#InterSystems Kubernetes Operator (IKO)

Mirror Your Database Across the Galaxy with Seeding

IKO Helm Status: WFH

Here is an option for your headspace if you are designing an multi-cluster architecture and the Operator is an FTE to the design.  You can run the Operator from a central Kubernetes cluster (A), and point it to another Kubernetes cluster (B), so that when the apply an IrisCluster to B the Operator works remotely on A and plans the cluster accordingly on B.  This design keeps some resource heat off the actual workload cluster, spares us some serviceaccounts/rbac and gives us only one operator deployment to worry about so we can concentrate on the IRIS workloads.

Kamino for IrisClusters

If you are in the business of building a robust High Availability, Disaster Recovery or Stamping multiple environments rapidly and in a consistent manner Karmada may just be the engine powering your Cloning Facility.

"Haul" a Portable Registry for Airgapped IrisClusters

Rancher Government Hauler streamlines deploying and maintaining InterSystems container workloads in air-gapped environments by simplifying how you package and move required assets. It treats container images, Helm charts, and other files as content and collections, letting you fetch, store, and distribute them declaratively or via CLI — without changing your existing workflows.   Meaning your charts and what have yous, can have conditionals on your pull locations in Helm values, etc. 

Target Practice for IrisClusters with KWOK

KWOK, Kubernetes WithOut Kubelet, is a lightweight tool that simulates nodes and pods—without running real workloads—so you can quickly test and scale IrisCluster behavior, scheduling, and zone assignment.  For those of you wondering what value is in this without the IRIS workload, you will quickly realize it when you play with your Desk Toys awaiting nodes and pods to come up or get the bill for provisioning expensive disk behind the pvc's for no other reason than just to validate your topology.

Background

For a variety of reasons, users may wish to mount a persistent volume on two or more pods spanning multiple availability zones. One such use case is to make data stored outside of IRIS available to both mirror members in case of failover.

Unfortunately the built-in storage classes in most Kubernetes implementations (whether cloud or on-prem) do not provide this capability:

• Does not support access mode "ReadWriteMany"
• Does not support being mounted on more than one pod at a time
• Does not support access across availability zones

A step by step implementation path to a cross regional stretched IrisCluster with Mirroring using the Intersystems Kubernetes Operator (IKO), Google Cloud Platform, and Tailscale.

I am giving this distraction the code name "Compliment Sandwich" for a reason yet to be realized, but I'd rather the community go right for the jugular shooting holes in a solution that implements wireguard based connectivity for our workloads in general, as I would like to refine it as a fall project leading up to KubeCon in Atlanta and if I miss the mark, Ill get it done before Amsterdam. 

Another step in this implementation path, adding cross cloud, cross regional stretched IrisCluster with Mirroring + Disaster Recovery using the Intersystems Kubernetes Operator (IKO) and Tailscale

Though trivial, Id like to go multi-cloud with the stretched IrisCluster for a couple of reasons to socialize the power of Wireguard when it supplies the network for a properly zoned IrisCluster by adding another mirror role to Amazon Web Services in the Western United States based datacenter in Oregon.

Background

For a variety of reasons, users may wish to mount a persistent volume on two or more pods spanning multiple availability zones. One such use case is to make data stored outside of IRIS available to both mirror members in case of failover.

Unfortunately the built-in storage classes in most Kubernetes implementations (whether cloud or on-prem) do not provide this capability:

• Does not support access mode "ReadWriteMany"
• Does not support being mounted on more than one pod at a time
• Does not support access across availability zones

Background

For a variety of reasons, users may wish to mount a persistent volume on two or more pods spanning multiple availability zones. One such use case is to make data stored outside of IRIS available to both mirror members in case of failover.

Unfortunately the built-in storage classes in most Kubernetes implementations (whether cloud or on-prem) do not provide this capability:

• Does not support access mode "ReadWriteMany"
• Does not support being mounted on more than one pod at a time
• Does not support access across availability zones

#InterSystems Demo Games entry

⏯️ Auto-scaling made easy in GKE with InterSystems Kubernetes Operator (IKO)

Kubernetes horizontal pod auto-scaling (HPA) is the key to handle the unpredictable compute workload in healthcare systems. IKO helps orchestrating the IRIS container deployment in Kubernetes including the capability to configure HPA. This demo uses XSLT processing as an example to showcase this type of elasticity.

🗣 Presenter: @Simon Sha, Sales Architect, InterSystems

InterSystems Kubernetes Operator (IKO) 3.8 is now Generally Available.  IKO 3.8 adds new functionality along with numerous bug fixes and security updates.  Highlights include:

• Compute Groups allows you to deploy more than one type of compute node to handle different types of workloads in a single IrisCluster
• Consolidate Volumes – you can now choose to deploy with fewer volumes, such as consolidating data and WIJ on the same volume.

