For the question in the Title, the AI Chat gave a response of:


The ‘Current Users’ value displayed by the $System.License.ShowSummary() method represents
real-time license usage tracked in shared memory on the local system.

We are trying to reconcile which user/process are associated with the counts that are returned.

Does anyone know how to get the detail of 'license usage tracked in shared memory on the local system.'?

Thanks you for your time.

- Patrick

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Hello Community! As another great year comes to a close, I wanted to notify you about an upcoming change to the vscode-objectscript extension. In an effort to reduce the extension's footprint, simplify maintenance, and improve ease of use, InterSystems plans to remove some rarely-used configuration settings. Our telemetry tells us that these settings are changed from the default by fewer than 2% of users. However, before finalizing the removal I would like to give any users of these settings the opportunity to explain why a setting shouldn't be removed.

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It was encouraging to see more people building VS Code extensions for the recent contest. However I noticed that of of the three extensions requiring credentials with which to make their connections only mine, gj :: dataLoader, leverages the long-established and officially-supported InterSystems Server Manager extension to obtain the connection definitions and to handle credentials securely.

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I have an Embedded Python method, which is essentially a call to one third-party module.

Most of the time, the method takes <0.1 seconds to execute, but sometimes it takes 30 or 60 seconds.

The server is relatively idle (20-30% CPU load).

How can I debug this issue further? Ideally, I want to know where this library spends the time. The library is mainly Python code (it's boto3, so it's not a Python C API proxy library).

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Apache Airflow is the leading open-source platform to programmatically author, schedule, and monitor data pipelines and workflows using Python. Workflows are defined as code (DAGs), making them version-controlled, testable, and reusable. With a rich UI, 100+ built-in operators, dynamic task generation, and native support for cloud providers, Airflow powers ETL/ELT, ML pipelines, and batch jobs at companies like Airbnb, Netflix, and Spotify.

Airflow Application Layout

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Introduction

In today's rapidly evolving threat landscape, organizations deploying mission-critical applications must implement robust security architectures that protect sensitive data while maintaining high availability and performance. This is especially crucial for enterprises utilizing advanced database management systems like InterSystems IRIS, which often powers applications handling highly sensitive healthcare, financial, or personal data.

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Hey Community!

We're happy to share a new video from our InterSystems Developers YouTube:

SQL Tricks and Tips @ Ready 2025

https://www.youtube.com/embed/WjE3JkDU-EU
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greetings Community!

InterSystems Learning Services is working to identify and create libraries of high-quality learning resources for third-party technologies, platforms, and systems that are part of, integrated with, or commonly used with InterSystems products and technologies. we don't create content for these ourselves, but want to support our clients, external and internal, in learning about them and how to use them.

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Introduction

As AI-driven automation becomes an essential part of modern information systems, integrating AI capabilities into existing platforms should be seamless and efficient. The IRIS Agent project showcases how generative AI can work effortlessly with InterSystems IRIS, leveraging its powerful interoperability framework—without the need to learn Python or build separate AI workflows from scratch.

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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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Supply Chain refers to a set of processes and activities performed by the company's business areas and its suppliers and partners (stakeholders), from the acquisition of raw materials, through production, to delivery to the end consumer. It can be better managed using SCM solutions with the orchestration of the InterSystems IRIS:

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Updated 12/09/25

Hi Community,

You can unlock the full potential of InterSystems IRIS—and help your team onboard—with the full range of InterSystems learning resources offered online and in person, for every role in your organization. Developers, system administrators, data analysts, and integrators can quickly get up to speed.

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I'm pleased to announce the publication of gj :: dataLoader, a new VS Code extension that simplifies the task of loading data from local CSV files into SQL tables on your InterSystems IRIS servers.

Here's an introductory video:

https://www.youtube.com/embed/XohVoW5rSy4
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What are best practices for JSON transformation in IRIS interoperability? This is for a non-healthcare use case, so any tools we happen to have around FHIR might not be available. The motivating use case is trimming down a verbose and needlessly complex REST API response to feed to an LLM - trying to reduce token usage and maybe get better results from less noisy data.

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The previous article introduced IrisOASTestGen, a tool designed to generate REST API test code for InterSystems IRIS based on OpenAPI 2.0 specifications. It demonstrated how to scaffold test cases using the default templates bundled with OpenAPI Generator.

This follow-up focuses on the next natural step: customizing the generated test code.
By extending the code generation logic with Mustache templates, it becomes possible to express richer semantics, implement CRUD-aware tests, and create more meaningful test suites.

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Hello!
I have the following XML document obtained through a string:

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<MainDocument xmlns="urn:hl7-org:v3">
<realmCode code="IT"/>
<title>kjbkjkjbkjb</title>
<effectiveTime value="20090905150716"/>
[.....other tags.....]
<versionNumber value="1"/>
<component>
<body>mhvjhjkvhj</body>
<component>
<section>content</section>
<ID>5</ID>

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Modern SQL engines are enormously complex pieces of software. Even when they appear stable and mature, subtle bugs can hide in their optimizers, type systems, predicate evaluation, or execution layers. These bugs rarely announce themselves loudly. Instead, they quietly produce incorrect results, behave inconsistently, or fail abruptly under specific combinations of SQL constructs.

This is precisely why tools like SQLancer exist. SQLancer automatically generates SQL queries and uses logical “oracles” to detect when a database behaves incorrectly. It has revealed hundreds of real bugs in widely used systems such as MySQL, PostgreSQL, SQLite, and DuckDB.

With this in mind, I attempted to bring SQLancer to InterSystems IRIS, starting with the NOREC oracle — a powerful method for detecting optimizer correctness issues. The journey, however, uncovered not just potential SQL correctness problems, but also a surprising number of driver-level and server-level failures that prevented SQLancer from running at full strength.

This article summarizes why SQLancer is important, how the NOREC oracle works, and what unexpected findings appeared while testing IRIS.

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One of the newest features of .Net core 10 with C# 14 is the file-based apps. This feature allows you to execute C# code in a simple .cs file without the need to create a solution, a project, or any of the related structure.

For example you can create a script.cs file using the notepad with the content:

Console.WriteLine(“This is a script in c#.”);

Then in the command line or the terminal you execute the command:

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Contestant

FastJsonSchema: High-Performance JSON Validation in IRIS

Validating JSON data against JSON Schema is a common requirement for modern applications. FastJsonSchema brings this capability natively to InterSystems IRIS, combining speed, simplicity, and full schema compliance.

Unlike traditional validation approaches, FastJsonSchema generates native ObjectScript code from your JSON Schemas and compiles it directly to iris object code, enabling idiomatic performance without relying on external libraries or runtimes.

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