vRealize Automation Header

Using vRealize Automation Cloud Template to execute a Code Stream Pipeline

VMware, , , ,

Looking at the latest vRA Cloud Template Schema, I saw something interesting in the definitions.

The ability to have a resource type of “codestream.execution”. This allows you to execute a Code Stream pipeline from within a cloud template. Once deployed, a Deployment will feature a resource object, of which you can also link a custom day 2 action to!

vRA Cloud Assembly - Deployment with codestream.execution resource object

This opens a lot of future possibilities of creative ways to extend your automation.

The schema looks like the below. And you can continue to follow this blog for an example. Continue reading Using vRealize Automation Cloud Template to execute a Code Stream Pipeline →

vSphere Kubernetes Drivers Operator - Red Hat OpenShift - Header

Using the new vSphere Kubernetes Driver Operator with Red Hat OpenShift via Operator Hub

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What is the vSphere Kubernetes Driver Operator (VDO)?

This Kubernetes Operator has been designed and created as part of the VMware and IBM Joint Innovation Labs program. We also talked about this at VMworld 2021 in a joint session with IBM and Red Hat. With the aim of simplifying the deployment and lifecycle of VMware Storage and Networking Kubernetes driver plugins on any Kubernetes platform, including Red Hat OpenShift.

This vSphere Kubernetes Driver Operator (VDO) exposes custom resources to configure the CSI and CNS drivers, and using Go Lang based CLI tool, introduces validation and error checking as well. Making it simple for the Kubernetes Operator to deploy and configure.

The Kubernetes Operator currently covers the following existing CPI, CSI and CNI drivers, which are separately maintained projects found on GitHub.

This operator will remain CNI agnostic, therefore CNI management will not be included, and for example Antrea already has an operator.

Below is the high level architecture, you can read a more detailed deep dive here.

vSphere Kubernetes Drivers Operator - Architecture Topology

Installation Methods

You have two main installation methods, which will also affect the pre-requisites below.

If using Red Hat OpenShift, you can install the Operator via Operator Hub as this is a certified Red Hat Operator. You can also configure the CPI and CSI driver installations via the UI as well.

  • Supported for OpenShift 4.9 currently.

Alternatively, you can install the manual way and use the vdoctl cli tool, this method would also be your route if using a Vanilla Kubernetes installation.

This blog post will cover the UI method using Operator Hub.

Pre-requisites

Continue reading Using the new vSphere Kubernetes Driver Operator with Red Hat OpenShift via Operator Hub →

AWS EKS Header

Deleting AWS EKS Cluster Fails? Learn How to Fix “Cannot Evict Pod as it Violates Disruption Budget” Error

Kubernetes, , , , , , , , , , ,
The Issue

I had to remove a demo EKS Cluster where I had screwed up an install of a Service Mesh. Unfortunately, it was left in a rather terrible state to clean up, hence the need to just delete it.

When I tried the usual eksctl delete command, including with the force argument, I was hitting errors such as:

2021-12-21 23:52:22 [!] pod eviction error ("error evicting pod: istio-system/istiod-76f699dc48-tgc6m: Cannot evict pod as it would violate the pod's disruption budget.") on node ip-192-168-27-182.us-east-2.compute.internal

With a final error output of:

Error: Unauthorized

eksctl delete cluster - Cannot evict pod as it would violate the pod's disruption budget - Error Unauthorized

The Cause

Well, the error message does call out the cause, moving the existing pods to other nodes is failing due to the configured settings. Essentially EKS will try and drain all the nodes and shut everything down nicely when it deletes the cluster. It doesn’t just shut everything down and wipe it. This is because inside of Kubernetes there are several finalizers that will call out actions to interact with AWS components (thanks to the integrations) and nicely clean things up (in theory).

To get around this, I first tried the following command, thinking if delete the nodegroup without waiting for a drain, this would bypass the issue:

 eksctl delete nodegroup standard --cluster veducate-eks --drain=false --disable-eviction

This didn’t allow me to delete the cluster however, I still got the same error messages.

The Fix

So back to the error message, and then I realised it was staring me in the face!