The IKO will dynamically provision storage in the form of persistent volumes and pods will claim them via persistent volume claims.

But storage can come in different shapes and sizes. The blueprint to the details about the persistent volumes comes in the form of the storage class.

This raises the question: we've deployed the IrisCluster, and haven't specified a storage class yet. So what's going on?

You'll notice that with a simple

kubectl get storageclass

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.

We now get to make use of the IKO.

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.

The IKO documentation is robust. A single web page, that consists of about 50 actual pages of documentation. For beginners that can be a bit overwhelming. As the saying goes: how do you eat an elephant? One bite at a time. Let's start with the first bite: helm.

What is Helm?

Helm is to Kubernetes what the InterSystems Package Manager (IPM, formerly ObjectScript Package Manager - ZPM) is to IRIS.

This article will cover turning over control of provisioning the InterSystems Kubernetes Operator, and starting your journey managing your own "Cloud" of InterSystems Solutions through Git Ops practices. This deployment pattern is also the fulfillment path for the PID^TOO||| FHIR Breathing Identity Resolution Engine.

Git Ops

LS,

I'm trying to learn how to use the IKO for deploying solutions to Kubernetes. In my current project I'm trying to deploy the IAM onto a K8S context. Are there directly usable samples of the yaml file I need to use for that?  

InterSystems Kubernetes Operator (IKO) 3.5 is now Generally Available.  IKO 3.5 adds significant new functionality along with numerous bug fixes.  Highlights include:

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. But IKO scaled down

My team works on implementing an Interoperability solution utilizing InterSystems Kubernetes Operator on Red Hat OpenShift container platform. 

We are trying to determine how many messages we can process in any given time. We have a Feeder app running in 10 containers sending 50k messages each to a load balancer all beginning at the same time.

Messages are received via HTTPS protocol by webgateway containers. 

Interoperability production runs in compute pods with persistent data, journals, and WIJ volumes.

We implemented Horizontal Pod Autoscaler to scale compute pods when CPU utilization is high.

Hello,

I work on deploying IRIS using Kubernetes operator and Red Hat OpenShift. I encouraged another team working on Java application to consider using IRIS as database. My team deployed IRIS cluster using two mirrored data pods for the other team. The other team asked me for the connection information.

To learn how to use Java with IRIS, I attempted to deploy two apps from Open Exchange:

https://openexchange.intersystems.com/package/CRUD-GLOBALS-IRISNATIVEAP…

Here I got errors like this:

package com.intersystems.jdbc does not  exist

The InterSystems Kubernetes Operation (IKO) version 3.3 is now available via the WRC download page and the InterSystems Container Registry.

IKO simplifies working with InterSystems IRIS or InterSystems IRIS for Health in Kubernetes by providing an easy-to-use irisCluster resource definition. See the documentation for a full list of features, including easy sharding, mirroring, and configuration of ECP.

IKO 3.3 Highlights:

Hey Developers,

Watch as the presenter uses IKO to deploy the WebGateway, SAM, and InterSystems API Manager with the latest version of the InterSystems Kubernetes Operator: 

⏯ IKO: The InterSystems Kubernetes Operator (Version 3.0)

IntroductionSeveral 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

Hey Developers,

New video is already on InterSystems Developers YouTube:

⏯ Deploying & Upgrading IRIS with Kubernetes Operator

Hi Developers,

The new video from Global summit 2019 is already on InterSystems Developers YouTube:

⏯ Intersystems IRIS Kubernetes Operator

Episode 20 of Data Points features a conversation with Bob Kuszewski about the Kubernetes and the InterSystems Kubernetes Operator (IKO). Take a listen to hear about some of the use cases and features of IKO, plus how it compares to InterSystems Cloud Manager (ICM) within the cloud space.

If you're looking for an introduction to Kubernetes as a technology, and a little teaser about the InterSystems Kubernetes Operator, check out the recently released Kubernetes Overview video. This video will introduce you to the functionality and use cases of Kubernetes, and explain a bit about how the InterSystems Kubernetes Operator makes it beneficial to use Kubernetes with InterSystems IRIS.

In the context of IKO (Iris Kubernetes Operator) the question of Service not redirecting dynamically to the correct Pod is still pending.
In production this can be dangerous since an overload (or any other simpler problem) can cause you to change the main Pod and leave the application inoperable until we intervene.

Intersystems support warned that this is still an issue of IKO, but there are some possibilities that I am studying.

To explore an idea I had, I would like the help of this Forum to answer the following question: