I've been working on deploying an IRIS for Health environment in EKS. There is a video session in the InterSystems learning portal about this feature but I have not succeeded in finding the proper documentation and resources to use this in my Kubernetes cluster.
Has this been deprecated/discontinued? Any idea where can I find the resources? Should I stick to StatefulSets instead of using the IrisCluster resource type provided by this operator?
I'm almost running out of disk space so I want to move 1 DB to a different hard drive. It's a rather simple but lengthy action during a shutdown of IRIS. But is this somehow possible under runtime in a stand-alone installation? I'm looking for kind of a "local drive failover"
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.
After running an extensive block of daily statistics my IRISTEMP has expanded dramatically. But FreeSpace shows 97% unused and FREE space. How can I shrink IRISTEMP in runtime without shutdown and manual intervention (which was the traditional approach)
1. A deployment may consist of two high availability instances and two disaster recovery instances in a different data center.
The corresponding UAT environment could replicate this giving a total of 8 instances. How do you confirm CPF and Scheduled task alignment across ALL instances.
In our team, there are several developers working in parallel on different projects. To ensure this distributed collaboration and high-quality code reviews, we rely on version control with Git. Our challenge is to harmonize the unique characteristics of InterSystems products and the possibilities of Git and Docker.
Very recently Docker showed a very new feature added to their Docker Desktop tool. It was a good way to start using Docker on macOS and Windows, and they also released the same tool for Linux as well. And new feature Extensions add an ability to extend this GUI application with some extra abilities from extensions.
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.
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.
In this article, we will learn how to set up a REST API for the IRIS Security Package. We will be able to create users, roles, add applications, etc... by simple HTTP requests as well as generate a client application in ObjectScript.
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 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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I am looking to migrate a few legacy debt collection applications built using InterSystems Cache to AWS. Does anyone here have any experience, ideas and best practices on migrating Cache products to the public cloud?
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.
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:
And I did not find a restriction on the use of Ensemble 2018 installed on Docker with Openshift, but I received information that Intersystems would not support this installation case. That is true?
I'm looking for a way to have an IRIS db distributed over several (hw) drives. Without touching the internal data structures (e.g. mapping) ! Are there any options in file systems to achieve this "splitting" or "appending" ?
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A lot of developers like to work with Studio and have been looking into source code version control such as GIT or into enabling modern development workflows like CICD or DevOps processes.
This article describe an elementary solution to get you started in CICD and DevOps, even if you are not yet ready to move to Atelier or forth coming VS Code approach which enable client side source code version control.
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).
Most transactional applications have a 70:30 RW profile. However, some special cases have extremely high write IO profiles.
I ran storage IO tests in the ap-southeast-2 (Sydney) AWS region to simulate IRIS database IO patterns and throughput similar to a very high write rate application.
The test aimed to determine whether the EC2 instance types and EBS volume types available in the AWS Australian regions will support the high IO rates and throughput required.
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