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We’ve already considered how to run an IRIS-based application in GCP Kubernetes in Deploying InterSystems IRIS Solution into GCP Kubernetes Cluster GKE Using CircleCI. Additionally, we’ve seen how to run an IRIS-based application in AWS Kubernetes in Deploying a Simple IRIS-Based Web Application Using Amazon EKS. Now, let’s look at how to deploy an application to the Azure Kubernetes Service (AKS).

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Question
· Nov 1, 2021
Globals export exclusion

Hello everyone,
I'd like to export Ensemble globals, but without Ensemble messages, this way:

^^database>s list("Ens*.gbl,'Ens.Message*.gbl")=""
^^database>write $SYSTEM.OBJ.Export(.list, "/tmp/globals.xml")

Documentation says that it could be done by adding an apostrophe, but it doesn't work for me - all Ens* globals are still exported.
What I'm doing wrong? Thanks!

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In this article, we’ll look at one of the ways to monitor the InterSystems IRIS data platform (IRIS) deployed in the Google Kubernetes Engine (GKE). The GKE integrates easily with Cloud Monitoring, simplifying our task. As a bonus, the article shows how to display metrics from Cloud Monitoring in Grafana.

Note that the Google Cloud Platform used in this article is not free (price list), but you can leverage a free tier. This article assumes that you already have a project in the Google Cloud Platform (referred to as <your_project_id>) and have permission to use it.

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Introduction
Several resources tell us how to run IRIS in a Kubernetes cluster, such as Deploying an InterSystems IRIS Solution on EKS using GitHub Actions and Deploying InterSystems IRIS solution on GKE Using GitHub Actions. These methods work but they require that you create Kubernetes manifests and Helm charts, which might be rather time-consuming.
To simplify IRIS deployment, InterSystems developed an amazing tool called InterSystems Kubernetes Operator (IKO). A number of official resources explain IKO usage in details, such as New Video: Intersystems IRIS Kubernetes Operator and InterSystems Kubernetes Operator.

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This article is a continuation of Deploying InterSystems IRIS solution on GKE Using GitHub Actions, in which, with the help of GitHub Actions pipeline, our zpm-registry was deployed in a Google Kubernetes cluster created by Terraform. In order not to repeat, we’ll take as a starting point that:

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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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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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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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Last time we deployed a simple IRIS application to the Google Cloud. Now we’re going to deploy the same project to Amazon Web Services using its Elastic Kubernetes Service (EKS).

We assume you’ve already forked the IRIS project to your own private repository. It’s called <username>/my-objectscript-rest-docker-template in this article. <root_repo_dir> is its root directory.

Before getting started, install the AWS command-line interface and, for Kubernetes cluster creation, eksctl, a simple CLI utility. For AWS you can try to use aws2, but you’ll need to set aws2 usage in kube config file as described here.

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Most of us are more or less familiar with Docker. Those who use it like it for the way it lets us easily deploy almost any application, play with it, break something and then restore the application with a simple restart of the Docker container.

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Hi, all!
As I know, InterSystems recommends the use of Huge Pages. And if count of Huge Pages is enough, we'll see (in cconsole.log) something like this during Cache startup:

12/29/17-14:40:50:360 (3625) 0 Allocated 4630MB shared memory using Huge Pages: 4096MB global buffers, 256MB routine buffers

But if count of Huge Pages is not enough for location of all Globals and Routines caches, Cache won't use Huge Pages.

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Article
· 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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Running TuneTable accounts among other the parameter named Block Count. In documentation, we see that this is an approximate numbers of 2K-blocks in which SQL-maps are stored. Databases in recent Cache doesn't support 2K-physical blocks so SQL-blocks are not physical blocks as it seems. So two questions:

- what are these blocks?

- how knowledge about count of blocks can help in SQL optimization?

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Question
· Oct 30, 2016
ISCAgent debug

Good day!
Is there an opportunity to debug the ISCAgent behaviour (in Linux)? ISCAgent uses /etc/iscagent/iscagent.conf as configuration file, but in docs I've found a description only for two parameters (port number and interface - http://docs.intersystems.com/latest/csp/docbook/DocBook.UI.Page.cls?KEY=...). Other parameters I can see by running /usr/local/etc/cachesys/ISCAgentCtrl status:

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