I recently started using Cursor/VSCode with an IRIS container for development rather than Studio/Terminal. I've noticed that whenever I use %G (so basically all the time), when I exit %G, the terminal window simply closes, rather than returning me to my usual namespace prompt. %G also does not retain the command stack like it does in old school terminal, so I'm forced to constantly retype every global reference. Anyone figured out a solution to this? It's a relatively minor problem in the grand scheme of things, but a time consuming and irritating one.
What is the recommended approach for handling upgrades in an InterSystems IRIS Kubernetes environment?
For example, if we deploy version 1.0.0 of our product and subsequently need to upgrade to 1.0.1, and this upgrade requires changes to SQL tables containing customer data.
The quickest solution that comes to mind is creating an 'upgrade method' that runs on startup to check if any data migration actions are required. However, I'm wondering if there are better solutions or established best practices for this.
What was your READY experience like? 🎉 We’ve put together a bingo card — check out how many squares match your experience!
Mark the moments that happened to you or share them in the comments below. And if you had a memorable READY moment that’s not on the card, tell us about it — we’d love to hear your story ✨
I’m thrilled to share that after several years of deep diving into the InterSystems IRIS data platform, I have finally summarized my project experiences into a new book IRIS (Data Platform) Programming Technical Guide. It is published by Beihang University Press, a prestigious central-level comprehensive publisher renowned for its leading role in aerospace, science, and technology publishing.
Writing this book was a significant engineering challenge for me. My goal was to bridge the gap between "understanding the syntax" and "building a production-ready project.
We are using IRIS for Health to develop an agentic AI chatbot workflow that can interact with a patient using voice commands, reach out to an EHR or other system for context, and provide recommendations back.
Presenters: 🗣 @Vic Sun, Sales Engineer at InterSystems 🗣 @Brad Nissenbaum, Sales Engineer at InterSystems 🗣 Danielle Micciantuono, Clinical Solutions Specialist at InterSystems
ExplantIQ is an intelligent data application that tackles one of healthcare's most overlooked financial and regulatory risks: the management of explanted medical device warranty credits. When an implanted device is removed from a patient (due to failure or recall) hospitals are legally required to pursue manufacturer credits, refund payers if the credit exceeds 50% of the device's cost, and report to CMS. Miss that obligation and you're facing a reverse False Claims Act violation. Industry data shows hospitals miss 81% of eligible credits.
ExplantIQ, built entirely on InterSystems IRIS for Health and DeepSee, solves this by unifying clinical, supply chain, billing, and FDA recall data into a single real-time compliance dashboard, complete with KPI scorecards, trend analytics, and a Text-to-SQL AI Assistant that lets compliance officers query live operational data in plain English. No separate BI tool. No additional architecture. All questions can be answered without leaving your browser tab.
Create an operational data store using the data flowing through your production. Create user-defined analytics tables based on fields and paths to their data from incoming documents with varying standards (FHIR, CDA, HL7v2, etc.).
Redoc is an Open Source solution capable of rendering API specifications in OpenAPI 2.0 or 3.0+ as very beautiful and functional web portals. Currently, to have something similar, we need the ZPM SwaggerUI extension or we need to install IAM - InterSystems API Manager and then configure the IAM Developer Portal. Well, now the community has one more option, iris-redoc. This solution installs a web application on your IRIS instance that uses Redoc to present a beautiful web portal for your REST APIs:
For those who learned Caché ObjectScript from scratch: what kind of personal or practice projects did you build to get comfortable with the language? I come from a C# background and I'm looking for project ideas that are small enough to be feasible but meaningful enough to actually teach the core COS concepts.
Discover how to accelerate cloud-based integration with InterSystems' native AWS adapters for S3, SQS, SNS, and CloudWatch.
This session provides a practical look at building modern interoperability workflows — from secure file ingestion and asynchronous messaging to automated notifications and centralized monitoring.
Recently, a question on the Community was asked by @Vermon Ferre about storing data from inherited classes in different globals. So, I decided to simulate the following behavior: I created a superclass called Article.MainClass and two subclasses, Article.Class1 and Article.Class2. By default, when each class extends %Persistent IRIS creates independent storage structures for them. This will work as intended if the first class in the list of superclasses is %Persistent. But it also means that if there are any parameters in the main class, they will be lost, because only parameters from the first class in the list get inherited.
What is the most efficient, memory-safe way to get the names of the corrupted indexes on very large tables for a rebuild. However, if an index has millions of corrupted rows, the .errors array in %ValidateIndices grows too large and throws a errorerror.
Welcome to another installment of the Platforms Update. A few notables to highlight:
Ubuntu 26.04 has been released, and corresponding IRIS support is coming soon.
IRIS 2026.2 will bring an end to support for Ubuntu 22.04 and Windows 10.
