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📄 Contents

␡
  1. Management Reference Guide
  2. Table of Contents
  3. Introduction
  4. Strategic Management
  5. Establishing Goals, Objectives, and Strategies
  6. Aligning IT Goals with Corporate Business Goals
  7. Utilizing Effective Planning Techniques
  8. Developing Worthwhile Mission Statements
  9. Developing Worthwhile Vision Statements
  10. Instituting Practical Corporate Values
  11. Budgeting Considerations in an IT Environment
  12. Introduction to Conducting an Effective SWOT Analysis
  13. IT Governance and Disaster Recovery, Part One
  14. IT Governance and Disaster Recovery, Part Two
  15. Customer Management
  16. Identifying Key External Customers
  17. Identifying Key Internal Customers
  18. Negotiating with Customers and Suppliers—Part 1: An Introduction
  19. Negotiating With Customers and Suppliers—Part 2: Reaching Agreement
  20. Negotiating and Managing Realistic Customer Expectations
  21. Service Management
  22. Identifying Key Services for Business Users
  23. Service-Level Agreements That Really Work
  24. How IT Evolved into a Service Organization
  25. FAQs About Systems Management (SM)
  26. FAQs About Availability (AV)
  27. FAQs About Performance and Tuning (PT)
  28. FAQs About Service Desk (SD)
  29. FAQs About Change Management (CM)
  30. FAQs About Configuration Management (CF)
  31. FAQs About Capacity Planning (CP)
  32. FAQs About Network Management
  33. FAQs About Storage Management (SM)
  34. FAQs About Production Acceptance (PA)
  35. FAQs About Release Management (RM)
  36. FAQs About Disaster Recovery (DR)
  37. FAQs About Business Continuity (BC)
  38. FAQs About Security (SE)
  39. FAQs About Service Level Management (SL)
  40. FAQs About Financial Management (FN)
  41. FAQs About Problem Management (PM)
  42. FAQs About Facilities Management (FM)
  43. Process Management
  44. Developing Robust Processes
  45. Establishing Mutually Beneficial Process Metrics
  46. Change Management—Part 1
  47. Change Management—Part 2
  48. Change Management—Part 3
  49. Audit Reconnaissance: Releasing Resources Through the IT Audit
  50. Problem Management
  51. Problem Management–Part 2: Process Design
  52. Problem Management–Part 3: Process Implementation
  53. Business Continuity Emergency Communications Plan
  54. Capacity Planning – Part One: Why It is Seldom Done Well
  55. Capacity Planning – Part Two: Developing a Capacity Planning Process
  56. Capacity Planning — Part Three: Benefits and Helpful Tips
  57. Capacity Planning – Part Four: Hidden Upgrade Costs and
  58. Improving Business Process Management, Part 1
  59. Improving Business Process Management, Part 2
  60. 20 Major Elements of Facilities Management
  61. Major Physical Exposures Common to a Data Center
  62. Evaluating the Physical Environment
  63. Nightmare Incidents with Disaster Recovery Plans
  64. Developing a Robust Configuration Management Process
  65. Developing a Robust Configuration Management Process – Part Two
  66. Automating a Robust Infrastructure Process
  67. Improving High Availability — Part One: Definitions and Terms
  68. Improving High Availability — Part Two: Definitions and Terms
  69. Improving High Availability — Part Three: The Seven R's of High Availability
  70. Improving High Availability — Part Four: Assessing an Availability Process
  71. Methods for Brainstorming and Prioritizing Requirements
  72. Introduction to Disk Storage Management — Part One
  73. Storage Management—Part Two: Performance
  74. Storage Management—Part Three: Reliability
  75. Storage Management—Part Four: Recoverability
  76. Twelve Traits of World-Class Infrastructures — Part One
  77. Twelve Traits of World-Class Infrastructures — Part Two
  78. Meeting Today's Cooling Challenges of Data Centers
  79. Strategic Security, Part One: Assessment
  80. Strategic Security, Part Two: Development
  81. Strategic Security, Part Three: Implementation
  82. Strategic Security, Part Four: ITIL Implications
  83. Production Acceptance Part One – Definition and Benefits
  84. Production Acceptance Part Two – Initial Steps
  85. Production Acceptance Part Three – Middle Steps
  86. Production Acceptance Part Four – Ongoing Steps
  87. Case Study: Planning a Service Desk Part One – Objectives
  88. Case Study: Planning a Service Desk Part Two – SWOT
  89. Case Study: Implementing an ITIL Service Desk – Part One
  90. Case Study: Implementing a Service Desk Part Two – Tool Selection
  91. Ethics, Scandals and Legislation
  92. Outsourcing in Response to Legislation
  93. Supplier Management
  94. Identifying Key External Suppliers
  95. Identifying Key Internal Suppliers
  96. Integrating the Four Key Elements of Good Customer Service
  97. Enhancing the Customer/Supplier Matrix
  98. Voice Over IP, Part One — What VoIP Is, and Is Not
  99. Voice Over IP, Part Two — Benefits, Cost Savings and Features of VoIP
  100. Application Management
  101. Production Acceptance
  102. Distinguishing New Applications from New Versions of Existing Applications
  103. Assessing a Production Acceptance Process
  104. Effective Use of a Software Development Life Cycle
  105. The Role of Project Management in SDLC— Part 2
  106. Communication in Project Management – Part One: Barriers to Effective Communication
  107. Communication in Project Management – Part Two: Examples of Effective Communication
  108. Safeguarding Personal Information in the Workplace: A Case Study
  109. Combating the Year-end Budget Blitz—Part 1: Building a Manageable Schedule
