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

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'm aware that some people might not be pleased by this article.
So I underline that this is my very personal view based on
working in this industry for more than a half-century.



If you develop in IRIS you are confronted with two major phenomena:

  • an incredibly fast and excellent designed data storage engine
  • a scripting language to work on this storage engine, actually named ObjectScript 

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Challenges of real-time AI/ML computations

We will start from the examples that we faced as Data Science practice at InterSystems:

  • A “high-load” customer portal is integrated with an online recommendation system. The plan is to reconfigure promo campaigns at the level of the entire retail network (we will assume that instead of a “flat” promo campaign master there will be used a “segment-tactic” matrix). What will happen to the recommender mechanisms? What will happen to data feeds and updates into the recommender mechanisms (the volume of input data having increased 25000 times)? What will happen to recommendation rule generation setup (the need to reduce 1000 times the recommendation rule filtering threshold due to a thousandfold increase of the volume and “assortment” of the rules generated)?
  • An equipment health monitoring system uses “manual” data sample feeds. Now it is connected to a SCADA system that transmits thousands of process parameter readings each second. What will happen to the monitoring system (will it be able to handle equipment health monitoring on a second-by-second basis)? What will happen once the input data receives a new bloc of several hundreds of columns with data sensor readings recently implemented in the SCADA system (will it be necessary, and for how long, to shut down the monitoring system to integrate the new sensor data in the analysis)?
  • A complex of AI/ML mechanisms (recommendation, monitoring, forecasting) depend on each other’s results. How many man-hours will it take every month to adapt those AI/ML mechanisms’ functioning to changes in the input data? What is the overall “delay” in supporting business decision making by the AI/ML mechanisms (the refresh frequency of supporting information against the feed frequency of new input data)?

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Fixing the terminology

A robot is not expected to be either huge or humanoid, or even material (in disagreement with Wikipedia, although the latter softens the initial definition in one paragraph and admits virtual form of a robot). A robot is an automate, from an algorithmic viewpoint, an automate for autonomous (algorithmic) execution of concrete tasks. A light detector that triggers street lights at night is a robot. An email software separating e-mails into “external” and “internal” is also a robot. Artificial intelligence (in an applied and narrow sense, Wikipedia interpreting it differently again) is algorithms for extracting dependencies from data. It will not execute any tasks on its own, for that one would need to implement it as concrete analytic processes (input data, plus models, plus output data, plus process control). The analytic process acting as an “artificial intelligence carrier” can be launched by a human or by a robot. It can be stopped by either of the two as well. And managed by any of them too.

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YURI MARX GOMES · Nov 18, 2020 7m read
Creating a PEX Business Operation

PEX is a new InterSystems IRIS feature to allows extends IRIS with existent features from Java or .NET.

It is possible create interoperability inbound and outbound adapters, business services (integrate from external to internal) and operations (integrate internal to external).

To create a PEX component it is necessary import .NET (InterSystems.EnsLib.PEX.*) or Java (com.intersystems.enslib.pex.*) packages and extends or implements the properly class.

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In this post I show strategies for backing up Caché using External Backup with examples of integrating with snapshot based solutions. The majority of solutions I see today are deployed on Linux on VMware so a lot of the post shows how solutions integrate VMware snapshot technology as examples.

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Hi all,


I want to share a quick little method you can use to enable ssl with a self signed certificate on your local development instance of IRIS/HealthShare. This enables you to test https-specific features such as OAuth without a huge lift.



1. Install OpenSSL


Debian Linux: $ sudo apt-get -y install openssl

RHEL: $ sudo yum install openssl


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Recently I wanted to get a list of all cached queries and their texts. Here's how to do that.

First create an SQL Procedure returning Cache Query text from a Cached Query routine name:

Class test.CQ

/// SELECT test.CQ_GetText()
ClassMethod GetText(routine As %String) As %String [ CodeMode = expression, SqlProc ]


And after that you can execute this query:

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Hi Community,

Did you know about OWASP and Top Ten Web Application security risks to your Web API or Web Apps?

OWASP is a community foundation created to help us to improve the security of web apps/web APIs. OWASP do the web apps more secure through its community-led open source software projects, hundreds of chapters worldwide, tens of thousands of members, and by hosting local and global conferences.

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Robert Cemper · Feb 8, 2019 2m read
Client for WebSockets based on Node.js

WebSockets as a communication technology wins increasing importance.
In the SAMPLES namespace, you find a nice example for running a WebSocket Server.
There is also a useful example for a Browser Client. JavaScript does most of the work. 

My point is:
How to consume the output of a WebSocket Server in your application?

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Dmitry 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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Robert Cemper · Apr 26, 2020 5m read
Materialized Views

A VIEW in SQL is basically a prepared SQL statement.
It has to be executed and assembled like any other SQL query.
MATERIALIZED VIEW means that the content is collected before hands and can be retrieved rather fast.
I saw the concept first with my favorite competitor named O* and they made a lot of noise about it.

  { favorite: because I could win every benchmark against them devil }

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InterSystems SAM is a great tool to monitor your InterSystems IRIS and InterSystems IRIS For Health clusters on prem or in a cloud environment. This article describes how you can implement a customized alert handler. This is currently an undocumented and most likely an unknown feature of InterSystems SAM. With future releases it will be probably made easier to leverage this useful concept.

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Henrique Dias · Apr 20 2m read
ZPM Explorer

Hi Community,

@José Roberto Pereira and I want to introduce ZPM Explorer, our graphic interface to explorer the greats applications that we have inside InterSystems Package Manager.

The idea

ZPM Explorer's idea is to make it easier for people to find out what ZPM offers. Every week, every day, a new app joins the ZPM world, so why not help developers and non-developers take advantage of this incredible world?!

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This is a demo to make use of a simple WebSocket Client with Embedded Python in IRIS.

To continue my series of WebSocket Client I have added an example written in Python.
The most impressive experience was how easy the writing and testing of the client was
which happened total offline from IRIS.
Embedding, running and feeding the client with data from IRIS was also incredibly simple.

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Dmitrii Kuznetsov · Feb 15 17m read
Four Database APIs

A concurrent session in IRIS:
SQL, Objects, REST, and GraphQL

Kazimir Malevich, "Athletes" (1932)

"But of course you don't understand! How can a person who has always traveled in a horse-drawn carriage understand the feelings and impressions of the express traveler or the pilot in the air?"

Kazimir Malevich (1916)


We’ve already addressed the topic of why object/type representation is superior to SQL for implementing subject area models. And those conclusions and facts are as true now as they have ever been. So why should we take a step back and discuss technologies that drag abstractions back to the global level, where they had been in the pre-object and pre-type era? Why should we encourage the use of spaghetti code, which results in bugs that are hard to track down, and which relies only on virtuoso developer skills? 

There are several arguments in favor of transmitting data via SQL/REST/GraphQL-based APIs as opposed to representing them as types/objects:

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In this article, I will show how you can easily containerize  .Net/Java Gateways.

For our example, we will develop an Integration with Apache Kafka.

And to interoperate with Java/.Net code we will use PEX .



Our solution will run completely in docker and look like this:


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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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