Revised minimum CPU specifications are in effect for 2025.3+
For those newly acquainted with these communications, this update provides details about recent enhancements as well as anticipated changes based on current information; however, future projections remain uncertain and the content should not be interpreted as a definitive product roadmap.
Today, coding assistants like Claude, GitHub Copilot and Cursor have transformed the way developers write code. However, these tools are limited by being isolated from the systems and data sources that developers work with daily. This limitation can be overcome through the Model Context Protocol (MCP), an open standard designed to connect AI assistants to external data sources and tools in a secure and standardized way.
In this review article, we'll explore the current state-of-the-art regarding the MCP within the InterSystems ecosystem.
I was really surprised that such a flexible integration platform with a rich toolset specifically for app connections has no out-of-the-box Enterprise Service Bus solution. Like Apache ServiceMix, Mule ESB, SAP PI/PO, etc, what’s the reason? What do you think? Has this pattern lost its relevance completely nowadays? And everybody moved to message brokers, maybe?
Wiki time: An enterprise service bus (ESB) implements a communication system between mutually interacting software applications in a service-oriented architecture (SOA) .
When IRIS 2023.2 reaches general availability, we’ll be making some improvements to how we tag and distribute IRIS & IRIS for Health containers.
IRIS containers have been tagged using the full build number format, for example 2023.1.0.235.1. Customers have been asking for more stable tags, so they don’t need to change their dockerfiles/Kubernetes files every time a new release is made. With that in mind, we’re making the following changes to how we tag container images.
Major.Minor Tags: Containers will be tagged with the year and release, but not the rest of the full build number.
For a variety of reasons, users may wish to mount a persistent volume on two or more pods spanning multiple availability zones. One such use case is to make data stored outside of IRIS available to both mirror members in case of failover.
What's the most straight-forward way to install this on an offline server? I'm trying to set this up on an Azure DevOps server to support our CI/CD pipelines. I've tried using zpm installing the tgz from the local filesystem. I note zpm seems to need a repo configured to install but I can't work out how to setup a bare-bones Filesystem repo (please point me to some documentation on this). I have no idea what I'm doing...
zpm:%SYS>install f:/tmp/zpm-registry-1.3.4.tgz
ERROR! 'tmp' not found in any repository.
zpm:%SYS>install zpm-registry-1.3.4.tgz
ERROR! 'zpm-registry-1.3.4.tgz' not found in any repository.
zpm:%SYS>install zpm-registry
ERROR! 'zpm-registry' not found in any repository.
zpm:%SYS>install "f:\tmp\zpm-registry-1.3.4.tgz"
ERROR! 'f:\tmp\zpm-registry-1.3.4.tgz' not found in any repository.
zpm:%SYS>list
IPM (zpm) 0.10.6
zpm:%SYS>repo
1) Filesystem
2) ORAS
3) Remote Repository
Which sort of repository do you wish to configure? 1
Name: local
local
Source: F:\tmp\*
Enabled? Yes
Available? Yes
Use for Snapshots? Yes
Use for Prereleases? Yes
Is Read-Only? No
local
Source: F:\tmp\*
Enabled? Yes
Available? Yes
Use for Snapshots? Yes
Use for Prereleases? Yes
Is Read-Only? No
zpm:%SYS>install f:/tmp/zpm-registry-1.3.4.tgz
ERROR! 'tmp' not found in any repository.
zpm:%SYS>install zpm-registry-1.3.4.tgz
ERROR! 'zpm-registry-1.3.4.tgz' not found in any repository.
zpm:%SYS>install zpm-registry
ERROR! 'zpm-registry' not found in any repository.
zpm:%SYS>install "f:\tmp\zpm-registry-1.3.4.tgz"
ERROR! 'f:\tmp\zpm-registry-1.3.4.tgz' not found in any repository.
zpm:%SYS>info
Welcome to the Package Manager Shell (ZPM). Version: 0.10.6
Enter q/quit to exit the shell. Enter ?/help to view available commands
No registry configured
System Mode: <unset>
Mirror Status: NOTINIT
IRIS for Windows (x86-64) 2025.2 (Build 227U) Thu Jul 10 2025 11:01:07 EDT
Currently installed top-level modules are listed below:
IPM 0.10.6
This demo highlights how HL7 validation logs can be transformed into scalable, actionable data quality insights using a lightweight application built on top of Health Connect.
Batch ingestion and parsing of HL7 validation error logs into structured data
Aggregation of errors by segment, field, and type to reveal systemic issues
Interactive dashboard (Streamlit) for filtering, exploration, and root cause analysis
Rapid identification of top error patterns across entire data feeds
Natural language chatbot for intent-driven data investigation and querying
PDF report generation for sharing clear, evidence-based feedback during data source onboarding
Special thanks to @Henry Wojnicki for his contributions to designing and refining the application workflow.
🗣 Presenter: @Lynn Wu, Sales Engineer at InterSystems
