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Every thriving community has members whose energy, creativity, and commitment help shape it into something extraordinary. In the InterSystems Developer Community, one such member is @Henry Pereira — a developer, open-source contributor, contest winner, and true believer in the power of collaboration.

👏 Let’s take a closer look at Henry’s remarkable journey and his continuing legacy in the InterSystems ecosystem.

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Starting out with ObjectScript, it is really exciting, but it can also feel a little unusual if you're used to other languages. Many beginners trip over the same hurdles, so here are a few "gotchas" you'll want to watch out for. (Also few friendly tips to avoid them)

NAMING THINGS RANDOMLY

We have all been guilty of naming something Test1 or MyClass just to move on quickly. But once your project grows, these names become a nightmare.

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Hi Community,

We're super excited and thankful to our 52 InterSystems colleagues who participated in the 📺 Demo Games for InterSystems Sales Engineers 📺 and created 19 amazing videos.

Our colleagues worldwide put their creativity, technical know-how, and demo magic to the test. What started as an internal contest to showcase technical skill and demo excellence became a true stage for imagination with some entries looking less like demos and more like short films, complete with acting, storytelling, and even a cinematic touch.

Also, we'd like to thank all the members of the Community who took the time to watch them and vote for their favourites!

And now it's time to announce the winners!

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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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Introduction

The InterSystems IRIS Data Platform has long been known for its performance, interoperability, and flexibility across programming languages. For years, developers could use IRIS with Python, Java, JavaScript, and .NET — but Go (or Golang) developers were left waiting.

Golang Logo

That wait is finally over.

The new go-irisnative driver brings GoLang support to InterSystems IRIS, implementing the standard database/sql API. This means Go developers can now use familiar database tooling, connection pooling, and query interfaces to build applications powered by IRIS.

Why GoLang Support Matters

GoLang is a language designed for simplicity, concurrency, and performance — ideal for cloud-native and microservices-based architectures. It powers some of the world’s most scalable systems, including Kubernetes, Docker, and Terraform.

Bringing IRIS into the Go ecosystem enables:

  • Lightweight, high-performance services using IRIS as the backend.
  • Native concurrency for parallel query execution or background processing.
  • Seamless integration with containerized and distributed systems.
  • Idiomatic database access through Go’s database/sql interface.

This integration makes IRIS a perfect fit for modern, cloud-ready Go applications.

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Table of Contents

  1. Purpose of the article
  2. What containers are and why they make sense with IRIS
     2.1 Containers and images in a nutshell
     2.2 Why containers are useful for developers
     2.3 Why IRIS works well with Docker
  3. Prerequisites
  4. Installing the InterSystems IRIS image
     4.1 Using Docker Hub
     4.2 Pulling the image
  5. Running the InterSystems IRIS image
     5.1 Starting an IRIS container
     5.2 Checking container status
     5.3 Executing code in the container terminal
     5.4 Accessing the IRIS Management Portal
     5.5 Connecting the container to VS Code
     5.6 Stopping or removing the container
     5.7 Setting a specific password with a bind mount
     5.8 Using durable %SYS volumes
      5.8.1 What gets stored with durable %SYS
      5.8.2 How to enable durable %SYS
  6. Using Docker Compose
     6.1 Docker Compose example
     6.2 Running Docker Compose
  7. Using a Dockerfile to run custom source code
     7.1 Dockerfile example
     7.2 Docker Compose example
     7.3 Understanding layers, image tagging and build vs. run time
     7.4 Source code and init script
     7.5 Building the image with Dockerfile
     7.6 Running instructions in the containerized IRIS terminal
  8. Conclusion and what’s next

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I am truly excited to continue my "InterSystems for Dummies" series of articles, and today, we want to tell you everything about one of the most powerful features we have for interoperability.

Hey, even if you have already had a go, we plan to take a really close look at how to get the most out of them and make our production even better.

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Article
· Sep 16 1m read
Reviews on Open Exchange - #55

If one of your packages on OEX receives a review you get notified by OEX only of YOUR own package.
The rating reflects the experience of the reviewer with the status found at the time of review.
It is kind of a snapshot and might have changed meanwhile.
Reviews by other members of the community are marked by * in the last column.

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Background

For a variety of reasons, users may wish to mount a persistent volume on two or more pods spanning multiple availability zones. One such use case is to make data stored outside of IRIS available to both mirror members in case of failover.

