I need to ingest streaming data over WebSockets. How can I create a custom inbound adapter for IRIS productions that supports many concurrent socket connections?

I want to build an event store using raw globals and replay events for rebuilding state. Can I hook into IRIS journaling or write my own event log and replay engine?

When writing dynamic SQL queries using embedded SQL, how can I force or ensure that filter conditions are pushed down to the data access layer rather than evaluated in memory?

We want to iterate over large global structures in real-time without blocking or locking readers. How can we safely use $Order() and implement a lock-free analytics approach?

What are the best practices for creating a multi-tenant app in IRIS? How can I isolate data per tenant using namespaces, control resource usage, and delegate access via roles securely?

For space optimization, we want to apply a domain-specific compression algorithm to binary stream data before writing to %Stream.GlobalBinary. Is it possible to override or extend stream classes to include compression/decompression?

Deploying new IRIS instances can be a time-consuming task, especially when setting up multiple environments with mirrored configurations.

I’ve encountered this issue many times and want to share my experience and recommendations for using Ansible to streamline the IRIS installation process. My approach also includes handling additional tasks typically performed before and after installing IRIS.

This code provide the configured production items with enabled or disabled status.

Include (Ensemble, EnsUI, EnsUtil)

Class Test.ProductionConfig
{

Hi Community,

It seems our Developer Community AI has decided to take a coffee break ☕️ (probably after answering one too many tricky ObjectScript questions).

For now, it’s gone mysteriously silent and refuses to generate answers. We suspect it might be rethinking its life choices after reading one too many deeply philosophical ObjectScript questions.

I know the next ones:

1. Place all different settings in environment variables. You have a different .env file for each environment, and you must add some code to Production for reading and setting these values. It's good for deploying into containers, but challenging for management when we have a large production. I mean, we have many settings that can vary depending on the environment: active flag, pool size, timeouts, and so on. Not only endpoints.

Hey Community,

We’re excited to announce a significant update to the Developer Community AI Chat — it now comes with a brand-new interface!

With this update, your experience becomes smoother and more intuitive:

• Easier navigation through your chats
• Clearer history and answers at a glance
• Seamless context retention for natural conversations

Introduction

In a previous article, I presented the IRIStool module, which seamlessly integrates the pandas Python library with the IRIS database. Now, I'm explaining how we can use IRIStool to leverage InterSystems IRIS as a foundation for intelligent, semantic search over healthcare data in FHIR format.

This article covers what I did to create the database for another of my projects, the FHIR Data Explorer. Both projects are candidates in the current InterSystems contest, so please vote for them if you find them useful.

You can find them at the Open Exchange:

• IRIStool and Data Manager
• FHIR Data Explorer

In this article we'll cover:

• Connecting to InterSystems IRIS database through Python
• Creating a FHIR-ready database schema
• Importing FHIR data with vector embeddings for semantic search

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
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With the rapid adoption of telemedicine, remote consultations, and digital dictation, healthcare professionals are communicating more through voice than ever before. Patients engaging in virtual conversations generate vast amounts of unstructured audio data, so how can clinicians or administrators search and extract information from hours of voice recordings?