Category Archives: VMware

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Tanzu Service Mesh – First look at deploy, configure and managing an app between clusters

I’ve finally found the time to dive into Tanzu Service Mesh (TSM), a product which has intrigued me greatly. In this blog post I cover setting up TSM, and configuring application connectivity between two clusters running in different public clouds.

What is a Service Mesh?

In software architecture, a service mesh is a dedicated infrastructure layer for facilitating service-to-service communications between services or micro-services, using a proxy. This then provides additional capability such as transit layer between platforms, observability, traffic management and more.

A service mesh provides the capability to secure and simplify your application communications between platforms/clusters/clouds without the need for introduction of lots of other software such as API Gateways.

A service mesh introduces a proxy component which sits side by side with any deployed service. And any inbound and outbound communication flows through the proxy to/from the service. This allows the proxy to provide all the functions needed to offer the capabilities discussed above and in the rest of this blog post.

What is Tanzu Service Mesh (TSM)?

TSM builds upon the principals mentioned above, offering consumers a full enterprise-class service mesh, designed to solve challenges across distributed micro-service applications by extending service mesh services outside Kubernetes clusters and providing a unified operational layer across platforms and technologies.

  • Extends the service mesh capability (discovery, connectivity, control, security, and observability) to users and data, and across clusters and clouds.

  • Facilitates the development and management of distributed applications across multiple clusters, multiple clouds, and in hybrid-cloud environments with Global Namespaces (discussed below), supporting federation across organizational boundaries, technologies, and service meshes.

  • Implements consistent application-layer traffic management and security policies across all your clusters and clouds.

Global Namespace – is a key concept introduced by TSM, that extends service mesh capabilities for resources in a distributed application by arranging these objects in a logical group. A global namespace is therefore not tied to a single cluster or cloud, connecting resources between two or more clusters/clouds. Each global namespace manages service discovery, observability, encryption, policies, and service-level objectives (SLOs) for its objects regardless of where they reside: in multiple clusters, sites, or clouds.

To learn more about the concepts introduced by TSM, please read the below document:

Tanzu Service Mesh - Logical Overview

Encryption for Data in Flight

TSM provides the value of a transit between clusters and clouds. In doing so comes many challenges, one such is achieving end-to-end encryption for in-flight traffic. This can be mandatory to comply with regulatory and security governance measures.

Tanzu Service Mesh includes a top-level certificate authority (CA) to provide a trusted identity to each node on the network. In the case of microservices architecture, those nodes are the pods that run the services. Tanzu Service Mesh can set up end-to-end mutual transport layer security (mTLS) encryption using a CA function.

Activating Tanzu Service Mesh

TSM is a SaaS service only from VMware, meaning no on-premises deployment for the control plane aspect. To activate, you will click the link provided when you request a trial or purchase the product,and linking it to your VMware Cloud Services Organisation (or create a new org if necessary.)

You must belong to an organization before you can access Tanzu Service Mesh. 

If you are an organization owner, you have access to all the resources of the organization. You can add cloud services to your organization and then invite users. 

After you add Tanzu Service Mesh to your organization, you can add users to the organization to give them access to Tanzu Service Mesh. 

For more information about organizations and adding users to an organization, see the VMware Cloud Services documentation.

Once you’ve activated the product, you will see it in your Cloud Services Portal as below.

VMware Cloud Services - Tanzu Service Mesh

Pre-requisites for Installation

This is something which caused me issues in the past, where I tried to deploy TSM to a cluster that did not have enough resources to begin with.

- Cluster with 6 nodes (though the documentation does say minimum of 3 lower down in the text)
> I've queried this

- Requires that every node in the cluster have at least 250 milliCPU and 650 MB of memory available

- Pod Limits - Requires a quota of at least 3 pods for each node on the cluster and additionally at least 30 pods for the whole cluster.

Basically, you need to make sure you have enough minimum nodes and resources.

Regarding supported Kubernetes distributions, the team validate against a number of Enterprise Kubernetes solutions as well as the upstream Kubernetes.

I deployed two new environments for my testing, an EKS and AKS cluster, with the following commands.

eksctl create cluster --name veducate-eks-tsm --region us-west-1 --nodegroup-name standard --node-type m5.xlarge --managed

az aks create -rg aks-tsm --name aks-tsm-cluster --node-count 4 --ssh-key $HOME/.ssh/id_rsa.pub -s standard_d4s_v5
Onboarding your Clusters into Tanzu Service Mesh

Onboarding involves registering the cluster with Tanzu Service Mesh and installing the necessary software on the cluster. Continue reading Tanzu Service Mesh – First look at deploy, configure and managing an app between clusters

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OpenShift on VMware – Integrating with vSphere Storage, Networking and Monitoring.

I was honoured to be a guest on the “Ask an OpenShift Admin” webinar recently. Where I had the chance to talk about OpenShift on VMware, always a hot topic, and how we co-innovate and work together on solutions.

You can watch the full session below. Keep reading to see the content I didn’t get to cover on a separate recording I’ve produced.

Ask an OpenShift Admin (Ep 54): OpenShift on VMware and the vSphere Kubernetes Drivers Operator

However, I had a number of topics and demo’s planned, that we never got time to visit. So here is the full content I had prepared.

Some of the areas in this webinar and my additional session we covered were:

  • Answering questions live from the views (anything on the table)
  • OpenShift together with VMware
  • Common issues and best practices for deploying OpenShift on VMware vSphere
  • Consuming your vSphere Storage in OpenShift
  • Integrating with the VMware Network stack
  • Infrastructure Up Monitoring
OpenShift on VMware – Integrating with vSphere Storage, Networking and Monitoring

Resources

Regards

Dean Lewis

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Using vRealize Automation Cloud Template to execute a Code Stream Pipeline

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

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

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

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Deploying Nvidia GPU enabled Tanzu Kubernetes Clusters

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