Some time ago I developed an application that tackled a familarial problem faced by many developers when required to update multiple UAT or PRODUCTION sites with the latest Software patches that have been developed and tested on your DEV server and now need to be deployed to multiple sites running that software.

In principle the solution works as follows:

1) Prepare an XML export of affected classes/routines/csp pages/hl7 definitions et al

2) Optionally create a global export of any new globals or changes to existing globals

Would you like to be sure your data transforms work as expected with a single command? And what about writing unit tests for your data transforms in a quick and simple way?

When talking about interoperability, there are usually a lot of data transforms involved. Those data transforms are used to convert data between different systems or applications in your code, so they are running a very important job.

This week I am going to look at CPU, one of the primary hardware food groups :) A customer asked me to advise on the following scenario; Their production servers are approaching end of life and its time for a hardware refresh. They are also thinking of consolidating servers by virtualising and want to right-size capacity either bare-metal or virtualized. Today we will look at CPU, in later posts I will explain the approach for right-sizing other key food groups - memory and IO.

So the questions are:

This is more for my memory that anything else but I thought I'd share it because it often comes up in comments, but is not in the InterSystems documentation.

There is a wonderful utility called ^REDEBUG that increases the level of logging going into mgr\cconsole.log.

You activate it by

a) start terminal/login

b) zn "%SYS"

c) do ^REDEBUG

This post will show you an approach to size shared memory requirements for database applications running on InterSystems data platforms including global and routine buffers, gmheap, and locksize as well as some performance tips you should consider when configuring servers and when virtualizing Caché applications. As ever when I talk about Caché I mean all the data platform (Ensemble, HealthShare, iKnow and Caché).

A list of other posts in this series is here

Index

This is a list of all the posts in the Data Platforms’ capacity planning and performance series in order. Also a general list of my other posts. I will update as new posts in the series are added.

You will notice that I wrote some posts before IRIS was released and refer to Caché. I will revisit the posts over time, but in the meantime, Generally, the advice for configuration is the same for Caché and IRIS. Some command names may have changed; the most obvious example is that anywhere you see the ^pButtons command, you can replace it with ^SystemPerformance.

While some posts are updated to preserve links, others will be marked as strikethrough to indicate that the post is legacy. Generally, I will say, "See: some other post" if it is appropriate.

Capacity Planning and Performance Series

Generally, posts build on previous ones, but you can also just dive into subjects that look interesting.

• Part 1 - Getting started on the Journey, collecting metrics.
• Part 2 - Looking at the metrics we collected.
• Part 3 - Focus on CPU.
• Part 4 - Looking at memory.
• Part 5 - Monitoring with SNMP.
• Part 6 - Caché storage IO profile.
• Part 7 - ECP for performance, scalability and availability.
• Part 8 - Hyper-Converged Infrastructure Capacity and Performance Planning
• Part 9 - Caché VMware Best Practice Guide
• Part 10 - VM Backups and IRIS freeze/thaw scripts
• Part 11 - Virtualizing large databases - VMware cpu capacity planning