From time to time, we get the previous question in support, something or someone is using more licenses than expected, and we need to find what. 

We have two scenarios. The first scenario is when we realize that the licenses are exhausted when the application does not work or when we try to connect through the terminal and get the "lovely"



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When you have been using cubes for business intelligence in a namespace for some time, you may find that there are many cubes in the namespace, only some of which are actively being used. However, it can be difficult to tell which cubes users are or are not querying, and maintaining unused cubes can be costly both in terms of storage and of computation to keep them up to date. This article provides some suggestions and examples for monitoring which cubes are in active use, and for removing cubes that you determine are no longer necessary.

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Evgeny Shvarov · Aug 2, 2020 1m read
Application Errors Analytics

Hi Developers!

As you know the application errors live in ^ERRORS global. They appear there if you call:

d e.Log() 

in a Catch section of Try-Catch.

With @Robert Cemper's approach, you can now use SQL to examine it.

Inspired by Robert's module I introduced a simple IRIS Analytics module which shows these errors in a dashboard:

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Hi All,

With this article, I would like to show you how easily and dynamically System Alerting and Monitoring (or SAM for short) can be configured. The use case could be that of a fast and agile CI/CD provisioning pipeline where you want to run your unit-tests but also stress-tests and you would want to quickly be able to see if those tests are successful or how they are stressing the systems and your application (the InterSystems IRIS backend SAM API is extendable for your APM implementation). 

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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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Released with no formal announcement in IRIS preview release 2019.4 is the /api/monitor service exposing IRIS metrics in Prometheus format. Big news for anyone wanting to use IRIS metrics as part of their monitoring and alerting solution. The API is a component of the new IRIS System Alerting and Monitoring (SAM) solution that will be released in an upcoming version of IRIS.

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David Underhill · Jul 12, 2019 2m read
Basic Database Metrics example

This is a self contained class that can be run from the Intersystems Task Scheduler which records peak usage details for databases and licenses built up throughout the day and retaining 30 days history.

To schedule the task to run every hour:  

d ##class(Metrics.Task).Schedule()

You can also specify your own start time, stop time, and run interval:

d ##class(Metrics.Task).Schedule(startTime, stopTime, intervalMins)

Metrics are stored in ^Metrics in the namespace that the class resides in/is run from.

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Robert Cemper · May 29, 2019 1m read
Simple Remote Server Control

This example is extracted from a long-running installation. The purpose is to have a simple monitoring of several servers at a rather primitive level. Just slightly more intelligent than a raw PING. But still easy to integrate. It avoids the overkill of information you are often confronted with while you are just interested in the number of active processes or similar basic figures.

The code is available for you here 

This is a coding example working on Caché 2018.1.3 and IRIS 2020.2 
It will not be kept in sync with new versions 
It is also NOT serviced by InterSystems Support !

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David Loveluck · Feb 25, 2019 4m read
Using Grafana directly from IRIS

There have been some very helpful articles in the community that show how to use Grafana with IRIS (or Cache/Ensemble) by using an intermediate database.

But I wanted to get at IRIS structures directly. In particular, i wanted to access the Cache History monitor data that is accessible by SQL as described here

and didn't want anything between me and the data.

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I wanted to see some alerts that occur in my Productions in a Mobile Device, I came across recently that although has an upfront cost  $5 you can send as many messages as you like after that, there is a 7 day free trial to check it out.

To Integrate this with a production I did the following.

Create an account and set up a device on

Record the following API Keys from the web site on the main page you will see

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APM normally focuses on the activity of the application but gathering information about system usage gives you important background information that helps understand and manage the performance of your application so I am including the IRIS History Monitor in this series.

In this article I will briefly describe how you start the IRIS or Caché History Monitor to build a record of the system level activity to go with the application activity and performance information you gather. I will also give examples of SQL to access the information.

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Hi Community,

This article assumes that you are familiar with Zabbix and SNMP monitoring, if not, there are some very interesting posts on the Community, especially this one ( which contains a lot of information on how to configure and request an SNMP Cache server.  

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Note (June 2019): A lot has changed, for the latest details go here

Note (Sept 2018): There have been big changes since this post first appeared, I suggest using the Docker Container version, the project and details for running as a container are still in the same place  published on GitHub so you can download, run - and modify if you need to.

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Mikhail Khomenko · Feb 13, 2017 14m read
Creating custom SNMP OIDs

This post is dedicated to the task of monitoring a Caché instance using SNMP. Some users of Caché are probably doing it already in some way or another. Monitoring via SNMP has been supported by the standard Caché package for a long time now, but not all the necessary parameters are available “out of the box”. For example, it would be nice to monitor the number of CSP sessions, get detailed information about the use of the license, particular KPI’s of the system being used and such. After reading this article, you will know how to add your parameters to Caché monitoring using SNMP.

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Carter Tiernan · Dec 22, 2016 2m read
The Polymetric Dashboard

> Customizable System Monitoring. ## Introduction The Polymetric Dashboard is a stand-alone module that provides enhanced monitoring tools for a Caché environment. Equipped with over one hundred sensors that monitor key system metrics, a robust REST API, and a modular AngularJS user interface, the Polymetric Dashboard is fully functional out of the box. However, the Polymetric Dashboard is designed to be customizable; any system metric can be monitored by creating a new sensor, and the visualization of collected data can be tailored to specific requirements and purposes.

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