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Hi, Community!

See how to efficiently validate incoming CDA documents and comply with standards using the cloud-based CDA Validation Service!

Streamlining CDA Data Feed Setup in Health Connect Cloud

https://www.youtube.com/embed/Sd6BpXyWezs?utm_source=youtube&utm_medium=social&utm_campaign=Sd6BpXyWezs
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We are happy to present the bonuses page for the applications submitted to the InterSystems "Bringing Ideas to Reality" Contest 2025!

See the results below.

The most upvoted idea on the InterSystems Ideas Portal—garnering 74 votes—requests a lightweight version of IRIS. While the platform has grown into a powerful data engine, many projects require only its SQL database capabilities. This article demonstrates how to build an unofficial, compact IRIS Community Edition image focused solely on core database functionality, reducing the image size by over 80%.

⚠️ Disclaimer

This project produces an unofficial, experimental image of InterSystems IRIS Community Edition.

• Not supported or endorsed by InterSystems.
• Use at your own risk. The modifications remove core platform features and may break compatibility with tools, APIs, and expected behaviors.
• No warranties or guarantees apply, including fitness for production use.
• Intended only for educational and experimental purposes by advanced users.

Why a Lightweight IRIS?

While IRIS today includes rich functionality—interoperability, analytics, machine learning, system management, etc.—many projects only require its core SQL capabilities. The official Community Edition Docker image is approximately:

• Disk usage: 3.5–3.8 GB
• Compressed size: ~1.1 GB

IRIS Light reduces that to:

• Disk usage: ~575–583 MB
• Compressed size: ~144–148 MB

This makes it suitable for:

• Microservice or containerized SQL use
• CI pipelines with faster startup and pull
• Horizontal scaling where full features are unnecessary

Hello Community! 👋
Welcome to the second part of the IRIS IO Utility series. This extension represents my submission for the InterSystems "Bringing Ideas to Reality" Contest 2025 and offers you an intuitive and powerful interface for importing and exporting data directly inside VS Code.

If one of your packages on OEX receives a review, you get notified by OEX only of YOUR own package.
The rating reflects the experience of the reviewer with the status found at the time of review.
It is kind of a snapshot and might have changed meanwhile.
Reviews by other members of the community are marked by * in the last column.

Hi all,

Does anyone know of a way to make Ens.ScheduleHandler alert on error?

Cheers,

Otto

Hello Community,

I’m working on a CSP application in Ensemble and want to implement versioning for JavaScript and CSS files using query strings (e.g., /js/app.js?v=1.0.0) to ensure browsers always load the latest files after deployment.

Updated 12/09/25

Hi Community,

You can unlock the full potential of InterSystems IRIS—and help your team onboard—with the full range of InterSystems learning resources offered online and in person, for every role in your organization. Developers, system administrators, data analysts, and integrators can quickly get up to speed.

I'm pleased to announce the publication of gj :: dataLoader, a new VS Code extension that simplifies the task of loading data from local CSV files into SQL tables on your InterSystems IRIS servers.

Here's an introductory video:

https://www.youtube.com/embed/XohVoW5rSy4
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Introduction

As AI-driven automation becomes an essential part of modern information systems, integrating AI capabilities into existing platforms should be seamless and efficient. The IRIS Agent project showcases how generative AI can work effortlessly with InterSystems IRIS, leveraging its powerful interoperability framework—without the need to learn Python or build separate AI workflows from scratch.

What are best practices for JSON transformation in IRIS interoperability? This is for a non-healthcare use case, so any tools we happen to have around FHIR might not be available. The motivating use case is trimming down a verbose and needlessly complex REST API response to feed to an LLM - trying to reduce token usage and maybe get better results from less noisy data.

Hello!
I have the following XML document obtained through a string:

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<MainDocument xmlns="urn:hl7-org:v3">
<realmCode code="IT"/>
<title>kjbkjkjbkjb</title>
<effectiveTime value="20090905150716"/>
[.....other tags.....]
<versionNumber value="1"/>
<component>
<body>mhvjhjkvhj</body>
<component>
<section>content</section>
<ID>5</ID>

I need to connect IRIS to a third-party FHIR server which in turn is connected to Keycloak.

For machine-to-machine communications, client credentials grants should be used. I don't know why exactly but the FHIR server requires access tokens to contain the "openid" scope, otherwise it returns 401 (unauthorized).