Unfortunately the built-in storage classes in most Kubernetes implementations (whether cloud or on-prem) do not provide this capability:

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Some languages ​​have the concept of a garbage collector for automatic memory management. I'd like to know if something like this exists in InterSystems Caché in the context of routines, %CSP.REST, or %CSP.Page.

The question arises from the %Close() method of the %RegisteredObject class. This indicates that I need to manually clear the object from memory if it's no longer in use, or in the web context, if the request has completed. Is this correct? Or am I completely wrong?

Thank you!

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If you thought native Go support for IRIS was exciting, wait until you see what happens when GORM enters the mix.

Just recently, we welcomed native GoLang support for InterSystems IRIS with the release of go-irisnative. That was just the beginning. Now, we’re kicking things up a notch with the launch of gorm-iris — a GORM driver designed to bring the power of Object Relational Mapping (ORM) to your IRIS + Go stack.

Why GORM?

GORM is one of the most popular ORM libraries in the Go ecosystem. It makes it easy to interact with databases using Go structs instead of writing raw SQL. With features like auto migrations, associations, and query building, GORM simplifies backend development significantly.

So naturally, the next step after enabling Go to talk natively with IRIS was to make GORM work seamlessly with it. That’s exactly what gorm-iris does.

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Background

For a variety of reasons, users may wish to mount a persistent volume on two or more pods spanning multiple availability zones. One such use case is to make data stored outside of IRIS available to both mirror members in case of failover.

Unfortunately the built-in storage classes in most Kubernetes implementations (whether cloud or on-prem) do not provide this capability:

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Ready to elevate your Business Intelligence game?

We've got an engaging video, perfect for all skill levels.

Discover how to get started with IRIS BI, optimize cube performance, and drive analytics adoption. Plus, get a sneak peek at what's next!

https://www.youtube.com/embed/Ekjzny8zj98
[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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Article
· Sep 16 14m read
High Availability IAM

One of the recommendations when deploying InterSystems Technologies for production is to set up High Availability. The recommended API Manager for these InterSystems Technologies is the InterSystems API Manager (IAM). IAM (essentially Kong Gateway) has multiple deployment topologies.

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Introduction

HL7 messages often contain multiple repeating segments such as NTE, AL1, OBX, ZTX, DG1, and others. These segments sometimes require individual processing and routing to different downstream systems. This technical paper introduces a configurable template designed to automate the splitting of these repeating HL7 segments, improving message handling and integration efficiency.

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I am working on a tool that configures an instance to use a common default routine database across all custom Namespaces. For instances that already have distinct default routine databases for their Namespaces, this would involve a step of merging over all code from the current default routine databases to the new "super" routine database. This should be done in such a way that only merges contents in the default routine database (not mapped databases) and is able to detect/exclude contents that already exist in the target database.

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Finishing my previous example for multiple IRIS instances, I tried
to compose a local single instance version. The step from the external
Python app to a version using embedded Python seemed to be obvious.
This was a wrong assumption, as some Python libraries just refused installation
into my local Windows-based environment.

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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.

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Hi,

Just thought I'd share quite a handy hook that has helped me out when developing on Health Connect Cloud with VS Code and GitBash. When developing on Health Connect Cloud, if changes are made directly on the server such as routing rules or component deployments, they aren't automatically included in source control, therefore you must export from the server into your local files and push to your remote repo. I'm sure there are easier methods to deal with that which I'm in the process of testing, but as a quick solution I thought it would be handy have a pre-commit hook which triggers a reminder in GitBash - see below.

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For historic reasons we've got a mix of ADT feeds coming out of our PAS (TrakCare) to a wide range of downstream systems. In particular, there are some that are direct from TrakCare to the downstream systems, and many more that pass through Ensemble as our integration engine.

This is complicating management of the integrations, and so we'd like everything to go through the integration engine. In other words move from the flow in the top of the diagram to the flow in the bottom of the diagram:

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Hi Community,

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

The importance of the coffee break

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.

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Is there any way of saving a representation of the results of a query created in the Message Viewer to a file - most obviously CSV.

We are reasonably adept at creating queries. We'd like to be able to send the output to a file, rather than resorting to cut'n'pasting from the message viewer window...

Is this possible? (on any version of Ensemble/Iris?)

Desired output to file something like:

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Hi,

It's me again😁, recently I am working on generating some fake patient data for testing purpose with the help of Chat-GPT by using Python. And, at the same time I would like to share my learning curve.😑

1st of all for building a custom REST api service is easy by extending the %CSP.REST

Creating a REST Service Manually

Let's Start !😂

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