With the release of InterSystems IRIS Cloud SQL, we're getting more frequent questions about how to establish secure connections over JDBC and other driver technologies. While we have nice summary and detailed documentation on the driver technologies themselves, our documentation does not go as far to describe individual client tools, such as our personal favourite DBeaver. In this article, we'll describe the steps to create a secure connection from DBeaver to your Cloud SQL deployment.

Keywords:  IRIS, Agents, Agentic AI, Smart Apps

Motive?

Transformer based LLMs appear to be a pretty good "universal logical–symbolic abstractor".  They started to bridge up the previous abyss among human languages and machine languages, which in essence are all logic symbols that could be mapped into the same vector space. 

Objective?

Wondering for 3 years we might be able to just use English (etc human natural languages) to do IRIS implementations as well, one day.

Data Collection

This is a step-by-step instruction guide for creating a task to collect data about the InterSystems database and globals therein (as seen in the associated Open Exchange App - find all the associated code there)

UPDATE (Aug 1 2024): Recently I've been asked about the differences between this and the History Monitor functionality. In short, the data collection monitor builds on the history monitor by adding the ability to track growth of individual globals.

Disclaimer: This software is merely for TEST/DEMO purposes.

You’ve seen how tools like Lovable are shaking up web development. People are spinning up entire apps just by talking to an AI, almost like pair‑programming on steroids.

Now imagine bringing that same “vibe coding” experience into healthcare. know, it sounds crazy. Healthcare is complex, full of regulations, and usually gives us a headache just thinking about the interoperability rules.

That’s exactly the space where withLove lives: an AI‑Native, Low‑Code platform built entirely on InterSystems IRIS for Health.

Introduction

InterSystems IRIS allows you to build REST APIs using ObjectScript classes and the %CSP.REST framework. This enables the development of modern services to expose data for web apps, mobile apps, or system integrations.

In this article, you'll learn how to create a basic REST API in InterSystems IRIS, including:

• A persistent data class
• A REST class with GET and POST methods
• A web application to expose the API

• A full demonstration using Docker

I need to reproduce a table (in fact a view, but let's start with a simple table 😊) in IRIS as the currently used in Oracle.

I need to expose/project one column to JDBC as CLOB, in my class I have the corresponding property defined as:

Property GlobStream As %Stream.GlobalCharacter;

In JDBC this column is projected as LONGVARCHAR, this is compliant with the documentation but I need to project it as CLOB.

In addition, I'm no expert in JDBC but wit seems that LONGVARCHAR has a Maximum Length 32,700 characters in JDBC, not quite enough for an arbitrary stream.

using  intersystemsdc/iris-ml-community:latest I failed with

Error: Invalid Community Edition license, may have exceeded core limit.
Shutting down the system : $zu(56,2)= 0Starting IRIS

What is the actual valid version with ML ??

I have a persistent class (GetOrgUpdatesResponse) that has a property which is a list of another persistent class (Organization).

What would be the best way to cascade deletes so that on deletion of a parent row each object in the list property is then also deleted? 

I have included a sample of my classes here for clarity

Class Integration.ISIS.BO.SyncOrg.Custom.GetOrgUpdatesResponse Extends (%Persistent, Ens.

Hi developers!

Observing the avalanche of AI-driven and vibe-coding developer tools that have been appearing lately almost every month with more and more exciting dev features, I was puzzled whether it is possible to leverage it with InterSystems IRIS. At least to build a frontend. And the answer - yes! At least with the approach I followed.

Here is my recipe to prompt the UI vs InterSystems IRIS Backend:

1. Have the REST API on the IRIS side, which reflects some Open API (swagger) spec.
2. Generate the UI with any vibe-coding tool (e.g., Lovable) and point the UI to the REST API endpoint.
3. Profit!

Here is the result of my own exercise - a 100% prompted UI vs IRIS REST API that allows to list, create, update delete entries of a persistent class (Open Exchange,frontend source, video):

What is the recipe in detail?

Hi developers. Just want to share with you a finding that might save you a few important minutes of your developer life with InterSystems IRIS.

But!

It should work; you deployed the REST API correctly, and everything is just in place.

What can go wrong?

Have you ever needed to change an IP or port before deploying an interface to production? Needed to remove items from an export? What about modifying the value(s) in a lookup table before deploying? Have you wanted to disable an interface before deploying? What about adding a comment, category, or alert setting to an interface before deploying to production?

If you’ve ever needed to make any changes to an interface or lookup table before deploying to production, then Export Editor is for you!

