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Download PDF Architecting The Cloud Design Decisions For Cloud Computing Service Model by Michael J. Kavis

Posted by Harapan Posted on 17.12 with 1 comment


Sinopsis

There was a time when every household, town, farm, or village had its own water well. Today, shared public utilities give us access to clean water by simply turning on the tap; cloud computing works in a similar fashion. Just like water from the tap in your kitchen, cloud computing services can be turned on or off quickly as needed. Like at the water company, there is a team of dedicated professionals making sure the service provided is safe, secure, and available on a 24/7 basis. When the tap isn’t on, not only are you saving water, but you aren’t paying for resources you don’t currently need.

In 2009, I was invited to the IBM Impact conference in Las Vegas as a guest blogger and analyst. Cloud computing was a vastly misunderstood term at that time, and there were very few enterprises leveraging any cloud services other than a few of the mature SaaS solutions like Salesforce.com and Concur’s expense management software. I witnessed some very intelligent senior IT people from various companies scoffing at the term cloud computing. I can still hear the lines: “We were doing this on the mainframe in the ’60s” and “There is nothing new here, this is just a fad.” At that time, my team of one developer was testing a prototype that was executing hundreds of thousands concurrent point-of-sale (POS) transactions to the cloud and back in subsecond response time on a virtual cloud server, costing us about half a dollar an hour charged against my CEO’s credit card. I started to think about how much it would cost to implement the infrastructure, licenses, and professional services to perform a proof-of-concept on-premises. I also thought about how many months it would take to go through a vendor evaluation, the procurement process, and all of the steps required to make a capital expenditure that would have been required to buy servers from a large vendor like IBM. At the end of several months, I would finally have all the hardware, software, licenses, and professional services that my developer would need to test his proof-of-concept. My start-up would have been out of cash by then, and all I would have to show for it would have been a few lunches paid for and a nice golf shirt with the vendor’s logo on it.


Content

  1. Why Cloud, Why Now?
  2. Evolution of Cloud Computing
  3. Enter the Cloud
  4. Start-Up Case Study: Instagram, from Zero to a Billion Overnight
  5. Established Company Case Study: Netflix, Shifting from On-Premises to the Cloud
  6. Government Case Study: NOAA, E-mail, and Collaboration in the Cloud
  7. Not-for-Profit Case Study: Obama Campaign, Six-Month Shelf-Life with One Big Peak
  8. Cloud Service Models
  9. Platform as a Service
  10. Software as a Service
  11. Deployment Models
  12. Cloud Computing Worst Practices
  13. Avoiding Failure When Moving to the Cloud
  14. Migrating Applications to the Cloud 
  15. Misguided Expectations
  16. Misinformed about Cloud Security
  17. Selecting a Favorite Vendor, Not an Appropriate Vendor 
  18. Outages and Out-of-Business Scenarios
  19. Underestimating the Impacts of Organizational Change
  20. Skills Shortage
  21. Misunderstanding Customer Requirements
  22. Unexpected Costs
  23. It Starts with Architecture
  24. The Importance of Why, Who, What, Where, When, and How
  25. Start with the Business Architecture
  26. Identify the Problem Statement (Why)
  27. Evaluate User Characteristics (Who)
  28. Identify Business and Technical Requirements (What)
  29. Visualize the Service Consumer Experience (Where)
  30. Identify the Project Constraints (When and with What)
  31. Understand Current State Constraints (How)
  32. Choosing the Right Cloud Service Model
  33. Considerations When Choosing a Cloud Service Model
  34. When to Use SaaS
  35. When to Use PaaS
  36. When to Use IaaS
  37. Common Cloud Use Cases
  38. The Key to the Cloud
  39. Why REST?
  40. The Challenges of Migrating Legacy Systems to the Cloud
  41. Auditing in the Cloud
  42. Data and Cloud Security
  43. Auditing Cloud Applications
  44. Regulations in the Cloud
  45. Audit Design Strategies
  46. Data Considerations in the Cloud
  47. Data Characteristics
  48. Multitenant or Single Tenant  
  49. Choosing Data Store Types
  50. Security Design in the Cloud
  51. The Truth about Data in the Cloud
  52. How Much Security Is Required
  53. Responsibilities for Each Cloud Service Model
  54. Security Strategies 
  55. Areas of Focus
  56. Creating a Centralized Logging Strategy
  57. Log File Uses
  58. Logging Requirements
  59. SLA Management
  60. Factors That Impact SLAs
  61. Defining SLAs
  62. Managing Vendor SLAs
  63. Monitoring Strategies
  64. Proactive vs. Reactive Monitoring
  65. What Needs to Be Monitored?
  66. Monitoring Strategies by Category
  67. Monitoring by Cloud Service Level
  68. Disaster Recovery Planning
  69. What Is the Cost of Downtime?
  70. Disaster Recovery Strategies for IaaS
  71. Recovering from a Disaster in the Primary Data Center
  72. Disaster Recovery Strategies for PaaS
  73. Disaster Recovery Strategies for SaaS
  74. Disaster Recovery Hybrid Clouds
  75. Leveraging a DevOps Culture to Deliver Software Faster and More Reliably
  76. Developing the DevOps Mind-Set
  77. Automate Infrastructure
  78. Automate Deployments
  79. Design Feature Flags
  80. Measure, Monitor, and Experiment
  81. Continuous Integration and Continuous Delivery
  82. Assessing the Organizational Impact of the Cloud Model
  83. Enterprise Model vs. Elastic Cloud Model
  84. IT Impact
  85. Business Impacts
  86. Organization Change Planning
  87. Change in the Real World
  88. Final Thoughts
  89. The Cloud Is Evolving Rapidly
  90. Cloud Culture
  91. New Business Models
  92. PaaS Is the Game Changer





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