where can I find a list of all command line utilities with a short description?

It's also an example of a customized SystemFunction extension (ZZISJSON) in Caché & IRIS
This time it is to be included in %ZLANGF00.mac

A JSON string is mostly imported from a file or over REST
You rely on a clean and compatible structure. This is the check.

required: ZPretty.mac

demo

Hi,

Recently I have encountered a new issue, more and more 3rd party applications move to the cloud.

Web-hooks incoming from their sites can no longer be identified using a known and fixed IP address, so our customer's security department blocks them.

In past similar cases we use to grant access in the customer's Fire-Wall to the specified IP address - this is no longer applicable.

Has anyone else encountered this problem ? do you have any ideas ?

Thanks

An all-in-1 package of the WebSocket MicroService Demo

To simplify the demo of the WebSocket-Micro-Server (WSockClientMicroSV)
the whole package is now bundled into a single Docker Image

How to use it

From the same terminal start the IRIS based client and prepare your orders

  docker-compose exec iris iris session iris %ZSocket

on WebTerminal it is simply

It is a classic Global Mapping exercise presenting ^SPOOL as Class / Table

Background

Device #2 named SPOOL dates back to the predecessors of Caché and IRIS
It was the first "%Stream" like option to buffer output before printing.
It is also the first and till today the most simple way of output redirection.

Solution

This is also an example of a mapped Global.
USE 2 redirects the output into the Global ^SPOOL

Hi,

I am attempting to set up a security role for our support team so they can have read access to the production and messages.

I have given the role RW rights on the resource associated with the database. However, when I log into Management Portal and select "Ensemble", the "Available Ensemble namespaces" list is empty.

What permissions do i need to set to be able to navigate to the production?

Thanks in advance,

Carl

Edit:

This is my introduction to a series of posts explaining how to create an end-to-end Machine Learning system.

Starting with one problem

Our IRIS Development Community has several posts without tags or wrong tagged. As the posts keep growing the organization
of each tag and the experience of any community member browsing the subjects tends to decrease.

First solutions in mind

We can think some usual solutions for this scenario, like:

Sapphire has CSV import, create and train IntegratedML model and I will create more features. See the pool. Check sapphire in https://openexchange.intersystems.com/package/SAPPHIRE

install and usage

Packed Pretty.xml installs routine ZPretty in any namespace.
calling $$Do^ZPretty(input,[filler],[newline]) returns a wrapped JSON string.
filler is the optional string for the indent, default = " "
newline is optional, default = $C(13,10)
input accepts: JSON_String, JSON_Stream, %DynamicAbstractObject

Currently, the process of using machine learning is difficult and requires excessive consumption of data scientist services. AutoML technology was created to assist organizations in reducing this complexity and the dependence on specialized ML personnel.

AutoML allows the user to point to a data set, select the subject of interest (feature) and set the variables that affect the subject (labels). From there, the user informs the model name and then creates his predictive or data classification model based on machine learning.

Hi Team,

When I tried to open ensemble in my system I got bellow error.

I have done lots of code in my local system but now not able to open the ensemble.

This is the second post of a series explaining how to create an end-to-end Machine Learning system.

Exploring Data

The InterSystems IRIS already has what we need to explore the data: an SQL Engine! For people who used to explore data in
csv or text files this could help to accelerate this step. Basically we explore all the data to understand the intersection
(joins) which should help to create a dataset prepared to be used by a machine learning algorithm.

What is the sql command to describe table in cache db.

Following up the previous part, it's time to take advantages for IntegratedML VALIDATION MODEL statement, to provide information in order to monitor your ML models. You can watch it in action here