Are you using Jupyter Notebooks with IRIS? Are you using the vscode-iris-jupyter-server VS Code extension for your notebooking? If so, please let me know either via direct message or with a comment on this post. I'd like to hear more about how our customers are working with tool specifically, and with data science more generally.

Thanks!

Hi Community,

We're happy to announce that registration for the event of the year — InterSystems Ready 2025 — is now open. This is the Global Summit we all know and love, but with a new name!

➡️ InterSystems Ready 2025

🗓 Dates: June 22-25, 2025

📍 Location: Signia Hilton Bonnet Creek, Orlando, FL, USA

Hi Community,

Let's meet at the online meetup with the winners of the AI Programming Contest: Vector Search, GenAI and AI Agents! It's a great opportunity to chat with the InterSystems Experts team and our contestants.

Winners' demo included!

Date & Time: Thursday, April 10, 12:00 pm EDT | 6:00 pm CEST

https://www.youtube.com/embed/wRuuKtYSU74?si=v0YREzoZ15gMqEz_
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Background

Embeddings is a new IRIS feature empowering the latest capability in AI semantic search.
This presents as a new kind of column on a table that holds vector data.
The embedding column supports search for another existing column of the same table.
As records are added or updated to the table, the supported column is passed through an AI model and the semantic signature is returned.
This signature information is stored as the vector for future search comparison.

Hey Community,

Enjoy the new video on InterSystems Developers YouTube:

⏯ Introduction to OMOP Platform

https://www.youtube.com/embed/5O9J-tRQZM8
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Hi Community,

It's time to announce the winners of the AI Programming Contest: Vector Search, GenAI and AI Agents!

Thanks to all our amazing participants who submitted 15 applications 🔥

Now it's time to announce the winners!

Migrating InterSystems IRIS and InterSystems IRIS for Health from on-premises to the cloud offers many advantages for Application Providers and Solution Providers. These advantages include simplified operations, access to flexible resources, and enhanced resilience. Companies no longer need to worry about the physical constraints and expenses associated with maintaining on-prem infrastructure, such as power and space requirements and expensive computer hardware.

One of the most compelling benefits is the ability to accelerate speed to market. By removing the burden of infrastructure maintenance, cloud environments enable faster development and deployment cycles, allowing businesses to respond quickly to market demands and opportunities. Operational costs are also lowered, because companies can scale resources up or down based on actual needs, leading to more efficient use of capital. Moreover, migrating to the cloud can contribute to a reduced carbon footprint by optimizing energy usage through shared cloud infrastructure.

Transitioning to the cloud may involve significant changes. Companies may benefit from a more operational focus, managing and optimizing cloud resources continuously. This shift may require changes to business models, reconsideration of margins, and strategies for scaling operations up or out. While requiring more investment, embracing these changes can lead to improved agility and competitive advantage in the marketplace.

Introduction

Database performance has become a critical success factor in a modern application environment. Therefore identifying and optimizing the most resource-intensive SQL queries is essential for guaranteeing a smooth user experience and maintaining application stability.

This article will explore a quick approach to analyzing SQL query execution statistics on an InterSystems IRIS instance to identify areas for optimization within a macro-application.

Rather than focusing on real-time monitoring, we will set up a system that collects and analyzes statistics pre-calculated by IRIS once an hour. This approach, while not enabling instantaneous monitoring, offers an excellent compromise between the wealth of data available and the simplicity of implementation.

We will use Grafana for data visualization and analysis, InfluxDB for time series storage, and Telegraf for metrics collection. These tools, recognized for their power and flexibility, will allow us to obtain a clear and exploitable view.

More specifically, we will detail the configuration of Telegraf to retrieve statistics. We will also set up the integration with InfluxDB for data storage and analysis, and create customized dashboards in Grafana. This will help us quickly identify queries requiring special attention.

To facilitate the orchestration and deployment of these various components, we will employ Docker.

To VSCode experts - see the screenshot. When right-click on a method with intentions to proceed to the source code:

I am always confused about what to choose: declaration or definition. What is the difference?

We have an OAuth server configured as an identity provider, and we have an external application (from another provider) that connects correctly with OAuth.

Due to the needs of the project, what we want to do is the following:

Hey Community,

It's time for the new batch of #KeyQuestions from the previous month.

Hi Community,

Traditional keyword-based search struggles with nuanced, domain-specific queries. Vector search, however, leverages semantic understanding, enabling AI agents to retrieve and generate responses based on context—not just keywords.

This article provides a step-by-step guide to creating an Agentic AI RAG (Retrieval-Augmented Generation) application.

Implementation Steps:

1. Create Agent Tools
   • Add Ingest functionality: Automatically ingests and index documents (e.g., InterSystems IRIS 2025.1 Release Notes).
   • Implement Vector Search Functionality
2. Create Vector Search Agent
3. Handoff to Triage (Main Agent)
4. Run The Agent

See the Langchain IRIS Tool in action on YouTube. You can see IRIS metrics, discover classes, generate fake data, and so on. Project using Ollama, IRIS VectorDB, Streamlit and Langchain.

I deployed an IRIS REST application using Installer class. I think I created the namespace FEEDER database with %DB_Default resource and I used the same resource in Web Application roles. I allowed Unauthenticated Authentication method. I used ^%ISCLOG and reviewed ^ISCLOG. I do not understand why I get 403 Forbidden response.