Containerization is a lightweight alternative to full machine virtualization that involves encapsulating an application in a container with its own operating environment.
We are a group of interface analysts in a healthcare setting, running IRIS for Health 2024, having upgraded over time from an old ENSEMBLE environment. We have been working on a wish list of development goals, but are having trouble finding the correct, best practice method/path for getting to what we envision.
In InterSystems IRIS 2024.3 and subsequent IRIS versions, the AutoML component is now delivered as a separate Python package that is installed after installation. Unfortunately, some recent versions of Python packages that AutoML relies on have introduced incompatibilities, and can cause failures when training models (TRAIN MODEL statement). If you see an error mentioning "TypeError" and the keyword argument "fit_params" or "sklearn_tags", read on for a quick fix.
Run InterSystems IRIS inside of Home Assistant, as an add-on. Before you dismiss this article possibly under the guise that this is just a gimmick, Id like you to step back and take a look at how easy it is to launch IRIS based applications using this platform. If you look at Open Exchange, you will see dozens of dozens of applications worthy of launching while they are basically hung out to dry as gitware, and launchable if you want to get into a laptop battle with containerd or Docker. With a simple git repo, and a specification, you can now build your app on IRIS, and make it launchable through a marketplace with limited hassle to your end users. Run it along side Ollama and the LLM/LAM implementations, expose anything in IRIS as a sensor or expose an endpoint for interaction in your IRIS app to interact with anything you've connected to HAOS. Wanna restart an IRIS production with a flick of a physical switch or Assisted AI? You can do it with this add-on, or your own, right alongside the home automation hackers.
"Haul" a Portable Registry for Airgapped IrisClusters
Rancher Government Hauler streamlines deploying and maintaining InterSystems container workloads in air-gapped environments by simplifying how you package and move required assets. It treats container images, Helm charts, and other files as content and collections, letting you fetch, store, and distribute them declaratively or via CLI — without changing your existing workflows. Meaning your charts and what have yous, can have conditionals on your pull locations in Helm values, etc.
If you have been tracking how HealthShare is being deployed via IPM Packages, you can certainly appreciate the adoption of OCI compliance storage for the packages themselves using ORAS... which is core to the Hauler solution.
The Istio Service Mesh is commonly used to monitor communication between services in applications. The "battle-tested" sidecar mode is its most common implementation. It will add a sidecar container to each pod you have in your namespace that has Istio sidecar injection enabled.
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:
I'm trying to deploy a python/flask application to an Iris4Health container (2025.1) but running into some issues with packages and where they should be installed.
Sometimes customers need a small IRIS instance to do something in the cloud and shut it down, or they need hundreds of containers (i.e. one per end user or one per interface) with small workloads. This exercise came about to see how small an IRIS instance could be. For this exercise we focused on what is the smallest amount of memory we can configure for an IRIS instance.Do you know all the parameters that affect the memory allocated by IRIS ?
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?
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I recently had a company-enforced OS upgrade, and ever since going from mac OS 14.x to 15.x, I am currently having issues with SSL in IRIS.
An ARM (M3 pro) machine running OS 15.2, with the latest Docker Desktop (at the time of writing, 4.37.0). The Docker container runs IRIS for UNIX (Ubuntu Server LTS for x86-64 Containers) 2022.1.2 (Build 574_0_22161U). This container has not changed.
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.
It's not clear to me, when using the InterSystems Container Repository, which version is the best / most recent non-preview Community Edition version to use.
I see lots of 2023.2.x versions, a single 2023.3 and 2024.1 version, but also a latest-cd and latest-em (with no explanation as to what cd and em mean).
I assume the trick is to use one of the latest-xx ones? If so, which?
Unfortunately I haven't been able to find any explanatory information anywhere about the nomenclature conventions used.
I'm trying to get the python external language server started up in a container I am starting. The container is up and running but I cannot get the python language server to start.
This is the error that is coming back when trying to start the language server. I have tried creating a custom image with that package installed but it still does not work. Is there something specific that needs to be done to to get this working? (FYI, I have the dotnet version working but creating a custom image and installing the dotnet runtimes via a docker file)
Well, now we got noPWS container with IRIS, and how to connect to it, simply, without any durable sys or files, using normal peoples way like Environment variables?
I'm discovering IRIS and I need to POC the solution, with a constraint: containerization. I'm used to deploy my apps in a Swarm cluster, and all my bind volumes are written on a GlusterFS volume.
The problem here, when I start my stack, the first log is:
[WARN] ISC_DATA_DIRECTORY is located on a mount of type 'fuse.glusterfs' which is not supported, consider a named volume for '/iris_conf'
Hi there, I'm wondering if anyone has run into an issue with <FILEFULL> when building an image from the ISC image? Specifically what's happening in our build is we are pre-loading our codebase into the image to make deployments faster and setting up source control, etc. When loading our libraries however we get hit with a <FILEFULL>. The resource limits on docker are pretty beefy and when observing resources on both the machine and container level we don't hit any issues. Oddly, this only happens when using the ARM64 version.
If you plan on using the nginx server to front end you IRIS instance (as opposed to the standard apache web gateway install) you will need to add a few configuration options into the CSP.conf file in order for all urls to work. It took me a little bit to figure this out but this seems to be the configuration that works.
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A few weeks ago I posted an announcement about a JavaScript-based interface for our mg_web WebServer interfacing addon module. mg_web isn't just restricted to use by JavaScript developers though. Many readers will be ObjectScript developers who are more used to using CSP as their web gateway. Some may even have much older legacy WebLink-based applications (and be wondering how to support them given that IRIS does not support WebLink).
Kubernetes is an open-source container orchestration framework developed by Google. In essence, it controls container speed and helps you manage applications consisting of multiple containers. Additionally, it allows you to operate them in different environments, e.g., physical machines, virtual machines, Cloud environments, or even hybrid deployment environments.
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Open Exchange app
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