Hi all!

In this article I would like to review those VS Code extensions which I use myself to work with InterSystems and which make my work much more convenient. I am sure this article will be useful for those who are just starting their journey to learn InterSystems technologies. However, I also hope that this article could be useful for experienced developers with many years of experience and open up new possibilities for them when using VS Code for development.

I have been using embedded python for more than 2 years now on a daily basis.
May be it's time to share some feedback about this journey.

Why write this feedback? Because, I guess, I'm like most of the people here, an ObjectScript developer, and I think that the community would benefit from this feedback and could better understand the pros & cons of chosing embedded python for developing stuff in IRIS. And also avoid some pitfalls.

• Feedback : Using embedded python daily for 2 years
• Introduction
• Starting with Python
  • Python is not ObjectScript
    • Pep8
    • Modules
    • Dunders
  • Conclusion
• Embedded Python
  • What is Embedded Python ?
  • How to use Embedded Python ?
  • How I use Embedded Python
    • Use Python libraries and code as they were ObjectScript classes
      • With the language tag
      • Without the language tag
      • Conclusion
    • Use a python first approach
      • Example : iris-fhir-python-strategy
      • Remarks
      • Where to find the code
      • How to implement a Strategy
      • Implementation of InteractionsStrategy
      • Implementation of Interactions
      • Interactions in Python
      • Implementation of the abstract python class
      • Too long, do a summary

Hi Community,
In this article I will demonstrate the usage of InterSystems Embedded Python, We will cover below topics:

Hello everyone

For those interested, here is an implementation example I used in one of my projects to interoperate with MongoDB using the pymongo package.

iris-mongodb

Interoperates with MongoDB (via pymongo package) with InterSystems IRIS (including outbound adapter)

Remember to import pymongo package.

Hi community,

The aim of this article is to explain how to create messaging between IRIS and Microsoft Teams.

In my company, we wanted to monitor error messages, and we used the Ens.Alert class to redirect those error messages through a Business Operation that sent an email.
The problem was that we sent those error messages to a support account where there were many emails. We wanted something specific for a specific team.

So we investigated how to make these messages reach the development team directly and they could have, in real time, a notification of an error in our production.
In our company we use Microsoft Teams as a corporate tool, so we asked ourselves: How could we make these messages reach the IRIS development team?

If you develop in IRIS you are confronted with two major phenomena:

• an incredibly fast and excellent designed data storage engine
• a scripting language to work on this storage engine, actually named ObjectScript

We all know that having a set of proper test data before deploying an application to production is crucial for ensuring its reliability and performance. It allows to simulate real-world scenarios and identify potential issues or bugs before they impact end-users. Moreover, testing with representative data sets allows to optimize performance, identify bottlenecks, and fine-tune algorithms or processes as needed. Ultimately, having a comprehensive set of test data helps to deliver a higher quality product, reducing the likelihood of post-production issues and enhancing the overall user experience.

In this article, let's look at how one can use generative AI, namely Gemini by Google, to generate (hopefully) meaningful data for the properties of multiple objects. To do this, I will use the RESTful service to generate data in a JSON format and then use the received data to create objects.

Among the numerous authors present on the InterSystems Developer Community, there are unsung heroes who leave a lasting impact through their dedication and contributions. One such member is @Ben Spead, whose experiences and milestones have greatly shaped our Developer Community. He has consistently championed the communities, starting with Zen Community in 2008 to being an early participant in the Developer Community's beta phase in 2015.

🤩 Let's take a closer look at Ben's journey with InterSystems technology and our Developer Community...

Overview

With the help of SQL, you can build, train, and manage machine learning models directly in the database with InterSystems IRIS's robust IntegratedML tool. Using SQL examples that represent your data, we will go over IntegratedML configuration and how it is used in practical situations in this article.

Monitoring your IRIS deployment is crucial. With the deprecation of System Alert and Monitoring (SAM), a modern, scalable solution is necessary for real-time insights, early issue detection, and operational efficiency. This guide covers setting up Prometheus and Grafana in Kubernetes to monitor InterSystems IRIS effectively.

This guide assumes you already have an IRIS cluster deployed using the InterSystems Kubernetes Operator (IKO), which simplifies deployment, integration and mangement.

When using Studio, ODBC or a terminal connection to Caché or Ensemble, you may have wondered how to secure the connection. One option is to add TLS (aka SSL) to your connection. The Caché client applications - TELNET, ODBC and Studio - all understand how to add TLS to the connection. They just need to be configured to do it.

Configuring these clients is easier in 2015.1 and later. I'm going to be discussing this new method. If you're already using the old, legacy method, it will continue to work, but I would recommend you consider switching to the new one.

The topic of for/while loop performance in Caché ObjectScript came up in discussion recently, and I'd like to share some thoughts/best practices with the rest of the community. While this is a basic topic in itself, it's easy to overlook the performance implications of otherwise-reasonable approaches.