In this article, we will run an InterSystems IRIS cluster using docker and Merge CPF files - a new feature allowing you to configure servers with ease.

On UNIX® and Linux, you can modify the default iris.cpf using a declarative CPF merge file. A merge file is a partial CPF that sets the desired values for any number of parameters upon instance startup. The CPF merge operation works only once for each instance.

Our cluster architecture is very simple, it would consist of one Node1 (master node) and two Data Nodes (check all available roles). Unfortunately, docker-compose cannot deploy to several servers (although it can deploy to remote hosts), so this is useful for local development of sharding-aware data models, tests, and such. For a productive InterSystems IRIS Cluster deployment, you should use either ICM or IKO.

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

Folks!

Recently I found several one-line long ObjectScript commands on DC and think that it'd be great not to lose it and to collect more!

So I decided to gather a few first cases, put in one OEX project, and share them with you!

And here is how you can use them.

While starting the development with IRIS we have a distribution kit or in case of Docker we are pulling the docker image and then often we need to initialize it and setup the development environment. We might need to create databases, namespaces, turn on/off some services, create resources. We often need to import code and data into IRIS instance and run some custom code to init the solution.

And there plenty of templates on Open Exchange where we suggest how to init REST, Interoperability, Analytics, Fullstack and many other templates with ObjectScript. What if we want to use only Python to setup the development environment for Embedded Python project with IRIS?

So, the recent release of Embedded Python template is the pure python boilerplate that could be a starting point for developers that build python projects with no need to use and learn ObjectScript. This article expresses how this template could be used to initialize IRIS. Here we go!

Hi Developers!

Recently we released the updated version 0.1.3 of ObjectScript Package Manager (ZPM) which comes with the support of simplified ObjectScript sources folder structure.

What 'simplified' does mean?

Before 0.1.3 ZPM expected the following structure:

/src

---/cls  - for ObjectScript classes

---/cls/package_name/class_name.cls

---/cls/package_name/class_name2.cls

---/mac - or Mac ObjectScript routines

---/mac/package_name/mac_routine.mac

---/mac/package_name/mac_routine2.mac

---/inc - for ObjectScript macro include files.

---/inc/package_name/include_file.inc

The OKR methodology (Objectives and Key Results or Objectives and Key Results) is used by the largest companies in the world (such as Google, Netflix, Spotify, BMW, Linkedin, etc.) for agile performance management. It was created in the 1970s by Andrew Grove, president of Intel, and introduced to the general public in his famous book “High Output Management”.

Around 1998 John Doerr, one of the world's top venture capitalists, after coming into contact with Intel's OKR, introduced the model to Larry Page and Sergey Brin, who started a small company called Google.

Hi Developers!

Often solutions with InterSystems IRIS BI can turn into a quite big solution with dozens of pivots and dashboards.

With every new IRIS BI solution release we can add changes that could influence the behavior of existing pivots or dashboards so they stop working. For example if we change the dimension or measure name, forget deploying some cubes or subject areas, conduct refactoring via mass renaming of cubes and its elements etc some widgets could stop functioning.

Translated from the Spanish Community Article Contest.

Following the latest programming contest on OEX I had some surprising observation.
There were almost exclusive applications based on AI in combination with pre-cooked Py modules.
But digging deeper, all examples used the same technical pieces of IRIS.

Seen from point of view of IRIS it was pretty much the same whether searching for text
or searching for images or other pattern. It ended in almost exchangeable methods.

There are many applications for working with HL7 V2 messages, but the tools for working with XML in IRIS Management Portal and Cache Studio are limited.

Millions of professionals use a wonderful tool, spreadsheets, for engineering calculations and financial analysis. It attracts a user-friendly interface and clear data organization. Cell formulas provide rich opportunities for automating calculations. No programming is required.

Hi Developers!

This is yet another short post that is intended to simplify developers' life. Now we'll talk about how to make GitHub run unit tests with every push to the repository by adding just one file to the repo. For free. On Github Cloud. Sounds great, isn't it?

It is possible and very easy to do. Credit goes to @Dmitry Maslennikov (and his repo), ZPM Package Manager, and GitHub Actions. Let's see how this all works!

Hi all!

I'm sharing a tool for data ingestion that we have used in some projects.

DataPipe is an interoperability framework for data ingestion in InterSystems IRIS in a flexible way. It allows you to receive data from external sources, normalize and validate the information and finally perform whatever operation you need with your data.

I think WebTerminal is an outstanding project, kudos to @Nikita Savchenko

Some of our applications provide SOAP services that use “DSTIME”-based SQL queries that return records that have recently been added or changed. Since the records don’t change often, these queries usually return a small number of records and therefore take little time.