The Good Old Days

The %Library.DynamicObject class has been in IRIS since before it became IRIS. If you have been using it since the Cache days, you may want to brush up on some of its changes.

In Cache 2018, the %Get method only had one argument. It was the key to retrieving from the JSON, meaning that if your JSON object called myObj, it would look like the following:

I know that people who are completely new to VS Code, Git, Docker, FHIR, and other tools can sometimes struggle with setting up the environment. So I decided to write an article that walks through the entire setup process step by step to make it easier to get started.

I’d really appreciate it if you could leave a comment at the end - let me know if the instructions were clear, if anything was missing, or if there’s anything else you'd find helpful.

The setup includes:

✅ VS Code – Code editor
✅ Git – Version control system
✅ Docker – Runs an instance of IRIS for Health Community
✅ VS Code REST Client Extension – For running FHIR API queries
✅ Python – For writing FHIR-based scripts
✅ Jupyter Notebooks – For AI and FHIR assignments

Before you begin: Ensure you have administrator privileges on your system.

In addition to reading the guide, you can also follow the steps in the videos:

For Windows

https://www.youtube.com/embed/IyvuHbxCwCY
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I have a new project to store information from REST responses into an IRIS database. I’ll need to sync information from at least two dozen separate REST endpoints, which means creating nearly that many ObjectScript classes to store the results from those endpoints.

It helps to remove special characters, such as non-utf-8 characters either control characters or unicode characters from text that is not printable or can't be parsed by downstream systems.

There is also $C(32) in this condition; sometimes NBSP appears in the text and it will not be recognized by TIE, but downstream it displays as "?".

Who hasn't been developing a beautiful example using a Docker IRIS image and had the image generation process fail in the Dockerfile because the license under which the image was created doesn't contain certain privileges?

In my case, what I was deploying in Docker is a small application that uses the Vector data type. With the Community version, this isn't a problem because it already includes Vector Search and vector storage. However, when I changed the IRIS image to a conventional IRIS (the latest-cd), I found that when I built the image, including the classes it had generated, it returned this error:

In a project I'm working on we need to store some arbitrary XML in the database. This XML does not have any corresponding class in IRIS, we just need to store it as a string (it's relatively small and can fit in a string).
Since there are MANY (millions!) of records in the database I decided to reduce as much as possible the size without compressing. I know that some XML to be stored is indented, some not, it varies.

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:

An extension “extends” or enhances a FHIR resource or a data element in a custom way. The extension can be added to the root of a resource, such as “Patient.ethnicity” in US Core profile, and they can be added to individual elements such as HumanName, Address or Identifier.

Did you know that you can also add an extension to a primitive data type?

Primitives usually store a single item and are the most basic element in FHIR. For example: "Keren", false, 1234, 12/08/2024 etc.

For example, the patient resources might look like this:

For my hundredth article on the Developer Community, I wanted to present something practical, so here's a comprehensive implementation of the GPG Interoperability Adapter for InterSystems IRIS.

Every so often, I would encounter a request for some GPG support, so I had several code samples written for a while, and I thought to combine all of them and add missing GPG functionality for a fairly complete coverage. That said, this Business Operation primarily covers data actions, skipping management actions such as key generation, export, and retrieval as they are usually one-off and performed manually anyways. However, this implementation does support key imports for obvious reasons. Well, let's get into it.

Introduction

Hello! In this article, I will be discussing database degrade, a type of data integrity issue one can face when using IRIS. First, I will be going over a review of the structure of IRIS databases. I'll then discuss how database degrade can manifest and common causes of degrade issues. I'll then conclude with general tips we give our customers about how to prevent or prepare for database degrade issues.

I'm sure most of you are familiar with utility %SYS.MONLBL that is crucial when analysing code performance bottlenecks. It allows you to select a number of routines that you want to monitor at runtime and also specify what process(es) you want to watch. BUT, what if you do not know exactly, what process would execute your code? This is true with many web based (CSP/REST) applications today. You want to minimize the resource utilization on your production system that needs analysis. So, how about doing a small tweak?

1. Define an INC file with these macros:

If you look at the values.yaml of the IKO's Helm chart you'll find:

useIrisFsGroup: false 

Let's break down what it is and in what situations you may want to set it to true.

FsGroup refers to the file system group.

RabbitMQ is a message broker that allows producers (those who send a data message) and consumers (those who receive a data message) to establish asynchronous, real-time, and high-performance massive data flows. RabbitMQ supports AMQP (Advanced Message Queuing Protocol), an open standard application layer protocol.
The main reasons to employ RabbitMQ include the following:

• You can improve the performance of the applications using an asynchronous approach.
• It lets you decouple and reduce dependencies between services, microservices, and applications with the help of a data message mediator, meaning that there is no need for producers and consumers of exchanged data to know each other.
• It allows the long-running processing of sent data (with the results) to be delivered after utilizing a response queue.
• It helps you migrate from monolithic to microservices, where microservices exchange data via Rabbit in a decoupled and asynchronous way.
• It offers reliability and resilience by making it possible for messages to be stored and forwarded. A message can be delivered multiple times until it is processed.
• Message queueing is the key to scaling your application. As the workload increases, you will only have to add more workers to handle the queues faster.
• It works well with data streaming applications.
• It is beneficial for IoT applications.
• It is a must for Bots’ communication.

Hi developers!

Observing the avalanche of AI-driven and vibe-coding developer tools that have been appearing lately almost every month with more and more exciting dev features, I was puzzled whether it is possible to leverage it with InterSystems IRIS. At least to build a frontend. And the answer - yes! At least with the approach I followed.

Here is my recipe to prompt the UI vs InterSystems IRIS Backend:

1. Have the REST API on the IRIS side, which reflects some Open API (swagger) spec.
2. Generate the UI with any vibe-coding tool (e.g., Lovable) and point the UI to the REST API endpoint.
3. Profit!

Here is the result of my own exercise - a 100% prompted UI vs IRIS REST API that allows to list, create, update delete entries of a persistent class (Open Exchange, frontend source, video):

What is the recipe in detail?