Category Archives: Kubernetes

Helm Pac-Man Header

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

Kubernetes, , , , ,

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 →

vROPs - Kubernetes - Prometheus - Telegraf - Header

vRealize Operations – Monitoring Kubernetes with Prometheus and Telegraf

VMware, Kubernetes, , , , , ,

In this post, I will cover how to deploy Prometheus and the Telegraf exporter and configure so that the data can be collected by vRealize Operations.

Overview

Delivers intelligent operations management with application-to-storage visibility across physical, virtual, and cloud infrastructures. Using policy-based automation, operations teams automate key processes and improve the IT efficiency.

Is an open-source systems monitoring and alerting toolkit. Prometheus collects and stores its metrics as time series data, i.e. metrics information is stored with the timestamp at which it was recorded, alongside optional key-value pairs called labels.

There are several libraries and servers which help in exporting existing metrics from third-party systems as Prometheus metrics. This is useful for cases where it is not feasible to instrument a given system with Prometheus metrics directly (for example, HAProxy or Linux system stats).

Telegraf is a plugin-driven server agent written by the folks over at InfluxData for collecting & reporting metrics. By using the Telegraf exporter, the following Kubernetes metrics are supported:

Why do it this way with three products?

You can actually achieve this with two products (vROPs and cAdvisor for example). Using vRealize Operations and a metric exporter that the data can be grabbed from in the Kubernetes cluster. By default, Kubernetes offers little in the way of metrics data until you install an appropriate package to do so.

Many customers have now decided upon using Prometheus for their metrics needs in their Modern Applications world due to the flexibility it offers.

Therefore, this integration provides a way for vRealize Operations to collect the data through an existing Prometheus deploy and enrich the data further by providing a context-aware relationship view between your virtualisation platform and the Kubernetes platform which runs on top of it.

vRealize Operations Management Pack for Kubernetes supports a number of Prometheus exporters in which to provide the relevant data. In this blog post we will focus on Telegraf.

You can view sample deployments here for all the supported types. This blog will show you an end-to-end setup and deployment.

Prerequisites
  • Administrative access to a vRealize Operations environment
  • Access to a Kubernetes cluster that you want to monitor
  • Install Helm if you have not already got it setup on the machine which has access to your Kubernetes cluster
  • Clone this GitHub repo to your machine to make life easier
git clone https://github.com/saintdle/vrops-prometheus-telegraf.git
vrops - git clone saintdle vrops-prometheus-telegraf.git
Information Gathering

Note down the following information:

  • Cluster API Server information
kubectl cluster-info

vROPs - kubectl cluster-info

  • Access details for the Kubernetes cluster
    • Basic Authentication – Uses HTTP basic authentication to authenticate API requests through authentication plugins.
    • Client Certification Authentication – Uses client certificates to authenticate API requests through authentication plugins.
    • Token Authentication – Uses bearer tokens to authenticate API requests through authentication plugin

In this example I will be using “Client Certification Authentication” using my current authenticated user by running:

kubectl config view --minify --raw

vROPs - kubectl config view --minify --raw

  • Get your node names and IP addresses
kubectl get nodes -o wide

vROPs - kubectl get nodes -o wide

Install the Telegraf Kubernetes Plugin

Continue reading vRealize Operations – Monitoring Kubernetes with Prometheus and Telegraf →

vSphere and CSI Header

Upgrading the vSphere CSI Driver (Storage Container Plugin) from v2.1.0 to latest

VMware, Kubernetes, , ,

In this post I’m just documenting the steps on how to upgrade the vSphere CSI Driver, especially if you must make a jump in versioning to the latest version.

Upgrade from pre-v2.3.0 CSI Driver version to v2.3.0

You need to figure out what version of the vSphere CSI Driver you are running.

For me it was easy as I could look up the Tanzu Kubernetes Grid release notes. Please refer to your deployment manifests in your cluster. If you are still unsure, contact VMware Support for assistance.

Then you need to find your manifests for your associated version. You can do this by viewing the releases by tag. 

Then remove the resources created by the associated manifests. Below are the commands to remove the version 2.1.0 installation of the CSI.

kubectl delete -f https://raw.githubusercontent.com/kubernetes-sigs/vsphere-csi-driver/v2.1.0/manifests/latest/vsphere-7.0u1/vanilla/deploy/vsphere-csi-controller-deployment.yaml

kubectl delete -f https://raw.githubusercontent.com/kubernetes-sigs/vsphere-csi-driver/v2.1.0/manifests/latest/vsphere-7.0u1/vanilla/deploy/vsphere-csi-node-ds.yaml

kubectl delete -f https://raw.githubusercontent.com/kubernetes-sigs/vsphere-csi-driver/v2.1.0/manifests/latest/vsphere-7.0u1/vanilla/rbac/vsphere-csi-controller-rbac.yaml

vsphere-csi - delete manifests

Now we need to create the new namespace, “vmware-system-csi”, where all new and future vSphere CSI Driver components will run. Continue reading Upgrading the vSphere CSI Driver (Storage Container Plugin) from v2.1.0 to latest →

Tanzu Blog Logo Header

First Look – Setup Tanzu Build Services and rebuilding Pac-Man

Kubernetes, VMware, , ,

This blog post will detail how to setup Tanzu Build Services in a test environment, and then create a container image from a dockerfile, fixing several vulnerabilities compared to the current container image.

What is Tanzu Build Service?
Tanzu Build Service uses the open-source Cloud Native Buildpacks project to turn application source code into container images. 

Build Service executes reproducible builds that align with modern container standards, and additionally keeps image resources up-to-date. It does so by leveraging Kubernetes infrastructure with kpack, a Cloud Native Buildpacks Platform, to orchestrate the image lifecycle. 

Build Service helps you develop and automate containerized software workflows securely and at scale.

You can read more about the Tanzu Build Services concepts here.

Pre-Reqs

Have an accessible Image Registry to both your local client and your Kubernetes cluster.

  • I used Dockerhub for my lab environment.

Install the Carvel tools.

  • kapp is a deployment tool that allows users to manage Kubernetes resources in bulk.
  • ytt is a templating tool that understands YAML structure.
  • kbld is needed to map relocated images to k8s config.
  • imgpkg is tool that relocates container images and pulls the release configuration files.
brew tap vmware-tanzu/carvel

brew install ytt kbld kapp imgpkg kwt vendir

Install the kp cli tool.

# Download from the Tanzu Network pages

chmod +x kp-linux-0.4.0 
sudo mv kp-linux-0.4.0 /usr/bin/local/kp

# Install using Brew

brew tap vmware-tanzu/kpack-cli
brew install kp

# Download from GitHub Releases Page
curl -LJO https://github.com/vmware-tanzu/kpack-cli/releases/download/v0.4.2/kp-linux-0.4.2
chmod +x kp-linux-0.4.2
sudo mv kp-linux-0.4.2 /usr/bin/local/kp
Installing Tanzu Build Services

Log in to your registry that will host the Build Services containers and be used by your Kubernetes cluster Continue reading First Look – Setup Tanzu Build Services and rebuilding Pac-Man →