Kubernetes

Getting started with VMware Pivotal Container Service (PKS) Part 3: NSX-T

03/28/2018 by William Lam 6 Comments

In this article, we are now going to start configuring NSX-T so that it will be ready for us to install PKS and consume the networking and security services provided by NSX-T. The result is that PKS can deliver on demand provisioning of all NSX-T components: Container Network Interface (CNI), NSX-T Container Plugin (NCP) POD, NSX Node Agent POD, etc) automatically when a new Kubernetes (K8S) Cluster is requested, all done with a single CLI or API call. In addition, PKS also provides a unique capability through its integration with NSX-T to enable network micro-segmentation at the K8S namespace level which allows Cloud/Platform Operators to manage access between application and/or tenant users at at a much finer grain level than was possible before which is really powerful!

As mentioned in the previous blog post, I will not be walking through a step-by-step NSX-T installation and I will assume that you already have a basic NSX-T environment deployed which includes a few ESXi host prepped as Transport Nodes and at least 1 NSX-T Controller and 1 NSX-T Edge. If you would like a detailed step by step walk through, you can refer to the NSX-T documentation here or you can even leverage my Automated NSX-T Lab Deployment script to setup the base environment and modify based on the steps in this article. In fact, this is the same script I have used to deploy my own NSX-T environment for PKS with some minor modification which I will be sharing at a later date.

If you missed any of the previous articles, you can find the complete list here:

Getting started with VMware Pivotal Container Service (PKS) Part 2: PKS Client

03/26/2018 by William Lam 6 Comments

In this article, we will configure the various command-line tools that will be used to interact with the PKS Platform which will then be consumed by either the Operators (managing the PKS infrastructure) and/or the the Developers (consumers of the Kubernetes Clusters).

Below is a quick summary, description and the consumers of the CLIs that we will be installing:

CLI	Description	Consumer
pks	Used to create/delete and manage K8S Clusters	Operator
kubectl	Used to interact with K8S Cluster and deploy applications including scaling up/down	Developer
uaac	Used to manage user accounts and authorization for the PKS platform	Operator
bosh	Used to manage PKS deployments and provides information about the VMs using its Cloud Provider Interface (CPI) which is vSphere in this case	Operator
om	Used to Used to manager and interact with Ops Manager	Operator
nsx-cli.sh	Used to clean NSX-T objects after a K8S have been deleted (will be Automated by PKS in future release)	Operator

Both PKS and Kubectl CLIs are supported on either Windows, MacOS and Linux, you can refer to Part 1 for a link to the binary downloads. The remainder of the tools are primarily used by Operators and to make them accessible for multiple users, you can deploy a centralized management VM. In my lab, I am referring to this VM as the "PKS Client" which is where we will be installing all the CLIs. You can use a variety of supported Operating Systems, but I found Ubuntu to work the best, especially for some of the package dependencies. I did try to use our own PhotonOS, but I was having some trouble figuring out the required packages. If I figure it out, then I will update the article as that may be preferred over Ubuntu if you have never worked with it before.

If you missed any of the previous articles, you can find the complete list here:

Getting started with VMware Pivotal Container Service (PKS) Part 1: Overview

03/23/2018 by William Lam 15 Comments

This past week and half, I have been spending quite a bit of time familiarizing myself with the recently released VMware Pivotal Container Service solution, also referred to as VMware PKS for short (yes, that is a K not a C which is a nod to Google's container scheduler Kubernetes). VMware PKS is part of a project that I am currently working on and I figure I would share the process and steps I took to deploy VMware PKS in my own personal lab, in case other folks are interested in trying out this neat and powerful solution for deploying Cloud Native Apps using Kubernetes which was co-developed between VMware, Pivotal and Google.

If you would like to learn more about this first release of VMware PKS and the benefits it provides to both developers (consumers) and operators (admins/SRE) for Kubernetes infrastructure, check out this blog post here. Merlin Glynn, one of the Product Managers for PKS also did an awesome light board video overview of VMware PKS if you want the sparks notes version. If you simply want to give PKS a try without deploying anything, the CNA folks have also published a PKS HOL which can you find here. Another useful resource is the Getting Started with Kubernetes-as-a-Service post from Michael West who works in CNA team and built the PKS HOL.