  110. Combating the Year-end Budget Blitz—Part 2: Tracking and Reporting Availability
  111. References
  112. Developing an ITIL Feasibility Analysis
  113. Organization and Personnel Management
  114. Optimizing IT Organizational Structures
  115. Factors That Influence Restructuring Decisions
  116. Alternative Locations for the Help Desk
  117. Alternative Locations for Database Administration
  118. Alternative Locations for Network Operations
  119. Alternative Locations for Web Design
  120. Alternative Locations for Risk Management
  121. Alternative Locations for Systems Management
  122. Practical Tips To Retaining Key Personnel
  123. Benefits and Drawbacks of Using IT Consultants and Contractors
  124. Deciding Between the Use of Contractors versus Consultants
  125. Managing Employee Skill Sets and Skill Levels
  126. Assessing Skill Levels of Current Onboard Staff
  127. Recruiting Infrastructure Staff from the Outside
  128. Selecting the Most Qualified Candidate
  129. 7 Tips for Managing the Use of Mobile Devices
  130. Useful Websites for IT Managers
  131. References
  132. Automating Robust Processes
  133. Evaluating Process Documentation — Part One: Quality and Value
  134. Evaluating Process Documentation — Part Two: Benefits and Use of a Quality-Value Matrix
  135. When Should You Integrate or Segregate Service Desks?
  136. Five Instructive Ideas for Interviewing
  137. Eight Surefire Tips to Use When Being Interviewed
  138. 12 Helpful Hints To Make Meetings More Productive
  139. Eight Uncommon Tips To Improve Your Writing
  140. Ten Helpful Tips To Improve Fire Drills
  141. Sorting Out Today’s Various Training Options
  142. Business Ethics and Corporate Scandals – Part 1
  143. Business Ethics and Corporate Scandals – Part 2
  144. 12 Tips for More Effective Emails
  145. Management Communication: Back to the Basics, Part One
  146. Management Communication: Back to the Basics, Part Two
  147. Management Communication: Back to the Basics, Part Three
  148. Asset Management
  149. Managing Hardware Inventories
  150. Introduction to Hardware Inventories
  151. Processes To Manage Hardware Inventories
  152. Use of a Hardware Inventory Database
  153. References
  154. Managing Software Inventories
  155. Business Continuity Management
  156. Ten Lessons Learned from Real-Life Disasters
  157. Ten Lessons Learned From Real-Life Disasters, Part 2
  158. Differences Between Disaster Recovery and Business Continuity , Part 1
  159. Differences Between Disaster Recovery and Business Continuity , Part 2
  160. 15 Common Terms and Definitions of Business Continuity
  161. The Federal Government’s Role in Disaster Recovery
  162. The 12 Common Mistakes That Cause BIAs To Fail—Part 1
  163. The 12 Common Mistakes That Cause BIAs To Fail—Part 2
  164. The 12 Common Mistakes That Cause BIAs To Fail—Part 3
  165. The 12 Common Mistakes That Cause BIAs To Fail—Part 4
  166. Conducting an Effective Table Top Exercise (TTE) — Part 1
  167. Conducting an Effective Table Top Exercise (TTE) — Part 2
  168. Conducting an Effective Table Top Exercise (TTE) — Part 3
  169. Conducting an Effective Table Top Exercise (TTE) — Part 4
  170. The 13 Cardinal Steps for Implementing a Business Continuity Program — Part One
  171. The 13 Cardinal Steps for Implementing a Business Continuity Program — Part Two
  172. The 13 Cardinal Steps for Implementing a Business Continuity Program — Part Three
  173. The 13 Cardinal Steps for Implementing a Business Continuity Program — Part Four
  174. The Information Technology Infrastructure Library (ITIL)
  175. The Origins of ITIL
  176. The Foundation of ITIL: Service Management
  177. Five Reasons for Revising ITIL
  178. The Relationship of Service Delivery and Service Support to All of ITIL
  179. Ten Common Myths About Implementing ITIL, Part One
  180. Ten Common Myths About Implementing ITIL, Part Two
  181. Characteristics of ITIL Version 3
  182. Ten Benefits of itSMF and its IIL Pocket Guide
  183. Translating the Goals of the ITIL Service Delivery Processes
  184. Translating the Goals of the ITIL Service Support Processes
  185. Elements of ITIL Least Understood, Part One: Service Delivery Processes
  186. Case Study: Recovery Reactions to a Renegade Rodent
  187. Elements of ITIL Least Understood, Part Two: Service Support
  188. Case Studies
  189. Case Study — Preparing for Hurricane Charley
  190. Case Study — The Linux Decision
  191. Case Study — Production Acceptance at an Aerospace Firm
  192. Case Study — Production Acceptance at a Defense Contractor
  193. Case Study — Evaluating Mainframe Processes
  194. Case Study — Evaluating Recovery Sites, Part One: Quantitative Comparisons/Natural Disasters
  195. Case Study — Evaluating Recovery Sites, Part Two: Quantitative Comparisons/Man-made Disasters
  196. Case Study — Evaluating Recovery Sites, Part Three: Qualitative Comparisons
  197. Case Study — Evaluating Recovery Sites, Part Four: Take-Aways
  198. Disaster Recovery Test Case Study Part One: Planning
  199. Disaster Recovery Test Case Study Part Two: Planning and Walk-Through
  200. Disaster Recovery Test Case Study Part Three: Execution
  201. Disaster Recovery Test Case Study Part Four: Follow-Up
  202. Assessing the Robustness of a Vendor’s Data Center, Part One: Qualitative Measures
  203. Assessing the Robustness of a Vendor’s Data Center, Part Two: Quantitative Measures
  204. Case Study: Lessons Learned from a World-Wide Disaster Recovery Exercise, Part One: What Did the Team Do Well
  205. (d) Case Study: Lessons Learned from a World-Wide Disaster Recovery Exercise, Part Two

