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.

Step-by-Step Guide to Exposing InterSystems IRIS with ngrok

This guide will walk you through the process of exposing your local InterSystems IRIS instance using ngrok.

Description

This is a template for a Flask application that can be deployed in IRIS as an native Web Application.

Installation

1. Clone the repository
2. Create a virtual environment
3. Install the requirements
4. Run the docker-compose file

git clone
cd iris-flask-template
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
docker-compose up

Usage

The base URL is http://localhost:53795/flask/.

Endpoints

• /iris - Returns a JSON object with the top 10 classes present in the IRISAPP namespace.
• /interop - A ping endpoint to test the interoperability framework of IRIS.

I have created a new docker stack with webgateway and IRIS for Health 2025.1. I have mapped the posts of wegateway like this:

• 8743:443
• 8780:80

I can access IRIS portal through 8743 without problems.

I also have created a FHIR repository, and I'm able to access it through 8743 port.

I have a web application, in another server with another domain, that connects to this FHIR repository. I have configured in FHIR endpoint the allowed origin to the domain of this application.

Hi Developers!

As you know the concept of ObjectScript Package Manager consists of ZPM client - client application for IRIS which helps you to install packages from the registry. And the code which works "on the other side" is  ZPM Registry - server which hosts packages and exposes API to submit, list and install it. Now when you install the ZPM client it installs packages from community package registry, which si hosted on pm.community.intersystems.com

But what if you want your own registry? E.g. you produce different software packages for your clients and you want to distribute it via private registry?  Also, you may want to use your own registry to deploy solutions with different combinations of packages.

Is it possible? The answer is YES! You can have it if you deploy ZPM registry on your server with InterSystems IRIS.

To make it happen you would need to set up your own registry server.

How to do that?

Let me introduce you to FHIRCraft, a lightweight tool to generate synthetic FHIR resources.

Now, you might be thinking:
“But wait — doesn’t Synthea already do that, and with tons of resources?”
Exactly — and that’s precisely why I created this app.

FHIRCraft is designed to generate simpler, smaller, and more focused FHIR resources. Unlike Synthea, it doesn’t aim to simulate entire patient histories or clinical workflows. Instead, it helps when you’re just getting started with FHIR — when you want to test things incrementally, or explore how specific resources behave in isolation.

Hello everyone,

I am attempting to implement continuous integration using Docker with Caché 2018.1, and I am in the process of creating an image for our client. I have already installed Caché 2018.1 on the RedHat server, but I am working on a script to create the database and namespace. For the database, I used the following code:

do ##class(SYS.Database).CreateDatabase("/usr/cachepoc/cache2018/mgr/poc/")

However, I have encountered some issues with this code.

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

https://community.intersystems.

I combined @Rodolfo Pscheidt https://github.com/RodolfoPscheidtJr/ollama-ai-iris with some files from @Guillaume Rongier https://openexchange.intersystems.com/package/iris-rag-demo.

My own project is https://github.com/oliverwilms/ollama-ai-iris

I can run load_data.py and it connects to IRIS (same container).

When I try to run query_data.py https://github.com/oliverwilms/ollama-ai-iris/blob/main/query_data.py , it cannot connect to ollama:

ConnectionError: Failed to connect to Ollama. Please check that Ollama is downloaded, running and accessible.

I wonder if I need to add in query_data.

The 2024.1.4 and 2023.1.6 maintenance releases of InterSystems IRIS^® data platform,InterSystems IRIS^® for Health^TM, and HealthShare^® Health Connect are now Generally Available (GA). These releases include the fixes for the following alert recently issued - Alert: SQL Queries Returning Wrong Results | InterSystems. Please share your feedback through the Developer Community so we can build a better product together.

I read the article by @Rodolfo Pscheidt:

https://community.intersystems.com/post/ollama-ai-iris

I forked his app and copied selected files from @Guillaume Rongier iris-rag-demo to make it containerized:

oliverwilms/ollama-ai-iris
 

I ran load_data.py and I got this output:

irisowner@e10968e4da42:/irisdev/app$ python3 load_data.py
Document ID: cbfa2f20-6627-407b-bbad-31722d18ca13
modules.json: 100%|█████████████████████████████████████████████████████████████| 349/349 [00:00<00:00, 778kB/s]
config_sentence_transformers.

I cloned iris-rag-demo from Open Exchange and issued docker-compose up -d. I went to the front end and type in the chat message:

Who was the 46th President of United States of America?

I got a run time error:

RuntimeError: ERROR <Ens>ErrBPTerminated: Terminating BP ChatProcess # due to error: ERROR #5002: ObjectScript error: <PYTHON EXCEPTION> *<class 'RuntimeError'>: <PYTHON EXCEPTION> <class 'ValueError' > ERROR #5002: ObjectScript error: <PYTHON EXCEPTION> *<class 'RuntimeError'

Traceback:

File "/irisdev/app/src/python/rag/app.py", line 28, in process_input agent_text = _service.

I cloned @Yuri Marx's langchain-iris-tool repo and typed docker-compose up -d. I see error message:

Error response from daemon: could not select device driver "nvidia" with capabilities: [[gpu]]

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

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.
Subsequently when search runs, a comparison of the stored signatures occurs without any further AI model processing overhead.

