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#InterSystems IRIS

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InterSystems IRIS is a Complete Data Platform
InterSystems IRIS gives you everything you need to capture, share, understand, and act upon your organization’s most valuable asset – your data.
As a complete platform, InterSystems IRIS eliminates the need to integrate multiple development technologies. Applications require less code, fewer system resources, and less maintenance.

Article
· Mar 31, 2023 3m read
Using JSON in IRIS

Saw the other day an article with the usage of the %ZEN package when working with JSON and decided to write an article describing a more modern approach. At some recent point, there was a big switch from using %ZEN.Auxiliary.* to dedicated JSON classes. This allowed to work with JSONs more organically.

Thus, at this point there are basically 3 main classes to work with JSON:

  • %Library.DynamicObject - provides a simple and efficient way to encapsulate and work with standard JSON documents. Also, there is a possibility instead of writing the usual code for creating an instance of a class like
set obj = ##class(%Library.DynamicObject).%New()

it is possible to use the following syntax

set obj = {}
  • %Library.DynamicArray - provides a simple yet efficient way to encapsulate and work with standard JSON arrays. With arrays you can use the same approach as with objects, meaning that yu can either create an instance of the class
set array = ##class(%DynamicArray).%New()

or you can do it by using brackets []

set array = []
  • %JSON.Adaptor is a means for mapping ObjectScript objects (registered, serial or persistent) to JSON text or dynamic entities.
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Pouring The Coffee: Creating and scheduling a task

Don't you wish a fresh, hot cup of coffee could be waiting for you right when you get into the office? Let's automate that!

Cache and IRIS come with a built-in Task Manager, which should have a familiar feel to those used to using the Windows task scheduler or using cron on Linux. Your user account will need access to the %Admin_Task resource to use it, and you can access it in the management portal under System Operation -> Task Manager. When first installed, there are roughly 20 types of task that you can schedule.

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Hi Developers!

Often I find questions on how to install IRIS, connect to IRIS from IDE, setup the environment, compile, debug, maintain the repository.

Here below possibly the shortest way to set up all the environment and start development with ObjectScript on InterSystems IRIS.

Prerequisites

Make sure you have Git, Docker, and VSCode installed

Install Docker and ObjectScript extensions into VSCode

Sign in or Create an account on Github

Here we go!

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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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Foreword

InterSystems IRIS versions 2022.2 and newer feature the ability to authenticate to a REST API using JSON web tokens (JWTs). This feature enhances security by limiting where and how often passwords transfer over the network in addition to setting an expiration time on access.

The goal of this article is to serve as a tutorial on how to implement a mock REST API using InterSystems IRIS and lock access to it behind JWTs.

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The following steps show you how to display a sample list of metrics available from the /api/monitor service.

In the last post, I gave an overview of the service that exposes IRIS metrics in Prometheus format. The post shows how to set up and run IRIS preview release 2019.4 in a container and then list the metrics.

This post assumes you have Docker installed. If not, go and do that now for your platform :)

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In the previous parts (1, 2) we talked about globals as trees. In this article, we will look at them as sparse arrays.

A sparse array - is a type of array where most values assume an identical value.

In practice, you will often see sparse arrays so huge that there is no point in occupying memory with identical elements. Therefore, it makes sense to organize sparse arrays in such a way that memory is not wasted on storing duplicate values.

In some programming languages, sparse arrays are part of the language - for example, in J, MATLAB. In other languages, there are special libraries that let you use them. For C++, those would be Eigen and the like.

Globals are good candidates for implementing sparse arrays for the following reasons:

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Article
· Jul 27, 2018 4m read
Load a ML model into InterSystems IRIS

Hi all. Today we are going to upload a ML model into IRIS Manager and test it.

Note: I have done the following on Ubuntu 18.04, Apache Zeppelin 0.8.0, Python 3.6.5.

Introduction

These days many available different tools for Data Mining enable you to develop predictive models and analyze the data you have with unprecedented ease. InterSystems IRIS Data Platform provide a stable foundation for your big data and fast data applications, providing interoperability with modern DataMining tools.

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Introduction

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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Continuing on with providing some examples of various storage technologies and their performance profiles, this time we looked at the growing trend of leveraging internal commodity-based server storage, specifically the new HPE Cloudline 3150 Gen10 AMD processor-based single socket servers with two 3.2TB Samsung PM1725a NVMe drives.

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cAdvisor (short for container Advisor) analyzes and exposes resource usage and performance data from running containers. cAdvisor exposes Prometheus metrics out of the box.

https://prometheus.io/docs/guides/cadvisor/

Prometheus is integrated in SAM. This makes it possible to leverage the cAdvisor metrics and expose them via Prometheus and Grafana.

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I have been using embedded python for more than 2 years now on a daily basis.
May be it's time to share some feedback about this journey.

Why write this feedback? Because, I guess, I'm like most of the people here, an ObjectScript developer, and I think that the community would benefit from this feedback and could better understand the pros & cons of chosing embedded python for developing stuff in IRIS. And also avoid some pitfalls.

image

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"Telegram" is a well-known instant messenger, which provides an API for creating bots. The features of this API allow you to create bots with a wide range of functionality including receiving payments.
With the help of the telegram bot, I solved a simple task - sending Alerts from Ensemble to Telegram.

Advantages: Alerts come to the mobile phone, a notification appears, so there is no need to install any additional applications (in contrast to the solution https://community.intersystems.com/post/sending-alerts-mobile-phone-using-pushover- httpoutboundadapter).

The bot can be extended by adding new commands, for example, for managing the Production or for solving other tasks in Iris, Ensemble or Cache.

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How can you allow computers to trust one another in your absence while maintaining security and privacy?

“A Dry Martini”, he said. “One. In a deep champagne goblet.”
“Oui, monsieur.”
“Just a moment. Three measures of Gordons, one of vodka, half a measure of Kina Lillet. Shake it very well until it’s ice-cold, then add a large thin slice of lemon peel. Got it?”
"Certainly, monsieur." The barman seemed pleased with the idea.
Casino Royale, Ian Fleming, 1953


OAuth helps to separate services with user credentials from “working” databases, both physically and geographically. It thereby strengthens the protection of identification data and, if necessary, helps you comply with the requirements of countries' data protection laws.

With OAuth, you can provide the user with the ability to work safely from multiple devices at once, while "exposing" personal data to various services and applications as little as possible. You can also avoid taking on "excess" data about users of your services (i.e. you can process data in a depersonalized form).

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In this series of articles, I'd like to present and discuss several possible approaches toward software development with InterSystems technologies and GitLab. I will cover such topics as:

  • Git 101
  • Git flow (development process)
  • GitLab installation
  • GitLab Workflow
  • Continuous Delivery
  • GitLab installation and configuration
  • GitLab CI/CD
  • Why containers?
  • Containers infrastructure
  • CD using containers
  • CD using ICM
  • Container architecture

In this article, we would talk about building your own container and deploying it.

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With the release of InterSystems IRIS Cloud SQL, we're getting more frequent questions about how to establish secure connections over JDBC and other driver technologies. While we have nice summary and detailed documentation on the driver technologies themselves, our documentation does not go as far to describe individual client tools, such as our personal favourite DBeaver. In this article, we'll describe the steps to create a secure connection from DBeaver to your Cloud SQL deployment.

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