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Hello everybody,

I would like to export project contents using Visual Studio Code, as well as I do with InterSystems Studio.

However, while attempting the export through the InterSystems extension I get the following error:

- There are no folders in the current workspace that code can be exported to.

These are the step to reproduce my error:

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Hi Community,

We’re excited to share a brand-new Instruqt tutorial:

🧑‍🏫 RAG using InterSystems IRIS Vector Search

This hands-on lab walks you through building a Retrieval Augmented Generation (RAG) AI chatbot powered by InterSystems IRIS Vector Search. You’ll see how vector search can be leveraged to deliver up-to-date and accurate responses, combining the strengths of IRIS with generative AI.

✨ Why try it?

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The most upvoted idea on the InterSystems Ideas Portal—garnering 74 votes—requests a lightweight version of IRIS. While the platform has grown into a powerful data engine, many projects require only its SQL database capabilities. This article demonstrates how to build an unofficial, compact IRIS Community Edition image focused solely on core database functionality, reducing the image size by over 80%.

⚠️ Disclaimer

This project produces an unofficial, experimental image of InterSystems IRIS Community Edition.

  • Not supported or endorsed by InterSystems.
  • Use at your own risk. The modifications remove core platform features and may break compatibility with tools, APIs, and expected behaviors.
  • No warranties or guarantees apply, including fitness for production use.
  • Intended only for educational and experimental purposes by advanced users.

Why a Lightweight IRIS?

While IRIS today includes rich functionality—interoperability, analytics, machine learning, system management, etc.—many projects only require its core SQL capabilities. The official Community Edition Docker image is approximately:

  • Disk usage: 3.5–3.8 GB
  • Compressed size: ~1.1 GB

IRIS Light reduces that to:

  • Disk usage: ~575–583 MB
  • Compressed size: ~144–148 MB

This makes it suitable for:

  • Microservice or containerized SQL use
  • CI pipelines with faster startup and pull
  • Horizontal scaling where full features are unnecessary

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It's been a while since the new UI for Productions and DTL was published as a preview and I would like to know your opinions about it.

WARNING: This is a personal opinion, totally personal and not related with InterSystems Corporation.

I'm going to start with the Interoperabilty screen:

Production screen:

The style is sober and without frills, following the line of cloud services design, I like it.

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Article
· Jun 18, 2025 2m read
Options for Python Devs + Poll!

I am writing this post primarily to gather an informal consensus on how developers are using Python in conjunction with IRIS, so please respond to the poll at the end of this article! In the body of the article, I'll give some background on each choice provided, as well as the advantages for each, but feel free to skim over it and just respond to the poll.

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Are you familiar with SQL databases, but not familiar with IRIS? Then read on...

About a year ago I joined InterSystems, and that is how IRIS got on my radar. I've been using databases for over 40 years—much of that time for database vendors—and assumed IRIS would be largely the same as the other databases I knew. However I was surprised to find that IRIS is in several ways quite unlike other databases, often much better. With this, my first article in the Dev Community, I'll give a high-level overview of IRIS for people that are already familiar with the other databases such as Oracle, SQL Server, Snowflake, PostgeSQL, etc. I hope I can make things clearer and simpler for you and save you some time getting started.

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FHIR Server

A FHIR Server is a software application that implements the FHIR (Fast Healthcare Interoperability Resources) standard, enabling healthcare systems to store, access, exchange, and manage healthcare data in a standardized manner.

Intersystems IRIS can store and retrieve the following FHIR resources:

  • Resource Repository – IRIS Native FHIR server can effortlessly store the FHIR bundles/resources directly in the FHIR repository.
  • FHIR Facade - the FHIR facade layer is a software architecture pattern used to expose a FHIR-compliant API on top of an existing one (often non-FHIR). It also streamlines the healthcare data system, including an electronic health record (EHR), legacy database, or HL7 v2 message store, without requiring the migration of all data into a FHIR-native system.

What is FHIR?