This will be the first, in a series of articles outlining my VMware PKS deployment and configuration which hopefully can help benefit others as it took me several attempts while learning about the solution. Although the first few articles will include manual guidance, rest assure, there will be some cool automation towards the end but I figure that folks may want to go through this once by hand to get a good understanding on all the different components and how they interact with each other. Plus, some of the PKS-specific automation is still being worked on by the product team and hopefully I will be able to share some of that real soon.

If you missed any of the previous articles, you can find the complete list here:

Test driving VMware Photon Controller Part 3a: Deploying Kubernetes

04/21/2016 by William Lam 6 Comments

If you have been following the series thus far, we have covered installing Photon Controller in Part 1 and then we learned how to create our first virtual machine using Photon Controller in Part 2. Next up, we will demonstrate how easy it is to stand up the three different Cluster Orchestration solutions that are supported on top of Photon Controller, starting with Kubernetes. Once the Cluster Orchestration solution has been setup, you can then deploy your application like you normally would through the Cluster Orchestration and behind the scenes, Photon Controller will automatically provision the necessary infrastructure to run your given application without having to know anything about the underlying resources.

If you recall from our last article, there are several default VM Flavors that are included in the Photon Controller installation. The ones that are named cluster-* are VM Flavors used for deploying the Cluster Orchestration virtual machines that have been configured to support high scale and throughput (up to 4vCPU and 8GB of memory). If you are testing this in a lab environment where you might be constrained on memory resources for your ESXi host (16GB of memory), then you actually have a few options. The first option is to create a new VM Flavor with a smaller configuration (e.g. 1vCPU/2GB memory) and then override the default VM Flavor when deploying the Cluster Orchestration. The second option which I learned from talking to Kris Thieler was that you can actually re-define the default cluster-* VM Flavors to fit your environment needs which he has documented here. To simplify our deployment, we will actually use Option 1 on just creating a new VM Flavor that we will use to override the default VM Flavor. If you have more than 16GB of memory, then you can skip Step 2.

Deploying Kubernetes Cluster

Step 1 - Download the Kubernetes VMDK from here and the Kubectl binary from here.

Step 2 - Run the following command to create our new VM Flavor override which we will call cluster-tiny-vm that is configured with 1vCPU/1GB of memory:

./photon -n flavor create --name cluster-tiny-vm --kind "vm" --cost "vm 1 COUNT,vm.flavor.cluster-other-vm 1 COUNT,vm.cpu 1 COUNT,vm.memory 1 GB,vm.cost 1 COUNT"

Step 3 - We will now upload our Kubernetes image and make note of the ID generated after the upload by running the following command:

./photon -n image create photon-kubernetes-vm-disk1.vmdk -n photon-kubernetes-vm.vmdk -i EAGER

Step 4 - Next, we also need the ID of our Photon Controller Instance deployment as it will be required in the next step by running the following command:

./photon deployment list

Step 5 - We will now enable the Kubernetes Cluster Orchestration on our Photon Controller instance by running the following command and specifying the ID of your deployment as well as the ID of the Kubernetes image from the previous two steps:

./photon -n deployment enable-cluster-type 7fd9a13d-e69e-4165-9b34-d436f4c67ea1 -k KUBERNETES -i 4332af67-2ff0-49f7-ba44-dd4140908e32

Step 6 - We can also see what Cluster Orchestration solutions have been enabled for our Photon Controller by running the following command and specifying our deployment ID:

./photon deployment show 7fd9a13d-e69e-4165-9b34-d436f4c67ea1

As you can see from the screenshot above, there is a Cluster Configuration section which provides a list of Cluster Orchestration solutions that have been enabled as well as their respective image.

Step 7 - We are now ready to spin up our Kubernetes (K8) Cluster by simply running the following command and substituting the network information from your environment. We are also going to only deploying a single K8 Slave (if you have additional resources you can spin up more or you can always re-size the cluster after it has been deployed) and lastly, we will override the default VM Flavor used by specifying -v option and providing the name of our VM Flavor called cluster-tiny-vm. You can just hit enter when prompted for the two etcd IP Addresses, the assumption is that you have DHCP running and those will automatically obtain an address.

