Capacity management is the IT risk management process for ensuring there is adequate infrastructure and computing resources to meet the current and future demand of the business in a cost effective and timely manner.
This book provides a detailed guideline for practical implementation of the capacity management process. The full benefits of implementing the process is usually harnessed when it operates as a value-added process - where capacity planning is driven from business demand, and not just based on infrastructure resources utilization, like CPU, memory, etc.
• Capacity management goals, benefits and strategy
• Common errors and gap analysis guideline
• Identify business metrics and collection techniques
• Implementing CDB - data aggregation and storage
• Capacity planning guideline, and how to build capacity planning model
• Creating capacity plan and stakeholders review
• Capacity Management Report-audience
• Auditing the capacity management process
• Capacity management in cloud computing and machine learning era.
Each chapter has thought provoking questions you may need to ask about the current or planned implementation of capacity management process in your firm.
Anyone interested in delivering excellent service to customers, but with focus on reducing IT Infrastructure spending will find this book very rewarding.
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About the Author
Table of Contents
Why I wrote this book
Who should read this book
Conventions Used in this Book
1 Capacity Management - Issues, Goals, and Benefits
2 Capacity Management Strategy
3 Capacity Management Gap Analysis & KPIS
4 Monitoring and Resource Data Collection
5 Business Metrics Data Collection Techniques
6 Data Aggregation Methods & Granularity
7 Capacity Database (CDB) & Data Storage Techniques
8 Capacity Reports
9 Capacity Planning
10 Building Analytical Capacity Planning Model
11 Capacity Planning Review with Stakeholders
12 The Capacity Plan
13 Capacity Threshold Alerting & Response Types
14 Cloud Computing Capacity Management
15 Auditing the Capacity Management Process
Appendix A – UNIX: Performance Data Collection Techniques
Appendix B - Windows: Performance Data Collection Techniques
Glossary of Terms