The amazing Iris-nator has arrived in town.

He knows what you think, with just a few questions he is able to guess the character you have thought of.

Do you dare?

Hi Community!

I'm very excited to share with you some highlights from yesterday, from UK&I Data Summit in Birmingham! There are exciting announcements, FREE tickets to the Summit and much more, so read on!

Introduction

MonLBL is a tool for analyzing the performance of ObjectScript code execution line by line. codemonitor.MonLBL is a wrapper based on the %Monitor.System.LineByLine package from InterSystems IRIS, designed to collect precise metrics on the execution of routines, classes, or CSP pages.

The wrapper and all examples presented in this article are available in the following GitHub repository: iris-monlbl-example

This article outlines the process of utilizing the renowned Jaeger solution for tracing InterSystems IRIS applications. Jaeger is an open-source product for tracking and identifying issues, especially in distributed and microservices environments. This tracing backend that emerged at Uber in 2015 was inspired by Google's Dapper and Twitter's OpenZipkin. It later joined the Cloud Native Computing Foundation (CNCF) as an incubating project in 2017, achieving graduated status in 2019. This guide will demonstrate how to operate the containerized Jaeger solution integrated with IRIS.

Are you curious about how to run Python scripts directly in your InterSystems IRIS or Caché terminal? 🤔 Good news it's easy! 😆 IRIS supports Embedded Python, allowing you to use Python interactively within its terminal environment.

How to access the Python Shell?

To launch the Python shell from the IRIS terminal, simply run the following command:

Hi Community,

It's voting time! Cast your votes for the best applications in our InterSystems Developer Tools Contest:

🔥 VOTE FOR THE BEST APPS 🔥

How to vote? Details below.

Introduction

To achieve optimized AI performance, robust explainability, adaptability, and efficiency in healthcare solutions, InterSystems IRIS serves as the core foundation for a project within the x-rAI multi-agentic framework. This article provides an in-depth look at how InterSystems IRIS empowers the development of a real-time health data analytics platform, enabling advanced analytics and actionable insights. The solution leverages the strengths of InterSystems IRIS, including dynamic SQL, native vector search capabilities, distributed caching (ECP), and FHIR interoperability. This innovative approach directly aligns with the contest themes of "Using Dynamic SQL & Embedded SQL," "GenAI, Vector Search," and "FHIR, EHR," showcasing a practical application of InterSystems IRIS in a critical healthcare context.

Hello

We are pretty new to Ensemble and we are considering on using a default setup for our production. Let me explain the situation. We have one sender that sends HL7 ADT messages to our system. We have 60+ other systems that need to recieve ADT messages. We where thinking on a few ways on how to do the setup.

Setup1:

Now that we have a good understanding of Python and its features, let's explore how we can leverage Python within IRIS.

• Introduction to Python in IRIS
• Language Tag
  • How to use it?
  • Pros
  • Cons
  • Conclusion
• Importing Python Modules (pypi modules)
  • How to use it
  • Pros
  • Cons
  • Conclusion
• Importing Python Modules (custom modules)
  • How to use it
  • Pros
  • Cons
  • Conclusion

Here is my code:

I recently had to refresh my knowledge of the HealthShare EMPI module and since I've been tinkering with IRIS's vector storage and search functionalities for a while I just had to add 1 + 1.

For those of you who are not familiar with EMPI functionality here's a little introduction:

Enterprise Master Patient Index

In general, all EMPIs work in a very similar way, ingesting information, normalizing it and comparing it with the data already present in their system. Well, in the case of HealthShare's EMPI, this process is known as NICE:

Background

For a variety of reasons, users may wish to mount a persistent volume on two or more pods spanning multiple availability zones. One such use case is to make data stored outside of IRIS available to both mirror members in case of failover.

Unfortunately the built-in storage classes in most Kubernetes implementations (whether cloud or on-prem) do not provide this capability:

One of the recommendations when deploying InterSystems Technologies for production is to set up High Availability. The recommended API Manager for these InterSystems Technologies is the InterSystems API Manager (IAM). IAM (essentially Kong Gateway) has multiple deployment topologies.

CCR now includes an AI-powered 'CCR Assistant', available to beta testers. The CCR Assistant helps you quickly get answers about common CCR workflows, terminology, or best practices. Every response includes references to relevant ICC Training courses, making it easy to dive deeper into any topic. As a future improvement, the links will point directly to the specific page of the ICC Training PDF that was used to generate the response.