Book Image

VMware Performance and Capacity Management, Second Edition - Second Edition

By : Sunny Dua
Book Image

VMware Performance and Capacity Management, Second Edition - Second Edition

By: Sunny Dua

Overview of this book

Performance management and capacity management are the two top-most issues faced by enterprise IT when doing virtualization. Until the first edition of the book, there was no in-depth coverage on the topic to tackle the issues systematically. The second edition expands the first edition, with added information and reorganizing the book into three logical parts. The first part provides the technical foundation of SDDC Management. It explains the difference between a software-defined data center and a classic physical data center, and how it impacts both architecture and operations. From this strategic view, it zooms into the most common challenges—performance management and capacity management. It introduces a new concept called Performance SLA and also a new way of doing capacity management. The next part provides the actual solution that you can implement in your environment. It puts the theories together and provides real-life examples created together with customers. It provides the reasons behind each dashboard, so that you get the understanding on why it is required and what problem it solves. The last part acts as a reference section. It provides a complete reference to vSphere and vRealize Operations counters, explaining their dependencies and providing practical guidance on the values you should expect in a healthy environment.
Table of Contents (28 chapters)
VMware Performance and Capacity Management Second Edition
Credits
Foreword
Foreword
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Part 1
Part 2
Part 3
Index

Enhancements to the dashboard


The preceding dashboards should be sufficient. However, if you think you need additional visibility to help you understand your environment, you can:

  • Use the percentile chart

  • Add utilization information

We will use compute as an example. It should be relatively straightforward to apply the idea to storage and network.

The percentile chart

The maximum value can be too aggressive. All it takes is one VM experiencing high contention, and you have to consider the cluster full already. This is fine if your IaaS is indeed unable to meet the business demand. What if the demand is not from the business but IT's own generated workload?

An example is a full AV scan or full backup that was performed during non-business hours. They may impact the VMs, making them suffer from contention. You may consider that acceptable if business is not affected.

This is where standard deviation and percentile come in. You can find out the value at, say, the 95th percentile, giving you better...