/10-deploys-per-day-dev-and-ops-cooperation-at-flickr John Allspaw and Paul Hammond https://www.youtube.com/watch?v=LdOe18KhtT4
  83. 83. Traditional Thinking To add new features To keep the site stable and fast Dev Ops
  84. 84. Traditional Thinking To enable the business Dev Ops
  85. 85. Tools and Cultures Dev Ops Culture
  86. 86. Five Tools 1. Automated infrastructure 2. Shared version control 3. One step build and deploy 4. Feature flags 5. Shared metrics 6. IRC and IM robots
  87. 87. Four Cultures 1. Respect 2. Trust 3. Healthy attitude about failure 4. Avoiding blame
  88. 88. CI Tools Source code Repository Container Images User Test Infrastructure as a Code (Immutable Infrastructure Commit Detect Deploy Pull Test Environment Production Environment Development
  89. 89. Trends of DevOps Tools 18% 19% 35% 10% 10% 11% 28% 24% 13% 10% 6% 3% RightScale 2015 State of the Cloud Report Use today Plan to use

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