In the first piece of this four-part series on improving high availability, I offered up and explained a definition for availability and presented some key terms used with this process. In this second part I compare and contrast additional terms associated with this process, discuss desirable traits of an availability process owner, present some effective methods for measuring availability.

Differentiating Slow Response from Downtime

Slow response can infuriate users and frustrate infrastructure specialists. The growth of a database, traffic on the network, contention for disk volumes, or the disabling of processors or portions of main memory in servers can all contribute to response time slowdowns. Each of these conditions requires analysis and resolution by infrastructure professionals. Users understandably are normally unaware of these root causes and sometimes interpret extremely slow response as downtime to their system. The threshold of time at which this interpretation occurs varies from user to user. It does not matter to users whether the problem is due to slowly responding software (slow response) or malfunctioning hardware (downtime). What does matter is that slow or non-responsive transactions can infuriate users who expect quick, consistent response times.

But slow response is different from downtime, and the root cause of these problems does matter a great deal to infrastructure analysts and administrators. They are charged with identifying, correcting, and permanently resolving the root causes of these service disruptions. Understanding the type of problem it is affects the course of action taken to resolve it. Slow response is usually a performance and tuning issue involving different personnel, different processes, and different process owners than those involved with downtime, which is an availability issue.

Differentiating Availability from High Availability

The primary difference between availability and high availability is that the latter is designed to tolerate virtually no downtime. All online computer systems are intended to maximize availability, or to minimize downtime, as much as possible. In high-availability environments, a number of design considerations are employed to make online systems as fault tolerant as possible. I refer to these considerations as the seven Rs of high availability and discuss them later in this chapter.

Desired Traits of an Availability Process Owner

As we mentioned previously, the most robust infrastructures select a single individual to be the process owner of availability. Some shops refer to this person as the availability manager. In some instances it is the operations managers; in others it is a strong technical lead in technical support. Regardless of who these individuals are, or to whom they report, they should be knowledgeable in a variety of areas, including systems, networks, databases, and facilities, and they must be able to think and act tactically. A slightly less critical, but desirable, trait of an ideal candidate for availability process owner is a knowledge of software and hardware configurations, backup systems, and desktop hardware and software.