Fast Healthcare Interoperability Resources (FHIR) is a standardized framework created by HL7 International to facilitate the exchange of healthcare data in a flexible, developer-friendly, and modern way. It leverages contemporary web technologies to ensure seamless integration and communication across various healthcare systems.

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When working with InterSystems IRIS, database developers and architects often face a critical decision: whether to use Dynamic SQL or Embedded SQL for querying and updating data. Both methods have their unique strengths and use cases, but understanding their performance implications is essential to making the right choice. Response time, a key metric in evaluating application performance, can vary significantly depending on the SQL approach used. Dynamic SQL offers flexibility, as queries can be constructed and executed at runtime, making it ideal for scenarios with unpredictable or highly variable query needs. Conversely, Embedded SQL emphasizes stability and efficiency by integrating SQL code directly into application logic, offering optimized response times for predefined query patterns.

In this article, I will explore the response times when using these two types of SQL and how they depend on different class structures and usage of parameters. So to do this, I'm going to use the following classes from the diagram:

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Hi Community,

In this article, I will introduce my application iris-AgenticAI .

The rise of agentic AI marks a transformative leap in how artificial intelligence interacts with the world—moving beyond static responses to dynamic, goal-driven problem-solving. Powered by OpenAI’s Agentic SDK , The OpenAI Agents SDK enables you to build agentic AI apps in a lightweight, easy-to-use package with very few abstractions. It's a production-ready upgrade of our previous experimentation for agents, Swarm.
This application showcases the next generation of autonomous AI systems capable of reasoning, collaborating, and executing complex tasks with human-like adaptability.

Application Features

  • Agent Loop 🔄 A built-in loop that autonomously manages tool execution, sends results back to the LLM, and iterates until task completion.
  • Python-First 🐍 Leverage native Python syntax (decorators, generators, etc.) to orchestrate and chain agents without external DSLs.
  • Handoffs 🤝 Seamlessly coordinate multi-agent workflows by delegating tasks between specialized agents.
  • Function Tools ⚒️ Decorate any Python function with @tool to instantly integrate it into the agent’s toolkit.
  • Vector Search (RAG) 🧠 Native integration of vector store (IRIS) for RAG retrieval.
  • Tracing 🔍 Built-in tracing to visualize, debug, and monitor agent workflows in real time (think LangSmith alternatives).
  • MCP Servers 🌐 Support for Model Context Protocol (MCP) via stdio and HTTP, enabling cross-process agent communication.
  • Chainlit UI 🖥️ Integrated Chainlit framework for building interactive chat interfaces with minimal code.
  • Stateful Memory 🧠 Preserve chat history, context, and agent state across sessions for continuity and long-running tasks.

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One of the challenges of creating a DICOM message is how to implement putting data in the correct place. Part of it is by inserting the data in the specific DICOM tags, while the other is to insert binary data such as a picture - In this article I will explain both.

To create a DICOM message, you can either use the EnsLib.DICOM.File class (to create a DICOM file) or the EnsLib.DICOM.Document class (to create a message that can be sent to PACS directly). In either case, the SetValueAt method will allow you to add your data to the DICOM tags.

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Hi colleagues!

Often, while developing a frontend app or any other communication vs REST API, it is worth having a Swagger UI - a test UI for the REST API that follows Open API 2.0 spec. Usually, it is quite a handful as it lets have quick manual tests vs REST API and its responses and the data inside.

Recently I've introduced the Swagger support to the InterSystems IRIS FHIR template for FHIR R4 API:

How to get it working.

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There are numerous excellent tools available for testing your REST APIs, especially when they are live. Postman, various web browser extensions, and even custom ObjectScript written with %Net.HttpRequest objects can get the job done. However, it is often difficult to test just the REST API without inadvertently involving the authentication scheme, the web application configuration, or even network connectivity. Those are a lot of hoops to jump through just to test the code within your dispatch class. The good news is that if we take our time to understand the inner workings of the %CSP.REST class, we will find an alternative option suited for testing only the contents of the dispatch class. We can set up the request and response objects to invoke the methods directly.

