
Art of Capacity Planning
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Content
- Intro
- Copyright
- Table of Contents
- Preface
- Why We Wrote and Revised This Book
- Focus and Topics
- Audience for This Book
- Organization of the Material
- Conventions Used in This Book
- O'Reilly Safari
- Using Code Examples
- We'd Like to Hear from You
- Acknowledgments
- Chapter 1. Goals, Issues, and Processes in Capacity Planning
- Background
- Preliminaries
- Quick and Dirty Math
- Predicting When Systems Will Fail
- Make System Stats Tell Stories
- Buying Stuff
- Performance and Capacity: Two Different Animals
- The Effects of Social Websites and Open APIs
- Readings
- Critical Section
- Resources
- Chapter 2. Setting Goals for Capacity
- Different Kinds of Requirements and Measurements
- External Service Monitoring
- SLAs
- Business Capacity Requirements
- User Expectations
- Architecture Decisions
- Providing Measurement Points
- Resource Ceilings
- Hardware Decisions (Vertical, Horizontal, and Diagonal Scaling)
- Disaster Recovery
- Readings
- Resources
- Chapter 3. Measurement: Units of Capacity
- Capacity Tracking Tools
- Fundamentals and Elements of Metric Collection Systems
- Round-Robin Database and RRDTool
- Ganglia
- Simple Network Management Protocol
- Treating Logs as Past Metrics
- Monitoring as a Tool for Urgent Problem Identification
- Network Measurement and Planning
- Load Balancing
- Applications of Monitoring
- Application-Level Measurement
- Storage Capacity
- Database Capacity
- Caching Systems
- Establishing Caching System Ceilings
- Special Use and Multiple Use Servers
- API Usage and Its Effect on Capacity
- Examples and Reality
- Summary
- Readings
- Performance
- Network
- Load Balancer
- Storage
- Database and Caching
- Resources
- Chapter 4. Predicting Trends
- Riding the Waves
- Trends, Curves, and Time
- Tying Application Level Metrics to System Statistics: Database Example
- Forecasting Peak-Driven Resource Usage: Web Server Example
- Caveats Concerning Small Datasets
- Automating the Forecasting
- Safety Factors
- Procurement
- Procurement Time: The Killer Metric
- Just-in-Time Inventory
- The Effects of Increasing Capacity
- Long-Term Trends
- Traffic Pattern Changes
- Application Usage Changes and Product Planning
- Iteration and Calibration
- Best Guesses
- Diagonal Scaling Opportunities
- Summary
- Readings
- Buy or Lease
- Time-Series Forecasting
- Curve Fitting
- Measurement
- Resources
- Chapter 5. Deployment
- Automated Deployment Philosophies
- Goal 1: Minimize Time to Provision New Capacity
- Goal 2: All Changes Happen in One Place
- Goal 3: Never Log in to an Individual Server (for Management)
- Goal 4: Have New Servers Start Working Automatically
- Goal 5: Maintain Consistency for Easier Troubleshooting
- Automated Installation Tools
- Preparing the OS Image
- The Installation Process
- Automated Configuration
- Defining Roles and Services
- An Example: Splitting Off Static Web Content
- User Management and Access Control
- Ad Hockery
- Example 2: Multiple Datacenters
- Summary
- Readings
- Resources
- Chapter 6. Autoscaling
- The Challenge
- Autoscaling on Amazon EC2
- Design Guidelines
- Scalability Analysis
- Properties
- Autoscaling by Fixed Amount
- Scaling by Percentage
- Startup Time Aware Scaling
- Potpourri
- Advanced Approaches
- Summary
- Readings
- Resources
- Appendix A. Virtualization
- Overview
- Looking Back and Moving forward
- Appendix B. Dealing with Instantaneous Growth
- Mitigating Failure
- Graceful Degradation and Disabling Heavy Features
- Baked Static Pages and Beyond
- Cache but Serve Stale
- Handling Outages
- Appendix C. Capacity Tools
- Monitoring
- Metric Collection and Event Notification Systems
- Ad Hoc Measurement and Graphing Tools
- Deployment Tools
- Automated OS Installation
- Configuration Management
- Cluster Management/Container Orchestration
- Inventory Management
- Trend Analysis and Curve Fitting
- Books on Queuing Theory and the Mathematics of Capacity Planning
- Index
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