Methods for Measuring Availability

The percentage of system availability is a very common measurement. It is found in almost all service level agreements and is calculated by dividing the amount of actual time a system was available by the total time it was scheduled to be up. For example, suppose an online system is scheduled to be up from 6:00 a.m. to midnight Monday through Friday and from 7:00 a.m. to 5:00 p.m. on Saturday. The total time it is scheduled to be up in hours is (18 x 5) + 10 = 100 hours. When online systems first began being used for critical business processing in the 1970s, online availability rates between 90% and 95% was common, expected, and reluctantly accepted. In our example, that would mean the system was up 90–95 hours per week or, more significantly, down for 5–10 hours per week and 20–40 hours per month.

Customers quickly realized that 10 hours a week of downtime was unacceptable and began negotiating service levels of 98% and even 99% guaranteed availability. As companies expanded worldwide and 24/7 systems became prevalent, the 99% level was questioned. Systems needing to operate around the clock were scheduled for 168 hours of uptime per week. At 99% availability, these systems were down, on average, approximately 1.7 hours per week. Infrastructure groups began targeting 99.9% uptime as their goal for availability for critical business systems. This target allowed for just over 10 minutes of downtime per week, but even this was not acceptable for systems such as worldwide email or an e-commerce Web site.

So the question becomes: Is the percentage of scheduled service delivered really the best measure of quality and of availability? An incident at Federal Express several years ago involving the measurement of service delivery will illustrate some points that could apply to the IT industry. FedEx had built its reputation on guaranteed overnight delivery. For many years its principal slogan was

When it positively, absolutely has to be there overnight, Federal Express.

FedEx guaranteed a package or letter would arrive on time, at the correct address, and in the proper condition. One of its key measurements of service delivery was the percentage of time that this guarantee was met. Early on, the initial goals of 99% and later 99.9% were easily met. The number of letters and packages they handled on a nightly basis was steadily growing from a few thousand to over 10,000, and less than 10 items were lost or delivered improperly.

A funny thing happened as the growth of their company started to explode in the 1980s. The target goal of 99.9% was not adjusted as the number of items handled daily started approaching one million. This meant that 1,000 packages or letters could be lost or improperly delivered every night and their service metric would still be met. One proposal to address this was to increase the target goal to 99.99%, but this goal could have been met while still allowing 100 items a night to be mishandled. A new set of deceptively simple measurements was established in which the number of items lost, damaged, delivered late, and delivered to the wrong address was tracked nightly regardless of the total number of objects handled.

The new set of measurements offered several benefits. By not tying it to percentages, it gave more visibility to the actual number of delivery errors occurring nightly. This helped in planning for anticipated customer calls, recovery efforts, and adjustments to revenue. By breaking incidents into three subcategories, each incident could be tracked separately as well as looked at in totals. Finally, by analyzing trends, patterns, and relationships, managers could pinpoint problem areas and recommend corrective actions.

In many ways, this experience with service delivery metrics at Federal Express relates closely to availability metrics in IT infrastructures. A small, start-up shop may initially offer online services only on weekdays for 10 hours and target for 99% availability. The 1% against the 50 scheduled hours allows for 0.5 hour of downtime per week. If the company grows to the point of offering similar online services 24/7 with 99% availability, the allowable downtime grows to approximately 1.7 hours.

A better approach is to track the quantity of downtime occurring on a daily, weekly, and monthly basis. As was the case with FedEx, infrastructure personnel can pinpoint and proactively correct problem areas by analyzing the trends, patterns, and relationships of these downtimes. Robust infrastructures also track several of the major components comprising an online system. The areas most commonly measured are the server environment, the disk storage environment, databases, and networks.

The tendency of many service suppliers to measure their availability in percentages of uptime is sometimes referred to as the rule of nines. Nines are continually added to the target availability goal as shown in Table 1. The table shows how the weekly minutes of allowable downtime changes from our example of the online system with 100 weekly hours and how the number of allowable undelivered items changes from our FedEx example.

Table 1. Rule of Nines Availability Percentage

Number
of
Nines

Percentage
of
Availability

Weekly
Hours
Down

Weekly
Minutes
Down

Daily Packages
Not Delivered
(out of 10K)

Daily Packages
Not Delivered
(out of 1M)

1

90.000%

10.000

600.00

1,000.0

100,000.0

2

99.000%

1.000

60.00

100.0

10,000.0

3

99.900%

0.100

6.00

10.0

1,000.0

4

99.990%

0.010

0.60

1.0

100.0

5

99.999%

0.001

0.06

0.1

10.0

In part three of this series I will discuss characteristics that I feel are essential for obtaining maximum availability. They coincidently all happen to start with the same letter leading me to refer to them as the Seven R's of High Availability.

References

Schiesser, Rich, IT Systems Management, Prentice Hall, 2002

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