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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

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gj :: configExplorer is a new VS Code extension integrating with Server Manager and leveraging Structurizr to produce configuration diagrams of your servers.

Here's a short introductory video.

https://www.youtube.com/embed/WHkoZsg6P-A
[This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]

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RabbitMQ is a message broker that allows producers (those who send a data message) and consumers (those who receive a data message) to establish asynchronous, real-time, and high-performance massive data flows. RabbitMQ supports AMQP (Advanced Message Queuing Protocol), an open standard application layer protocol.
The main reasons to employ RabbitMQ include the following:

  • You can improve the performance of the applications using an asynchronous approach.
  • It lets you decouple and reduce dependencies between services, microservices, and applications with the help of a data message mediator, meaning that there is no need for producers and consumers of exchanged data to know each other.
  • It allows the long-running processing of sent data (with the results) to be delivered after utilizing a response queue.
  • It helps you migrate from monolithic to microservices, where microservices exchange data via Rabbit in a decoupled and asynchronous way.
  • It offers reliability and resilience by making it possible for messages to be stored and forwarded. A message can be delivered multiple times until it is processed.
  • Message queueing is the key to scaling your application. As the workload increases, you will only have to add more workers to handle the queues faster.
  • It works well with data streaming applications.
  • It is beneficial for IoT applications.
  • It is a must for Bots’ communication.

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Dear Community,

As the 🎄 Festive Season 🎄 approaches, we’re excited to send our warmest wishes your way. May your holidays be filled with the joy of 🧑‍💻 learning, 🫂 connecting with fellow developers, and the thrill of new ideas and challenges waiting in the year ahead!

Looking back on 2025, we’re delighted to celebrate another year of remarkable achievements together with YOU, our incredible members:

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InterSystems Official
· Nov 19, 2025
Client SDKs available on external repositories

Hi community!

I am excited to say that since the beginning of this year we have published many of the client SDKs for InterSystems IRIS, InterSystems IRIS for Health and Health Connect to the corresponding external repositories (Maven, NuGet, npm and PyPI). This provides many benefits to you such as:

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The August Article Bounty on the Global Masters article caught my attention, and one of the proposed topics sounded quite interesting in regard to its future use in my teaching. So, here's what I'd like to tell my students about tables in IRIS and how they correlate with the object model.

First of all, InterSystems IRIS boasts a unified data model. This means that when you work with data, you are not locked into a single paradigm. The same data can be accessed and manipulated as a traditional SQL table, as a native object, or even as a multidimensional array (a global). It means that when you create an SQL table, IRIS automatically creates a corresponding object class. When you define an object class, IRIS automatically makes it available as an SQL table. The data itself is stored only once in IRIS's efficient multidimensional storage engine. The SQL engine and the object engine are simply different "lenses" to view and work with the same data.

First, let's look at the correlation between the relational model and the object model:

Relational Object
Table Class
Column Property
Row Object
Primary key Object Identifier

It's not always a 1:1 correlation, as you may have several tables represent one class, for example. But it's a general rule of thumb.

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Hi Community,

In this article, I will introduce my application iris-fhir-bridge

IRIS-FHIR-Bridge is a robust interoperability engine built on InterSystems IRIS for Health, designed to transform healthcare data across multiple formats into FHIR and vice versa. It leverages the InterSystems FHIR Object Model (HS.FHIRModel.R4.*) to enable smooth data standardization and exchange across modern and legacy healthcare systems.

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Regardless of whether an instance of IRIS is in the cloud or not, high availability and disaster recovery are always important considerations. While IKO already allows for the use of NodeSelectors to enforce the scheduling of IRISCluster nodes across multiple zones, multi-region k8s clusters are generally not recommended or even supported in the major CSP's managed Kubernetes solutions. However, when discussing HA and DR for IRIS, we may want to have an async member in a completely separate region, or even in a different cloud provider altogether.

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