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#Kubernetes

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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.

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So if you are following from the previous post or dropping in now, let's segway to the world of eBPF applications and take a look at Parca, which builds on our brief investigation of performance bottlenecks using eBPF, but puts a killer app on top of your cluster to monitor all your iris workloads, continually, cluster wide!

Continous Profiling with Parca, IRIS Workloads Cluster Wide

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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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· Nov 28, 2023 2m read
k9s - Manage Your IrisClusters In Style

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.

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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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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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In our previous article, we have explored the most common Kubernetes components:

  • We started with the pods and the services we needed to communicate with each other.
  • Then, we examined the Ingress component used to Route traffic into the cluster.
  • We also skimmed through an external configuration using ConfigMaps and Secrets.
  • Afterward, we analyzed Data persistence with the help of Volumes.
  • Finally, we took a quick look at pod blueprints with such replicating mechanisms as Deployments and StatefulSets (the latter is employed specifically for such stateful applications as databases).

In this article, we will explore Kubernetes architecture and configuration.

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