This time I want to talk about something not specific to InterSystems IRIS, but that I think is important if you want to work with Docker and your server at work is a PC or laptop with Windows 10 Pro or Enterprise.

As you likely know, containers technology comes basically from Linux world and, nowadays, is on Linux hosts were it shows maximum potential. Those who use Windows on a normal basis see that both, Microsoft and Docker, have done important efforts during these last years that allow us to run containers based on Linux images on our Windows system in a really easy way... but it's something not supported for production systems and, this is the big problem, is not reliable if we want to keep persistent data outside of containers, in the host system,... mostly due to the big differences between Windows and Linux file systems. In the end, Docker for Windows itself uses a small linux virtual machine (MobiLinux) to run the containers... it does it transparently for the windows user... and it works perfectly well if, as I said, you don't require that your databases survive longer than the container...

Well,...let's get to the point,... the point is that many times, to avoid issues and simplify, we need a full Linux system and, if our server is based on Windows, the only way of having it is through a virtual machine. At least till WSL2 in Windows is released, but that will be another story and sure it'll take a bit of time to become robust enough.

In this article, I'll tell you, step by step, how to install an environment where you'll be able to work, if you need it, with Docker containers on an Ubuntu system in your Windows server. Let's go...

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Keywords: Python, JDBC, SQL, IRIS, Jupyter Notebook, Pandas, Numpy, and Machine Learning 

1. Purpose

This is another 5-minute simple note on invoking the IRIS JDBC driver via Python 3 within i.e. a Jupyter Notebook, to read from and write data  into an IRIS database instance via SQL syntax, for demo purpose. 

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Hi Developers!

Many of you publish your InterSystems ObjectScript libraries on Open Exchange and Github.

But what do you do to ease the usage and collaboration to your project for developers?

In this article, I want to introduce the way how to introduce an easy way to launch and contribute to any ObjectScript project just by copying a standard set of files to your repository.

Let's go!

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Over the past year or so, my team (Application Services at InterSystems - tasked with building and maintaining many of our internal applications, and providing tools and best practices for other departmental applications) has embarked on a journey toward building Angular/REST-based user interfaces to existing applications originally built using CSP and/or Zen. This has presented an interesting challenge that may be familiar to many of you - building out new REST APIs to existing data models and business logic.

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Last time we launched an IRIS application in the Google Cloud using its GKE service.

And, although creating a cluster manually (or through gcloud) is easy, the modern Infrastructure-as-Code (IaC) approach advises that the description of the Kubernetes cluster should be stored in the repository as code as well. How to write this code is determined by the tool that’s used for IaC.

In the case of Google Cloud, there are several options, among them Deployment Manager and Terraform. Opinions are divided as to which is better: if you want to learn more, read this Reddit thread Opinions on Terraform vs. Deployment Manager? and the Medium article Comparing GCP Deployment Manager and Terraform

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Keywords: Deep Learning, Grad-CAM, X-Ray, Covid-19, HealthShare, IRIS


Over the Easter Weekend I touched on some deep learning classifier for Covid-19 Lungs.  The demo result seems fine, seemingly matching some academic research publications around that time on this topic. But is it really "fine "? 

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Hi colleagues!

Every day Johns Hopkins University publishes new data on coronavirus COVID-19 pandemic status.

I built a simple InterSystems IRIS Analytics dashboard using InterSystems IRIS Community Edition in docker deployed on GCP Kubernetes which shows key measures of the disease outbreak.

This dashboard is an example of how information from CSV could be analyzed with IRIS Analytics and deployed to GCP Kubernetes in a form of InterSystems IRIS Community Edition.

Added the interactive map of the USA:

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Imagine you want to see what InterSystems can give you in terms of data analytics. You studied the theory and now you want some practice. Fortunately, InterSystems provides a project that contains some good examples: Samples BI. Start with the README file, skipping anything associated with Docker, and go straight to the step-by-step installation. Launch a virtual instance, install IRIS there, follow the instructions for installing Samples BI, and then impress the boss with beautiful charts and tables. So far so good. 

Inevitably, though, you’ll need to make changes.

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While the integrity of Caché and InterSystems IRIS databases is completely protected from the consequences of system failure, physical storage devices do fail in ways that corrupt the data they store.  For that reason, many sites choose to run regular database integrity checks, particularly in coordination with backups to validate that a given backup could be relied upon in a disaster.

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InterSystems has recently completed a performance and scalability benchmark of IRIS for Health 2020.1, focusing on HL7 version 2 interoperability. This article describes the observed throughput for various workloads, and also provides general configuration and sizing guidelines for systems where IRIS for Health is used as an interoperability engine for HL7v2 messaging.

