This article is a continuation of this post.

In the previous article, we discussed the development of business processes, which are part of the components required for system integration and serve as a production coordinator.

It's a challenge when you need, as a software architect, design a corporate architecture to meet the current business requirements, you need achieve level 5. With InterSystems IRIS.
it's possible. With 1 product you get SQL + NoSQL + ESB + BI + Open Analytics + Real time virtual cubes + NLP + AutoML + ML (with Python) and Advanced cloud + Sharding support.

The InterSystems Server Manager extension for Visual Studio Code lets you define connections to your servers, list their namespaces and edit or view code there. You can also launch Portal for a server.

Server Manager 3.0 improves security by becoming a VS Code Authentication Provider. It is my entry for the November 2021 InterSystems Security Contest. Click here to visit the contest page where you may decide to vote for this entry. Please ignore the clickable "Contestant" label on this article header above, as it relates to a different contest for new DC articles. If you want to support me in that contest, simply "like" this post.

Hi developers,

In this post, we would like to tell you how to take the most out of the Developer Community, to learn as much as you can from the InterSystems experts on the technology!

Pay attention to these steps to become an advanced user of our community!

This article is a follow-up to this post.

In the previous article, [What is a Production?], we checked the production contents. We ran the sample code and checked the flowing messages' contents into the production on the Visual Trace page.

I'd like to share with you some storage features that also exist in Caché but are almost
unknown and mostly not used. They are of course available in IRIS and gain importance
with large and distributed storage architectures.

1. Integrated ML Demonstration

This repository is a demonstration of IntegratedML and Embedded Python.

• 1. Integrated ML Demonstration
• 2. Building the demo
  • 2.1. Architecture
  • 2.2. Building the nginx container
• 3. Running the demo
• 4. Python back-end
  • 4.1. Embedded Python
  • 4.1.1. Setting up the container
  • 4.1.2. Using Embedded Python
  • 4.1.3. Side By Side Comparaison
  • 4.2. Launching the server
• 5. IntegratedML
  • 5.1. Exploring both datasets
  • 5.2. Managing models
  • 5.2.1. Creating a model
  • 5.2.2. Training a model
  • 5.2.3. Validating a model
  • 5.2.4. Making predictions
• 6. Using COS
• 7. More explainability with DataRobot
• 8. Conclusion

Testing ECP-based applications often take quite some effort for setup and preparation.
I have created a Docker-based workbench that allows you to have it quick at hands.
And if you crash it? You just give your containers a fresh start.
The whole setup runs code-based during the start-up of your instance.
In that sense, it is also a portable coding example using ZPM and the objectscript-docker-template

see Video

InterSystems technologies are renowned for their high performing databases, which support the systems and operations of many organisations. However a key ingredient to this success is the quality and maintainability of their code.

The quality of code can impact everything from speed and ease of fixing bugs and making enhancements, to the overall performance of your organization and your ability to get ahead in the marketplace.

By ensuring your code is maintainable, you can reduce approximately 75% of the systems life cycle costs*. This is why, at George James Software, the solutions we build are always straightforward and written in high quality code - because we know that this solid foundation can positively impact the rest of your organization.

With a maintainable system you're able to reduce your overall maintenance as any issues that occur are significantly faster to identify and fix. This means you're free to allocate that time and budget to enhancements, enabling you to get the most value out of your applications and ultimately better support your organization.

Keep an eye out for our next few posts about what a maintainable system looks like and the tools that can help you keep your code maintainable, in order to help you to reduce those maintenance costs.

Talking with a friend of mine, Machine Learning specialist @Renato Banzai , he brought one of the biggest challenges faced by companies nowadays: deploying ML/AI in live environments.

I'm running reviews on Open Exchange since April 2021.
I have seen excellent packages, good ones, and some that made me feel just lost.
And I started to recognize contributors also by their style and organization of the submitted packages.

Artificial intelligence has solved countless human challenges – and medical coding might be next.
As organizations prepare for ICD-11, medical coding is about to become more complicated. Healthcare organizations in the United States already manage 140,000+ codes in ICD-10. With ICD-11, that number will rise.
Some propose artificial intelligence as a solution. AI could aid computer-based medical coding systems, identifying errors, enhancing patient care, and optimizing revenue cycles, among other benefits.

Inspired by @Evgeny Shvarov and his recent article
Deploying InterSystems IRIS Embedded Python Solutions with ZPM Package Manager
I propagated the idea forward to do the same also for modules in Node.js.

For a long time, we have been using a utility in production to export the result of a query to an Excel spreadsheet. Moreover, we have applied a modification of it, in which the explicit setting of column formats is a priority.