As you know in Caché / IRIS you have the possibility to define a property as Multidimensional as documented here:
https://docs.intersystems.com/iris20201/csp/docbook/DocBook.UI.Page.cls?KEY=GOBJ_proplit#GOBJ_proplit_multidim
and the explanation of how to use it
https://docs.intersystems.com/iris20201/csp/docbook/Doc.View.cls?KEY=GOBJ_proplit#GOBJ_proplit_multidim_values

Though the access is quite comfortable (in traditional COS sense) there are 2 main restrictions that hurt:

#1) It is not saved to disk unless your application includes code to save it specifically.
#2) It cannot be stored in or exposed through SQL tables
   there are some more
I'll show how to overcome these limits

   GIS stands for Geographic Information System.
  and it's not a typical arena for Caché. But it's definitely an environment with high data volume.

You see 3 major areas

- Visual front end:
   A mature area well covered by a bunch of commercial and open source products.
   No need for Caché there.

While the classic solution followed rather close the concepts and design of the ancestors
Caché / IRIS allows a more modern approach to flexible/multidimensional properties

For those experts that can't stop after AoC2019
I have posted some rather old code in traditional style to improve it.

The Amazon Web Services (AWS) Cloud provides a broad set of infrastructure services, such as compute resources, storage options, and networking that are delivered as a utility: on-demand, available in seconds, with pay-as-you-go pricing. New services can be provisioned quickly, without upfront capital expense. This allows enterprises, start-ups, small and medium-sized businesses, and customers in the public sector to access the building blocks they need to respond quickly to changing business requirements.

Updated: 2-Apr, 2021 

Introduction

The common requirement in many applications is logging of data changes in a database - which data has changed, who changed them and when (audit logging). There are many articles about this question and there are different approaches on how to do that in Caché.

Ansible helped me solve the problem of quickly deploying Caché and application components for Data Platforms benchmarks. You can use the same tools and methodology for standing up your test labs, training systems, development or other environments. If you deploy applications at customer sites you could automate much of the deployment and ensure that system, Caché and your application are configured to your applications best practice standards.

Introduction

If you're solving complex problems in ObjectScript, you probably have a lot of code that works with %Status values. If you have interacted with persistent classes from an object perspective (%Save, %OpenId, etc.), you have almost certainly seen them. A %Status provides a wrapper around a localizable error message in InterSystems' platforms. An OK status ($$$OK) is just equal to 1, whereas a bad status ($$$ERROR(errorcode,arguments...)) is represented as a 0 followed by a space followed by a $ListBuild list with structured information about the error. $System.Status (see class reference) provides several handy APIs for working with %Status values; the class reference is helpful and I won't bother duplicating it here. There have been a few other useful articles/questions on the topic as well (see links at the end). My focus in this article will be on a few debugging tricks techniques rather than coding best practices (again, if you're looking for those, see links at the end).

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 of the 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 ^pButtons command, you can replace it with ^SystemPerformance.

Capacity Planning and Performance Series

Generally posts build on previous, but you can also just dive in to 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 Caché freeze/thaw scripts
• Part 11 - Virtualizing large databases - VMware cpu capacity planning

This example is extracted from a long-running installation. The purpose is to have a simple monitoring of several servers at a rather primitive level. Just slightly more intelligent than a raw PING. But still easy to integrate. It avoids the overkill of information you are often confronted with while you are just interested in the number of active processes or similar basic figures.

The code is available for you here 

This is a coding example working on Caché 2018.1.3 and IRIS 2020.2 
It will not be kept in sync with new versions 
It is also NOT serviced by InterSystems Support !

Globals, these magic swords for storing data, have been around for a while, but not many people can use them efficiently or know about this super-weapon altogether.

If you use globals for tasks where they truly shine, the results may be amazing, either in terms of increased performance or dramatic simplification of the overall solution (1, 2).

Globals offer a special way of storing and processing data, which is completely different from SQL tables. They were first introduced in 1966 in the M(UMPS) programming language, which was initially used in medical databases. It is still used in the same way, but has also been adopted by some other industries where reliability and high performance are top priorities: finance, trading, etc.

Later M(UMPS) evolved into Caché ObjectScript (COS). COS was developed by InterSystems as a superset of M. The original language is still accepted by developers' community and alive in a few implementations. There are several signs of activity around the web: MUMPS Google group, Mumps User's group), effective ISO Standard, etc.

Modern global based DBMS supports transactions, journaling, replication, partitioning. It means that they can be used for building modern, reliable and fast distributed systems.

Globals do not restrict you to the boundaries of the relational model. They give you the freedom of creating data structures optimized for particular tasks. For many applications reasonable use of globals can be a real silver bullet offering speeds that developers of conventional relational applications can only dream of.

Globals as a method of storing data can be used in many modern programming languages, both high- and low-level. Therefore, this article will focus specifically on globals and not the language they once came from.

Recently, a partner company started to develop an Angular client for their Cache application. Together, we decided to leverage the power of Caché dynamic objects to exchange JSON encoded data between client and server parts. However, we realized that currently there is a gap in Cache JSON implementation that prevents simple use of traditional registered and persistent classes to exposed their data with the same ease as with XML. I wrote a small JSON adapter, that does the job and bridgers the gap. It's purpose is simple expose data described by a regular Cache class in a one-to-one fashion to a %DynamicObject. On the other hand, when a serialized JSON data comes in, it can be easily deserialized into dynamic object and subsequently bound to regular class by the newly created adapter.