./photon cluster create -n k8-cluster -k KUBERNETES --dns 192.168.1.1 --gateway 192.168.1.1 --netmask 255.255.255.0 --master-ip 192.168.1.55 --container-network 10.2.0.0/16 --etcd1 192.168.1.56 -s 1 -v cluster-tiny-vm

Step 8 - The process can take a few minutes and you should see a message like the one shown above which prompts you to run the cluster show command to get more details about the state of the cluster.

./photon cluster show 9b159e92-9495-49a4-af58-53ad4764f616

Exploring Kubernetes

At this point, you have now successfully deployed a fully functional K8 Cluster using Photon Controller with just a single command. We can now take explore our K8 setup a bit by using the kubectl CLI that you had downloaded earlier. For more information on how to interact with K8 Cluster using kubectl command, be sure to check out the official K8 documentation here.

To view the nodes within the K8 Cluster, you can run the following command and specifying the IP Address of the master VM provided in the previous step:

./kubectl -s 192.168.1.55:8080 get nodes

Lets now do something useful with our K8 Cluster and deploy a simple Tomcat application. We first need to download the following two configuration files that will define our application:

We then need to edit the photon-Controller-Tomcat-rc.yml file and delete the last two lines as it contains an incorrect syntax:

labels:
name: "tomcat-server"

To deploy our application, we will run the following two commands which will setup our replication controller as well as the service for our Tomcat application:

./kubectl -s 192.168.1.55:8080 create -f photon-Controller-Tomcat-rc.yml
./kubectl -s 192.168.1.55:8080 create -f photon-Controller-Tomcat-service.yml

We can then check the status of our application deloyment by running the following command:

./kubectl -s 192.168.1.55:8080 get pods

You should see a tomcat-server-* entry and the status should say "Image: tomcat is not ready on the node". You can give it a few seconds and then re-run the command until it is showing "Running" as the status which means our application has been successfully deployed by the K8 Cluster.

We can now open a browser to the IP Address of our K8 Master VM's IP, which in my environment was 192.168.1.55 and specify port 30001 which was defined in the configuration file of Tomcat application and we should see that we now have Tomcat running.

We can also easily scale up the number of replication servers for our Tomcat application by running the following command:

./kubectl -s 192.168.1.55:8080 scale --replicas=2 rc tomcat-server

You can easily scale the application back down by re-running the command and specifying a value of one. Lastly, if we want to delete our application, we can run the following two commands:

./kubectl -s 192.168.1.55:8080 delete service tomcat
./kubectl -s 192.168.1.55:8080 delete rc tomcat-server

Once we are done using using our K8 Cluster, we can tear it down by specifying the ID of the K8 Cluster found in Step 8 by running the following command which will now delete the VMs that Photon Controller had deployed:

./photon -n cluster delete 9b159e92-9495-49a4-af58-53ad4764f616

Hopefully this gave you a quick taste on how easy it is to setup a fully functional K8 Cluster using Photon Controller. In the next article, we will take a look at deploying a Mesos Cluster using Photon Controller, so stay tuned!

Using Ansible to provision a Kubernetes Cluster on VMware Photon

11/05/2015 by William Lam 1 Comment

I am always interested in learning and playing with new technologies, solutions and tools. Ansible, a popular configuration management tool which was recently acquired by Redhat, is one such tool that I have had on my to do list for some time now. It is quite difficult to find extra free time and with a new 7month year old, it has gotten even harder. However, in the last week or so I have been waking up randomly at 4-5am and I figured I might as well put this time to go use and give Ansible a try.

As the title suggests, I will be using Ansible to deploy a Kubernetes Cluster running on top of VMware's Photon OS. The motivation behind this little project was after watching Kelsey Hightower's recorded session at HashiConf on Managing Applications at Scale and comparing HashiCorp's Nomad and Google's Kubernetes (K8s) scheduler. I knew there were already a dozen different ways to deploy K8s, but I figure I would try something new and add a VMware spin to it by using the Photon OS.

