I have started working on utilizing Epic on FHIR about a month ago.

Creating a Public Private Key Pair

mkdir /home/ec2-user/path_to_key
openssl genrsa -out ./path_to_key/privatekey.pem 2048

For backend apps, you can export the public key to a base64 encoded X.509 certificate named publickey509.pem using this command...

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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Hi! I've extended my demo repository, andreas5588/demo-dbs-iris, to make it easy to test the FOREIGN SERVER and FOREIGN TABLE features in IRIS.

To achieve this, I created a namespace called FEDERATION. The idea is as follows:

When trying to build a custom container, I'm getting a <LICENSE LIMIT EXCEEDED> during the build process.

Will this stop the container for building? Do I need a license in order to build a custom container?

Monitor incremental changes in the database through scheduled tasks, display change trends through charts, set alarm thresholds, and write information to messages.log

How to use it

You can install it through Docker or ZPM

Deploying with Docker Prerequisites

Make sure you have git and Docker desktop installed.

Hello. On some hosts, IRIS in containers.intersystems.com/intersystems/iris-community:2024.1 falls with a core dump.

auser:~$ docker run --rm -it --entrypoint=""  containers.intersystems.com/intersystems/iris-community:2024.1 bash
irisowner@6170dcdbe77c:~$ iris start IRIS
Illegal instruction (core dumped)

Coredump stack:

Hi everyone,

I’m currently experimenting with the SQL Gateway Connection, CREATE FOREIGN SERVER, and the THROUGH command (IRIS Documentation). To speed up my tests, I’ve combined several DemoDataSets in a Docker container and would like to automate the creation of SQL Gateway Connections using code.

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:

Hey folks! Having recently onboarded to InterSystems, I realized that despite having a totally free and awesome Community Edition, it's not super clear how to get it. I decided to write up a guide highlighting all the different ways you can access the Community Edition of InterSystems IRIS:

Get InterSystems IRIS Community Edition as a Container

Working with a containerized instance of the Community Edition is the recommended approach for folks who are new to developing on InterSystems IRIS, and in my opinion it's the most straightforward. InterSystems IRIS Community Edition can be found on DockerHub; if you have an InterSystems SSO account, you can also find it in the InterSystems Container Registry.

In either case, you'll want to pull the image you want using the docker CLI:

docker pull intersystems/iris-community:latest-em
// or
docker pull containers.intersystems.com/intersystems/iris-community:latest-em

Next, you'll need to start the container: In order to interact with IRIS from outside the container (for example, to use the management portal) you'll need to publish some ports. The following command will run the IRIS Community Edition container with the superserver and web server ports published; note that you can't have anything else running that depends on ports 1972 or 52773!

docker run --name iris -d --publish 1972:1972 --publish 52773:52773 intersystems/iris-community:latest-em

I cloned @Yuri.Marx's langchain-iris-tool repo and modified docker-compose yaml per this post:

https://community.intersystems.com/post/error-when-trying-langchain-iris...

Now I see this:

Introducing Smart Clinical Sidechick — the intelligent, no-drama partner your EHR wishes it could be. She reads FHIR data in real time, interprets lab results without ghosting, and explains clinical alerts like she actually cares. Built with GPT-4 brains and YAML sass, she’s not here to replace your main EHR—just to make it look bad. Tired of irrelevant alerts and cryptic warnings? Sidechick serves up real, explainable insights, not vague “elevated risk” vibes. And when your backend crashes, she doesn’t panic—she self-heals.

I am brand new to using AI. I downloaded some medical visit progress notes from my Patient Portal. I extracted text from PDF files. I found a YouTube video that showed how to extract metadata using an OpenAI query / prompt such as this one:

ollama-ai-iris/data/prompts/medical_progress_notes_prompt.txt at main · oliverwilms/ollama-ai-iris

At hackathons that InterSystems participated and I supported, many students were asking how all their teammates could use the same IRIS database that they spun up in a container. I suggested using ngrok to expose their localhost IRIS and realized we don't have documentation on that. Hence, I thought this would be great to let more people knwo about this powerful technique for enhancing collaboration during development and testing.

Background

Embeddings is a new IRIS feature empowering the latest capability in AI semantic search.
This presents as a new kind of column on a table that holds vector data.
The embedding column supports search for another existing column of the same table.
As records are added or updated to the table, the supported column is passed through an AI model and the semantic signature is returned.
This signature information is stored as the vector for future search comparison.