The art of capacity planning scaling web resources in the cloud

In their early days, Twitter, Flickr, Etsy, and many other companies experienced sudden spikes in activity that took their web services down in minutes. Today, determining how much capacity you need for handling traffic surges is still a common frustration of operations engineers and software develo...

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Bibliographic Details
Main Authors: Kejariwal, Arun, Allspaw, John (Author)
Format: eBook
Language:English
Published: Sebastopol, CA O'Reilly Media 2017
Edition:Second edition
Subjects:
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Table of Contents:
  • Includes bibliographical references and index
  • Monitoring as a Tool for Urgent Problem IdentificationNetwork 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
  • Chapter 2. Setting Goals for CapacityDifferent 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
  • 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
  • Goal 1: Minimize Time to Provision New CapacityGoal 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
  • Forecasting Peak-Driven Resource Usage: Web Server ExampleCaveats 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