I had found an out dated reference on setting up K8s in the Photon OS documentation and though a few of the steps are no longer needed, it provided a good base for me on creating the Ansible playbook for setting up a K8s Cluster. If you are not familiar with Ansible, this getting started guide was quite helpful. For our K8s setup, we will have a 2-Node setup, one being the Master and the other the Minion. If you are interested in an overview of K8s, be sure to check out the official documentation here.

Step 1 - You will need to deploy at least 2 Photon OS VMs, one for the Kubernetes Master and one for the Minon. This can be done using either the ISO or by deploying the pre-packaged OVA. For more details on how to setup Photon OS, please refer to the documentation here. This should take only a few minutes as the installation or deployment of Photon OS is pretty quick. In my setup, I have 192.168.1.133 as Master and 192.168.1.111 as the Minion.

Step 2 - Download and install Ansible on your client desktop. There are several options depending on the platform you plan to use. For more information take a look at the documentation here. In my setup, I will be using a Mac OS X system and you can easily install Ansible by running the following command:

brew install ansible

Step 3 - Next, to verify and test that our installation of Ansible was successful, we will need to create our inventory host file (I called it hosts but you can name it anything you want) which will contain the mappings to our Photon OS VMs. The example below assumes you do not have DNS running in your environment and I am making use of the variable options in host file to specify a friendly names versus just using the IP Addresses which will be read in later. If you do have DNS in your environment, you do not need the last section of the file.

[kubernetes_cluster]
192.168.1.133
192.168.1.111

[masters]
192.168.1.133

[minions]
192.168.1.111

[kubernetes_cluster:vars]
master_hostname=photon-master
master_ip=192.168.1.133
minion_hostname=photon-node
minion_ip=192.168.1.111

[kubernetes_cluster]

192.168.1.133

192.168.1.111

[masters]

192.168.1.133

[minions]

192.168.1.111

[kubernetes_cluster:vars]

master_hostname=photon-master

master_ip=192.168.1.133

minion_hostname=photon-node

minion_ip=192.168.1.111

Step 3 - We will be performing a basic "ping" test to validate that Ansible is in fact working and can communicate with our deployed Photon VMs. Run the following command which will specify the inventory host file as input:

ansible -i hosts all -m ping --user root --ask-pass

Step 4 - If the previous step was successful, we can now create our Ansible playbook which will contain the instructions on setting up our K8s Cluster. Download the kubernetes_cluster.yml to your desktop and then run the following command:

ansible-playbook -i hosts --user root --ask-pass kubernetes_cluster.yml

If you want to use SSH keys for authentication and if you have already uploaded the public keys to your Photon VMs, then you can replace --ask-pass with --private-key and specify the full path to your SSH private keys.

Step 5 - Once the Ansible playbook has been successfully executed, you should see summary at the end showing everything was ok. To verify that our K8s Cluster has been properly setup, we will check the Minon's node status state which should show "ready". To do so, we will login to the K8s Master node and run the following command:

kubectl get nodes

You should see that the status field shows "Ready" which means the K8s Cluster has been properly configured.

At this point you have a basic K8s Cluster setup running on top of VMware Photon. If you are interested in exploring K8s further, there are some nice 101 and 201 official tutorials that can be found here. Another handy reference that I used for creating my Ansible playbook was this article here which provided a way to create loops using the lineinfile param.

How to deploy a Kubernetes Cluster on vSphere?

09/05/2014 by William Lam 18 Comments

In the previous article, we walked through the installation of govmomi which is the vSphere SDK for Go and govc which is a command-line interface that uses the SDK to expose vSphere functionality which is used in the Kubernetes vSphere Provider. Now that we have all the prerequisites installed, we are now ready to deploy a Kubernetes Cluster onto a vSphere based infrastructure.

UPDATE (10/26/15) - It looks like the instructions on setting up a Kubernetes Cluster has since changed and I have updated the instructions below. One of the main changes is instead of building from source we are just downloading the Kubernetes binaries.

tep 1 - You will need to download the latest Kubernetes binary (kubernetes.tar.gz) which can be found here. At the time of updating this article, the latest is v1.2.0-alpha2.

