Hey community, how are you doing?

How do you exercise your creativity? How do you test new ideas?

Over the years I have always thought about creating new things, modifying existing ones, experimenting, testing, breaking (it always happens), building again, starting over.

Globals as a Graph Data Structure in Python

How to use the IRIS Native API + Python to see globals as a Graph Network Chart.

Iris Globals

Reading the documentation these topics are related to globals:

The healthcare technology market is in strong evolution. Gartner's wave chart for healthcare technologies demonstrates what these technologies are, very well reflected by healthcare.digital. I call this HealthTech See:

These technologies can use InterSystems technologies (ISC Health Tech), see:

¡Hi everybody!

As you likely are aware, the new version of InterSystems IRIS for Health (I4H) it's already available in Docker Hub. It's the Community version and is free and fully functional. There have been comments about it in other articles and posts,... so today I won't add anything about features. Here I want to explore "the mistery about the disappearance, or better, absence of our persistent data when we run a container with the durable option"  (I didn't find a terrifying font to emphasize the thriller... post editor is not terrific for styling ) .

InterSystems IRIS for Health ENSDEMO

Yet another basic setup of ENSDEMO content into InterSystems IRIS for Health.

Make sure you have Docker up and running before starting.

Setup

Clone the repository to your desired directory

git clone https://github.com/OneLastTry/irishealth-ensdemo.git

Once the repository is cloned, execute:

Always make sure you are inside the main directory to execute docker-compose commands.

Purpose

Most CloudFormation articles are Linux-based (no wonder), but there seems to be a demand for automation for Windows as well. Based on this original article by Anton, I implemented an example of deploying a mirror cluster to Windows servers using CloudFormation.I also added a simple walk through.
The complete source code can be found here.

Update: 2021 March 1 I added a way to connect to Windows shell by public key authentication via a bastion host as a one-liner.

I'd like to share with you some storage features that also exist in Caché but are almost 
unknown and mostly not used. They are of course available in IRIS and gain importance
with large and distributed storage architectures.

This article is a follow-up to this post.

In the previous article, [What is a Production?], we checked the production contents. We ran the sample code and checked the flowing messages' contents into the production on the Visual Trace page.

Date and Time is an important factors in our life. Because all applications are engaging based on Date/Time. But our world is split into multiple time zones. if our product is launched in the world, to maintain the history of events we are definitely required to convert all times to our local time or UTC ( Coordinated Universal Time ). As I know, many known programming languages of C#, JavaScript, Java, etc., provided the library to convert the date and time. i.e with a time zone name we can be able to convert without knowing the UTC offset.

Some of you might not be aware of this "Known Issue/Limitation" when defining a BPL-based Business Process.

And those who are not might have encountered this (somewhat "unpleasant" error):

Like hardware hosts, virtual hosts in public and private clouds can develop resource bottlenecks as workloads increase. If you are using and managing InterSystems IRIS instances deployed in public or private clouds, you may have encountered a situation in which addressing performance or other issues requires increasing the capacity of an instance's host (that is, vertically scaling).

For a long time, we have been using a utility in production to export the result of a query to an Excel spreadsheet. Moreover, we have applied a modification of it, in which the explicit setting of column formats is a priority.

In the last years the data architecture and platforms focused into Big Data repositories and how toprocess it to deliver business value. From this effort many technologies were created to process tera and petabytes of data, see:

Talking with a friend of mine, Machine Learning specialist @Renato Banzai , he brought one of the biggest challenges faced by companies nowadays: deploying ML/AI in live environments.