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In the first article in this series, we’ll take a look at the entity–attribute–value (EAV) model in relational databases to see how it’s used and what it’s good for. Then we'll compare the EAV model concepts to globals.

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This is a coding example working on IRIS 2020.2 
It will not be kept in synch with new versions 
It is also NOT serviced by InterSystems Support !

My demo video is now also available to watch the demo in operation.


Hi folks,
It's time now for a Micro Service Demo with a total fresh IRIS Image and an image that you both PULL with
docker  and run with only 4 lines of docker commands. 
June 1st, 2020 - rcc

There is now a compact All-in-1 version available that combines all parts in a single container image.
For details see: IRIS-NativeAPI-Nodejs-compact
May 24, 2020 - rcc

I have added a simplified installation using Docker, see context
May 25, 2020 - rcc

There are enhanced scripts suitable & tested for Linux & Windows available here
May 26, 2020 - rcc

This demo is a redesign of the WebSocket Client based on Node.js existing already for Caché. The major changes:

  • use of the new IRIS Native API for Node.js  especially Working with Global Arrays
  • change from a directly triggered client to a server design
  • put the result into a separate docker image as an example for a MicroService / MicroServer
  • add a simple interface in IRIS to control the MicroService execution.

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In an earlier article (hope, you’ve read it), we took a look at the CircleCI deployment system, which integrates perfectly with GitHub. Why then would we want to look any further? Well, GitHub has its own CI/CD platform called GitHub Actions, which is worth exploring. With GitHub Actions, you don’t need to rely on some external, albeit cool, service.

In this article we’re going to try using GitHub Actions to deploy the server part of  InterSystems Package Manager, ZPM-registry, on Google Kubernetes Engine (GKE).

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Nowadays, there is a lot of applications that are using Open Authorization framework (OAuth) to access resources from all kinds of services in a secure, reliable and efficient manner. InterSystems IRIS is already compatible with OAuth 2.0 framework, in fact, there is a great article in the community regarding OAuth 2.0 and InterSystems IRIS in the following link here.

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InterSystems and Intel recently conducted a series of benchmarks combining InterSystems IRIS with 2nd Generation Intel® Xeon® Scalable Processors, also known as “Cascade Lake”, and Intel® Optane™ DC Persistent Memory (DCPMM). The goals of these benchmarks are to demonstrate the performance and scalability capabilities of InterSystems IRIS with Intel’s latest server technologies in various workload settings and server configurations. Along with various benchmark results, three different use-cases of Intel DCPMM with InterSystems IRIS are provided in this report.

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Keywords:  PyODBC, unixODBC, IRIS, IntegratedML, Jupyter Notebook, Python 3



A few months ago I touched on a brief note on "Python JDBC connection into IRIS", and since then I referred to it more frequently than my own scratchpad hidden deep in my PC. Hence, here comes up another 5-minute note on how to make "Python ODBC connection into IRIS".

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Igor Titarenko · Sep 10, 2020 3m read
How To Create "Write-Only" Code

One of the leading benefits of ObjectScript is the speed and efficiency it allows for an experienced developer. Let's look at an example of how you can benefit from ObjectScript today.

Suppose you have a class that stores the names of your users. We'll call the class Data.User, and give it a string property Name. Next, we will need a method to create a new user or update an existing one. A naive, simplistic approach might look like this example:


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I'm always on the lookout for tools that make the development and testing of my interfaces more efficient. A couple of years ago I came across HL7 Spy, from Inner Harbour Software. It quickly became my go-to tool for running message comparison reports for interface engine migrations, message statistics gathering, and troubleshooting message receipt and delivery. It also offered enhanced functionality for things like fetching messages via sftp that other tools don't provide.

I've recently been working with HL7 Spy's author, Jon Reis, to enable support for fetching messages directly from the Ensemble message store. Its SQL Loader feature now has native Caché/IRIS support, and I've contributed a small server-side class to support the extraction of messages using it.

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Dmitriy Maslennikov · May 11, 2020 5m read
Work with SAML in IRIS

When a company is quite large and many different applications used by employees. But while those applications are mostly completely different, how to make it possible to not force users to enter credentials as many times as many applications they would like to use. The best way is to use SSO, so, it will be possible to have a portal, where users could launch any application used in a company. There are many different ways how to give access to your application by using the SSO mechanism, and some of them are:

  • OAuth2
  • Kerberos
  • SAML

InterSystems already supports OAuth2 and can be quite easily deal with Kerberos. But I would like to discuss about using SAML (Security Assertion Markup Language).

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