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.


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Article
· Sep 30, 2016 1m read
ECP Magic

I saw someone recently refer to ECP as magic. It certainly seems so, and there is a lot of very clever engineering to make it work. But the following sequence of diagrams is a simple view of how data is retrieved and used across a distributed architecture.

For more more on ECP including capacity planning follow this link: Data Platforms and Performance - Part 7 ECP for performance, scalability and availability

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The release of IBM POWER 8 processors with AIX 7.1 introduced up to 8 SMT threads per processor core (logical or physical). Which SMT level (1, 2, 4, or 8) to use can be confusing and varies based on multiple factors. This article is meant to help with a starting point for your specific application.

Firstly, if running on a version of 2014.x or older, it is advised to use SMT 4 or lower. SMT 8 with those older versions of Cache' has shown a decline in performance and scaling in benchmarking applications.

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Article
· Nov 19, 2015 1m read
Disk and storage design considerations

There are many storage technologies available today from various vendors. The storage technology and configuration best for your application depends on the application access patterns and workloads.

The attached document discusses the various design considerations and recommendations for various technologies. This guide is to help you during discussions with your storage vendor to determine the appropriate storage technologies and products that will work best to meet the performance goals for your applications.

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++Update: August 2, 2018

This article provides a reference architecture as a sample for providing robust performing and highly available applications based on InterSystems Technologies that are applicable to Caché, Ensemble, HealthShare, TrakCare, and associated embedded technologies such as DeepSee, iKnow, Zen and Zen Mojo.

Azure has two different deployment models for creating and working with resources: Azure Classic and Azure Resource Manager. The information detailed in this article is based on the Azure Resource Manager model (ARM).

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Often times support and sales engineers are asked about recent benchmark results on various platforms and large scale configurations. These will be made available here in the Developer Community in the "Documentation" section, and as an example here's a link to a recent Intel E7 v2 series processor benchmark.

https://community.intersystems.com/documentation/data-scalability-intersystems-caché-and-intel-processors-0

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