Step 2 - Go ahead and extract the contents of kubernetes.tar.gz file by running the following command:

tar -zxvf kubernetes.tar.gz

Step 2 - Download the Kubernetes VMDK using either "wget" or "curl" depending on what is available on your system. Since I am on a Mac, it only has curl by default. Here are the two commands depending on the which download utility you have access to:

wget https://storage.googleapis.com/govmomi/vmdk/kube.vmdk.gz{,.md5}
curl -O https://storage.googleapis.com/govmomi/vmdk/kube.vmdk.gz{,.md5}

Once the download has completed, you should now see two files in your working directory: kube.vmdk.gz and kube.vmdk.gz.md5

Step 3 - Next we need to un-compress the VMDK by running the following command:

gzip -d kube.vmdk.gz

Step 4 - Once the VMDK has been extracted, we will need to upload it to a vSphere datastore. Before doing so, we need to set a couple of environmental variables that provide connection details to your vSphere environment. Below are the commands to set the environmental variables, you will need to replace the information from your own environment.

export GOVC_URL='https://[USERNAME]:[PASSWORD]@[ESXI-HOSTNAME-IP]/sdk'
export GOVC_DATASTORE='[DATASTORE-NAME]'
export GOVC_DATACENTER='[DATACENTER-NAME]'
export GOVC_RESOURCE_POOL='*/Resources'
export GOVC_GUEST_LOGIN='kube:kube'
export GOVC_INSECURE=true

You can leave the last three variables as-is. The GOVC_RESOURCE_POOL defines the full path to root Resource Pool on an ESXi host which will always exists and for vCenter Server, it is the name of the vSphere Cluster or Resource Pool the GOVC_GUEST_LOGIN is the credentials to the Kubernetes Master/Node VMs which are defaulted in the VMDK that was downloaded. The last variable GOVC_INSECURE is if you have an ESXi or vCenter Server using self-signed SSL Certificate, you will need to ensure this variable is set.

To upload the kube.vmdk to the vSphere Datastore and under the kube directory which will be created for you, you will run the following command:

govc datastore.import kube.vmdk kube

Step 5 - We now have our base kube.vmdk uploaded to our ESXi host and before we are ready to deploy our Kubernetes Cluster, we need to set the provider by running the following command:

export KUBERNETES_PROVIDER=vsphere

Step 6 - We are now ready to deploy the Kubernetes Cluster which consists of Kubernetes Master and 4 Kubernetes Minions and they will be derived from the kube.vmdk that we just uploaded. To do so, you will run the following command:

kubernetes/cluster/kube-up.sh

Note: If you see a message about "Docker failed to install on kubernetes-minion-N" it is possible that this related to a timing issue in which the Minion may not be up when the Master is checking. You can verify this by running the next command, else you can follow the instructions to bring down the Kubernetes Cluster and re-creating it.

Step 7 - In the previous step, we deployed the Kubernetes Cluster and you will see the assigned IP Addresses for the Master/Minions along with the credentials (auto-generated) for the Docker Containers. We can confirm that the everything was created successfully by checking the number of running Minions by running the following command:

cluster/kubecfg.sh list minions

Step 8 - Once we have confirmed we have 4 running Minions, we can now deploy a Docker Container onto our Kubernetes Cluster. Here is an example of deploying 2 nginx mapping from port 8080 to 80 instances by running the following command:

cluster/kubecfg.sh -p 8080:80 run dockerfile/nginx 2 myNginx

Step 9 - We should expect to see two "Pods" for the nginx instances we have instantiated and we can do so by running the following command:

cluster/kubecfg.sh list pods

Here are some additional commands to stop and remove the Pods:

cluster/kubecfg.sh stop myNginx
cluster/kubecfg.sh rm myNginx

You can also bring down the Kubernetes Cluster (which will destroy the Master/Minion VMs) by running the following command:

cluster/kube-down.sh

Hopefully this gave you a good introduction to the new Kuberenetes vSphere Provider and I would like to re-iterate that this is still being actively developed on and the current build is an Alpha release. If you have any feedback/requests or would like to contribute, be sure to check out the Kubernetes and govmomi Github repository and post your issues/pull requests.