Hi all.

I'm trying to create an indexed table with an vector field so I can search by the vector value.
I've been investigating and found that to get the vector value based on the text (token), use a Python method like the following:

ClassMethod TokenizeData(desc As %String) As %String [ Language = python ]
{
    import iris
    # Step 2: Generate Document Embeddings
    from sentence_transformers import SentenceTransformer

    model = SentenceTransformer('/opt/irisbuild/all-MiniLM-L6-v2')

    # Generate embeddings for each document
    document_embeddings = model.

Hello,

i am building a new container with Docker-Compose with a --volume ./:/irisdev/app:rw to mount a host volume (UBUNTU).

If i try to create some data in /irisdev/app i have no write permission

If i open a bash host session i see all mounted files of my ./ directory. But with ls -l only UID 100 has write permission. The UID for "iris owner" is 52773.

Is there a way to set the UID and Group to "iris owner" ?

regards Matthias 

I have a flask application, its working locally. I also have a iris for health 2024.3 docker container front-ended with the iris nginx container.

I can configure the WSGI application with iris for health, give it a "url" (/flask or /csp/flask) but I cannot access the flask application. It looks like the url is not found within the nginx configuration. Is there any documentation or suggestion for configuration/enabling a flask app with a IRIS container front ended with the nginx container (provided by intersystems container registry) 

Just curious what the process is for debugging either a .py file that is uploaded to a specific namespace/location or a python classmethod defined in a .cls file.

My method can be run via the "Debug" breadcrumb but it doesnt hit breakpoints it just runs without a debugger. Also objectscript methods debug correctly

Hello,

When setting up a new web app in iris (iris is in a container) iris complains that a WSGI framework is not installed. I have installed python into the container as well as both flask and django via the python virtual environment (see second screenshot) and the python language server is running

Is this the wrong way to install flask? How do I get the container version to recoginize that flask is installed?

In a containerized environment, you can manage your container time via the TZ variable or via the /etc/timezone and /etc/localtime directories:

environment:
      - TZ=Europe/Paris

volumes:
    - "/etc/timezone:/etc/timezone:ro"
    - "/etc/localtime:/etc/localtime:ro"

You can find complete examples here:

IRIS Community

IRISHealth_Community

IRIS production

IRISHealth production

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:

1. Set up JDBC connections for each namespace.
2. Create a FOREIGN SERVER within the FEDERATION namespace for each connection.
3. Define a FOREIGN TABLE a least for one table based on each foreign server.

The Script:  demo-dbs-iris/src/sql/02_create_foreign_server.sql

IRIS does not support executing SQL statements that combine tables from different namespaces.

Hi, I'm trying to use the iris python package to create a connection to and Iris Health instance (Docker Container), but getting and error. I can login to the instance using the UI with the same uname/password but unable to create the python connection. Any suggestions?

conn = iris.connect("testserver",52222,"%SYS","username","password")

After executing this I get an exception trap
An error occurred: Invalid Message Count: expected: 1 got: 825110831

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. 

(By the way, if you’re interested, the Docker container is available here: Demo DBs IRIS.)

To achieve this, I’m using SQL to create a connection by running a command like INSERT INTO %Library.sys_SQLConnection

Hi fellow developers in InterSystems IRIS!

I'm often being asked, especially related to technical bonuses we encourage for every Open Exchange contest why do we constantly give bonuses for Docker, IPM and ObjectScript Quality pass.

In fact, this is very easy to answer.

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...

openssl req -new -x509 -key ./path_to_key/privatekey.pem -out ./path_to_key/publickey509.pem -subj '/CN=medbank'

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.

Installation

1.Clone/git pull the repo into any local directory

git clone https://github.com/Sara771dev/Database-Size-Monitoring.

👩‍💻Looking to boost efficiency in your development and deployment process? See how Docker containers can help.

Hello,

The title says it all. I’m building an IRIS image with docker-compose using a separate Dockerfile. Pretty straightforward procedure: I import a Installer script inside the container containing a Installer Manifest I defined. Within the manifest, I create a namespace with code and data databases in separate locations. My intention is to keep the code database inside the container, so whenever I build the container, the imported code is replaced. The data, however, should be persistent.

iris-docker-multi-stage-script

A python script to keep your docker iris images in shape ;)

Witout changing your dockerfile or your code you can reduce the size of your image by 50% or more !

TL;DR

Name the builder image builder and the final image final and add this to end of your Dockerfile:

Modify your Dockerfile to use a multi-stage build:

ARG IMAGE=intersystemsdc/irishealth-community:latest
FROM $IMAGE as builder

Add this to end of your Dockerfile:

FROM $IMAGE as final

ADD --chown=${ISC_PACKAGE_MGRUSER}:${ISC_PACKAGE_IRISGROUP} https://github.com/grongierisc/iris-docker-multi-stage-script/releases/latest/download/copy-data.py /irisdev/app/copy-data.py

RUN --mount=type=bind,source=/,target=/builder/root,from=builder \
    cp -f /builder/root/usr/irissys/iris.cpf /usr/irissys/iris.cpf && \
    python3 /irisdev/app/copy-data.py -c /usr/irissys/iris.cpf -d /builder/root/ 

Boom! You're done!