Hi Developers,

We are happy to announce the first InterSystems online programming contest of the year:

🏆 InterSystems Full Stack Contest🏆

Duration: February 2 - March 1, 2026

Prize pool: $12,000

Hi Community,

Enjoy the new video on InterSystems Developers YouTube:

 ⏯  InterSystems IRIS & IRIS Health as a Managed Service @ Ready 2025 

One objective of vectorization is to render unstructured text more machine-usable. Vector embeddings accomplish this by encoding the semantics of text as high-dimensional numeric vectors, which can be employed by advanced search algorithms (normally an approximate nearest neighbor algorithm like Hierarchical Navigable Small World). This not only improves our ability to interact with unstructured text programmatically but makes it searchable by context and by meaning beyond what is captured literally by keyword.

IRIS makes SIEM systems integration simple with Structured Logging and Pipes!

This is an excellent candidate for a developer community post (like Dev.to, Medium, or the InterSystems Community). It bridges the gap between high-level architecture and hands-on implementation.

Here is the summarized article format.

Building a Robust Asynchronous Queue Manager with InterSystems IRIS and Angular

As applications scale, handling heavy computational tasks synchronously becomes a bottleneck. Whether it's processing large data sets, sending high-volume emails, or managing API integrations, a decoupled architecture is essential.

Hi developers!

I'm testing vibecoding with ObjectScript and my silicon friend created a code-block that got me thinking "what's wrong"?

Here is the piece of code:

for i=0:1:(json.%Size()-1) {

set p = json.%Get(i)

if (p="value1")!(p="value2") {

quit 1
}

AI wanted to quit from a method with a return value. Good intention, but bad use of the command.

And ObjectScript compiler compiles this code with no error(?) (syntax linter in VSCode says it's a syntax, kudos @Brett Saviano ).

But in action, it produces <COMMAND>, of course.

Hi Developers!

Currently I have 2000+ lines in a class, and I think it's a lot already? What are the best practices? 

if 10K lines OK? How do you cope with it? Please share?

Greetings,

As a long time Cache developer is there a way to get a copy of the Cache Studio that supports IRIS 2024.3? I do not have a WRC account? I need Studio just to experiment, not to build commercial software.

Thank you,

Everardo

We use local containers  a lot for evaluation and development with Health Connect and other IRIS based applications.

When evaluating Podman Desktop on Windows as replacement for Docker Desktop, we are experiencing an issue with the durable %SYS:

The only way it works is when we use a named volume which then is located inside the WSL-Podman-Machine under /var/lib/containers/storage/volumes/.

When I build docker containers my build log usually looks like this:

#9 24.94 Using 'iris.cpf' configuration file
#9 25.82
#9 27.55 Starting Control Process
#9 27.55 Global buffer setting requires attention.  Auto-selected 25% of total memory.
#9 27.55 Allocated 4999MB shared memory
#9 27.55 3915MB global buffers, 391MB routine buffers
#9 29.84 This copy of InterSystems IRIS has been licensed for use exclusively by:
#9 29.84 No local key detected, trying license server.
#9 29.84 Copyright (c) 1986-2026 by InterSystems Corporation
#9 29.

In the previous article, we examined how we can use the %CSP.Request and %CSP.Response classes to test a REST API without having the API fully set up and accessible across a network with an authentication mechanism. In this article, we will build on that foundation to perform some simple unit testing of one of our REST API methods.

The unit testing framework requires a couple of setup steps before we can use it. First, we have to ensure that the unit testing portion of the management portal is enabled so we can review the results of our tests.

We are attempting to "Repoint" old class data to new class data to save disk space and data redundancy across multiple tables. This works to a point.  In essence the two classes are sharing the same data / Index / stream globals.  But if an ID in the Old_Class is opened, a property is modified, and saved the property that is in the New_Class (but not in the Old_Class) is NULLed / blanked.

Simplified explanation of data and what’s occurring.

Intersystems IRIS Productions provide a powerful framework for connecting disparate systems across various protocols and message formats in a reliable, observable, and scalable manner. intersystems_pyprod, short for InterSystems Python Productions, is a Python library that enables developers to build these interoperability components entirely in Python. Designed for flexibility, it supports a hybrid approach: you can seamlessly mix new Python-based components with existing ObjectScript-based ones, leveraging your established IRIS infrastructure.

Welcome to the finale of our journey in building MAIS.

• In Part 1, we constructed the agnostic "Brain" using LiteLLM and IRIS.
• In Part 2, we designed the "Persona", mastering Dynamic Prompt Engineering and the ReAct theory.

Now, the stage is set. Our agents are ready, defined, and eager to work. However, they remain frozen in time. They require a mechanism to drive the conversation, execute their requested tools, and pass the baton to one another.

Today, we will assemble the Nervous System