Kubernetes (commonly stylized as k8s) is an open-source container-orchestration system for automating application deployment, scaling, and management. It aims to provide a platform for automating deployment, scaling, and operations of application containers across clusters of hosts. It works with a range of container tools, including Docker.
Are you ready yet? Have you packed all you'll need for the summit? And don't forget the needed power-socket adapters if you come from outside the US!
Have you signed up for the Container Bootcamp on Sunday? Or one of the various Experience Labs, the many informative sessions and one of the symposia on Wednesday afternoon?
Again, there is a mobile app for attendees that should help you keep it all under control and even allow you to book time with InterSystems personnel for a one-on-one deep-dive on whatever you need.
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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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.
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.
Are we correct to assume that the IKO topology only allows for the use of one 'data' node type, and one 'compute' node type? So if we want to use several different iris based compute nodes (or data nodes) we have to apply several yaml files? So the following topology config is not possible:
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).
K9s is a terminal-based UI (aka kubectl clown suit), to manage Kubernetes clusters that drastically simplifies navigating, observing, and managing your applications in K8s, including Custom Resources like the InterSystems Kubernetes Operator (IKO) and ArgoCD Applications. If you are about to take your CKD, CKA, or CKS, leave k9s well enough alone for awhile as the abstraction to kubectl will become the standard for navigating the cluster and you will undoubtedly become estranged to the extended flags of kubectl and bomb the exam.
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.
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This week I was able to demo a proof of concept for our FMS interface on traffic cop architecture to my team. We are working on modernizing an Interoperability production running on mirrored Health Connect instances. We deploy IRIS workloads on Red Hat OpenShift Container Platform using InterSystems Kubernetes Operator (IKO). We can define any number of replicas for the compute stateful set where each compute pod runs our Interoperability production. We introduced Horizontal Pod Autoscaler (HPA) to scale up the number of compute pods based on memory or CPU utilization.
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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.
InterSystems Kubernetes Operator (IKO) 3.5 is now Generally Available. IKO 3.5 adds significant new functionality along with numerous bug fixes. Highlights include:
Below we define the environment we will be creating via a Custom Resource Definition (CRD). It lets us define something outside the realm of what the Kubernetes standard knows (this is objects such as your pods, services, persistent volumes (and claims), configmaps, secrets, and lots more). We are building a new kind of object, an IrisCluster object.
Want a commercial grade FHIR® Implementation included in your micro service ecosystem and barely have enough time to fill out your Health plan elections?
If you are a customer of the new InterSystems IRIS® Cloud SQL and InterSystems IRIS® Cloud IntegratedML® cloud offerings and want access to the metrics of your deployments and send them to your own Observability platform, here is a quick and dirty way to get it done by sending the metrics to Google Cloud Platform Monitoring (formerly StackDriver).
The IKO allows for sidecars. The idea behind them is to have direct access to a specific instance of IRIS. If we have mirrored data nodes, the web gateway will (correctly) only give us access to the primary node. But perhaps we need access to a specific instance. The sidecar is the solution.
Building on the example from the previous article, we introduce the sidecar by using a mirrored data node and of course arbiter.
If you're interested in containers, take a look at what we got planned for Global Summit, September 22-25, Boston Marriott Copley Place. Register now to take advantage of our early bird pricing.
Hi All! For those of you who attended experience labs at the 2021 Virtual Summit, you may recall that one of the lab sessions was around Kubernetes. We've now converted that lab to be fully on-demand. You can launch a small cluster of VMs and follow the exercise to manage your Kubernetes cluster, deploy InterSystems IRIS containers to it, and watch its self-healing nature when destroying a pod.
Watch as the presenter uses IKO to deploy the WebGateway, SAM, and InterSystems API Manager with the latest version of the InterSystems Kubernetes Operator:
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In case you're planning on deploying IRIS For Health, or any of our containerized products, via the IKO on OpenShift, I wanted to share some of the hurdles we had to overcome.
As with any IKO based installation, we first need to deploy the IKO itself. However we were getting this error:
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Did you catch an Experience Lab at the 2021 Virtual Summit? Head over to the InterSystems Learning siteto access all four of these hands-on exercises, and get up to speed on:
InterSystems Kubernetes Operator (IKO) 3.6 is now Generally Available. IKO 3.6 adds significant new functionality along with numerous bug fixes. Highlights include:
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