Cannot evict pod as it would violate the pod's disruption budget

What is a Pod Disruption Budget? It’s essentially a way to ensure availability of your pods from someone killing them accidentality.

A PDB limits the number of Pods of a replicated application that are down simultaneously from voluntary disruptions. For example, a quorum-based application would like to ensure that the number of replicas running is never brought below the number needed for a quorum. A web front end might want to ensure that the number of replicas serving load never falls below a certain percentage of the total.

To find all configured Pod Disruption Budgets:

kubectl get poddisruptionbudget -A

Then delete as necessary:

kubectl delete poddisruptionbudget {name} -n {namespace}

eks - kubectl get poddisruptionbudgets -A - kubectl delete poddisruptionbudgets

Finally, you should be able to delete your cluster.

eksctl delete cluster - successful

 

Regards

Dean Lewis

Helm Pac-Man Header

Creating and hosting a Helm Chart package to install Pac-Man on Kubernetes

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If you’ve have been following any of my blogs that relate to Kubernetes, I am sure that you will have seen the use of my demo application Pac-Man, designed to replicate a small production application with a front end UI service, DB back end service and load balancing service.

If not, you can find it here:

In this blog post, I am going to cover how I create a Helm Chart package to install the application on a Kubernetes cluster, and then host it on GitHub so that it can be re-used as necessary between different clusters.

This was on my to-do list for quite a while, as I wanted to explore Helm in more detail and understand how the charts work. What better way to do this than create my own?

What is Helm and why use it?

Helm is a tool that simplifies the installation and lifecycle of Kubernetes applications. As an example, it is a little bit like Brew or Yum for Linux.

Helm uses a package format called charts; these charts are a collection of files that describe a related set of Kubernetes resources. These charts can range from the simple, deploy a single pod, deployment set, etc, to the complex, deploy a full application made up of Deployments, StatefulSets, PVCs, Ingress, etc.

Helm has become over the years one of the defacto client tools to use for simplification of deploying an application to your Kubernetes environment. Take Kasten for example, to deploy their K10 software, their guide gives you only the Helm commands to do so.

You can install Helm from the below script, for other methods please see their official documentation.

curl -fsSL -o get_helm.sh https://raw.githubusercontent.com/helm/helm/main/scripts/get-helm-3

chmod 700 get_helm.sh

./get_helm.sh
Creating a template Helm Chart

The Helm Client makes it easy to get started from scratch, you can create a template chart by running the following command, which creates a folder of the name you specify, with a number of example files you can use.

helm create {name}

# For this blog post I ran the following

helm create pacman-kubernetes

helm create pacman-kubernetes

In more detail, this structure offers the following: Continue reading Creating and hosting a Helm Chart package to install Pac-Man on Kubernetes →

Tanzu Nvidia Header

Deploying Nvidia GPU enabled Tanzu Kubernetes Clusters

VMware, Kubernetes, , , ,

In this blog post I’m going to detail how deploy and configure a Nvidia GPU enabled Tanzu Kubernetes Grid cluster in AWS. The method will be similar for Azure, for vSphere there are a number of additional steps to prepare the system. I’m going to essentially follow the official documentation, then run some of the Nvidia tests. Like always, it’s good to get a visual reference and such for these kinds of deployments.

Pre-Reqs
  • Nvidia today only support Ubuntu deployed images in relation to a TKG deployment
  • For this blog I’ve already deployed my TKG Management cluster in AWS
Deploy a GPU enabled workload cluster

It’s simple, just deploy a workload cluster that for the compute plane nodes (workers) that uses a GPU enabled instance.

You can create a new cluster YAML file from scratch, or clone one of your existing located in:

~/.config/tanzu/tkg/clusterconfigs

Below are the four main values you will need to change. As mentioned above, you need a GPU enabled instance, and for the OS to be Ubuntu. The OS version will default if not set to 20.04.

CONTROL_PLANE_MACHINE_TYPE: t3.large
NODE_MACHINE_TYPE: g4dn.xlarge
OS_ARCH: amd64
OS_NAME: ubuntu
OS_VERSION: "20.04

The rest of the file you configure as you would for any workload cluster deployment. Continue reading Deploying Nvidia GPU enabled Tanzu Kubernetes Clusters →