#Interoperability

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In healthcare, interoperability is the ability of different information technology systems and software applications to communicate, exchange data, and use the information that has been exchanged.

Hi Community,

In the first part of this series, we examined the fundamentals of Interoperability on Python (IoP), specifically how it enables us to construct such interoperability elements as business services, processes, and operations using pure Python.

Now, we are ready to take things a step further. Real-world integration scenarios extend beyond simple message handoffs.They involve scheduled polling, custom message structures, decision logic, filtering, and configuration handling.In this article, we will delve into these more advanced IoP capabilities and demonstrate how to create and run a more complex interoperability flow using only Python.

To make it practical, we will build a comprehensive example: The Reddit Post Analyzer Production. The concept is straightforward: continuously retrieving the latest submissions from a chosen subreddit, filtering them based on popularity, adding extra tags to them, and sending them off for storage or further analysis.

The ultimate goal here is a reliable, self-running data ingestion pipeline. All major parts (the Business Service, Business Process, and Business Operation) are implemented in Python, showcasing how to use IoP as a Python-first integration methodology.

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Modern data architectures utilize real-time data capture, transformation, movement, and loading solutions to build data lakes, analytical warehouses, and big data repositories. It enables the analysis of data from various sources without impacting the operations that use them. To achieve this, establishing a continuous, scalable, elastic, and robust data flow is essential. The most prevalent method for that is through the CDC (Change Data Capture) technique. CDC monitors for small data set production, automatically captures this data, and delivers it to one or more recipients, including analytical data repositories. The major benefit is the elimination of the D+1 delay in analysis, as data is detected at the source as soon as it is produced, and later is replicated to the destination.

This article will demonstrate the two most common data sources for CDC scenarios, both as a source and a destination. For the data source (origin), we will explore the CDC in SQL databases and CSV files. For the data destination, we will use a columnar database (a typical high-performance analytical database scenario) and a Kafka topic (a standard approach for streaming data to the cloud and/or to multiple real-time data consumers).

Overview

This article will provide a sample for the following interoperability scenario:

Open Exchange app
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The 2025.3 release of InterSystems IRIS® data platform, InterSystems IRIS® for Health, and HealthShare® Health Connect is now Generally Available (GA). This is a Continuous Delivery (CD) release.

Release Highlights:

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Hey Community,

Enjoy the new video on InterSystems Developers YouTube:

⏯ Using SerenityGPT to Build Out an Application GenAI Middleware at InterSystems @ Ready 2025

https://www.youtube.com/embed/ZXULSWMmOD0
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When I started my journey with InterSystems IRIS, especially in Interoperability, one of the initial and common questions I had was: how can I run something on an interval or schedule? In this topic, I want to share two simple classes that address this issue. I'm surprised that some similar classes are not located somewhere in EnsLib. Or maybe I didn't search well? Anyway, this topic is not meant to be complex work, just a couple of snippets for beginners.

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The Interoperability user interface project has continued from 2025.1 and has incorporated many of the items that you – our customers and partners – have suggested and observed. We are continuing to invest in feedback and updating this important user experience. In the latest relea

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Hello Community,

Great news for developers who have just started working with InterSystems IRIS! We have hands‑on interactive tutorials available via the Instruqt platform! These are perfect for getting up to speed quickly, playing in real environments, and building confidence with IRIS‑based development.

Here is the list of available tutorials:

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I am using IRIS for Windows (x86-64) 2022.1 (Build 209) Tue May 31 2022 12:27:55 EDT [Health:3.5.0]. I created Interoperability Production with a Service to read file from S3 bucket and an Operation to write files to a different S3 bucket. I specified AWS ProviderCredentialsFile.

I see "Terminating Job 7096 / 'From S3 Bucket' with Status = ERROR #5023: Remote Gateway Error: Connection cannot be established, %QuitTask=

Do I need anything like Python libraries or AWS CLI to make this work?

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