Does Kubernetes have the ability/need to hook into a cloud provider (AWS, Rackspace) to spin up new nodes? If so, how does it then provision the node - does it run Ansible etc? Or will Kubernetes need to have all the nodes available to it manually?
The short answer is no.
The longer answer is explained in the following blog posting that describes the new kubeadm command:
http://blog.kubernetes.io/2016/09/how-we-made-kubernetes-easy-to-install.html
There are three stages in setting up a Kubernetes cluster, and we
decided to focus on the second two (to begin with):
Provisioning: getting some machines
Bootstrapping: installing Kubernetes on them and configuring certificates
Add-ons: installing necessary cluster add-ons like DNS and monitoring services, a pod network, etc
We realized early on that there's enormous variety in the way that
users want to provision their machines.
They use lots of different cloud providers, private clouds, bare
metal, or even Raspberry Pi's, and almost always have their own
preferred tools for automating provisioning machines: Terraform or
CloudFormation, Chef, Puppet or Ansible, or even PXE booting bare
metal. So we made an important decision: kubeadm would not provision
machines. Instead, the only assumption it makes is that the user has
some computers running Linux.
Update
http://blog.kubernetes.io/2017/01/stronger-foundation-for-creating-and-managing-kubernetes-clusters.html
Related
I'm developing a Kubernetes scheduler and I want to test its performance when nodes join and leave a cluster, as well as how it handles node failures.
What is the best way to test this locally on Windows 10?
Thanks in advance!
Unfortunately, you can't add nodes to Docker Desktop with Kubernetes enabled. Docker Desktop is single-node only.
I can think of two possible solutions, off the top of my head:
You could use any of the cloud providers. Major (AWS, GCP, Azure) ones have some kind of free tier (under certain usage, or timed). Adding nodes in those environments is trivial.
Create local VM for each node. This is less than perfect solution - very resource intesive. To make adding nodes easier, you could use kubeadm to provision your cluster.
I have recently been reading more about infrastructure as a service (IaaS) and platform as a service (PaaS) and had some questions. I see when we opt for a PaaS solution, it is generally very easy to create the infrastructure as the cloud providers handle that for us and we can even automate the deployment using an infrastructure as code solution like Terraform.
But if we use an IaaS solution or even a local on premise cluster, we lose a lot of the automation it seems that PaaS allows. So I was curious, are there any good tools out there for automating infrastructure deployment on a local cluster that is not in the cloud?
The best thing I could think of was to run a local Kubernetes cluster and then Dockerize each of the infrastructure components, but this seems difficult as each node in the cluster will need its own specific configuration files.
From my basic Googling, it seems like there is not a good solution to this.
Edit:
I was not clear enough with my original intentions. I have two problems I am trying to solve.
How do I automate infrastructure deployment locally? For example, suppose I wanted to create a Hadoop HDFS cluster. I would need to configure one node to be the namenode with an accessible IP, and the other nodes to be datanodes that are aware of the namenode's IP. At the moment, I have to do this manually by logging into each node, checking it's IP, and then configuring each one. How would I automate this? If I were to use a Kubernetes approach, how do I specify that one of the running pods needs to be the namenode and the others are datanodes? How do I find the pods' IPs and have them be aware of the namenode IP?
The next problem I have is very similar to the first, but a slight modification. How would I deploy specific configuration files to each node. For instance in Kafka, the configuration file for one node, requires the IPs of the Zookeeper nodes, as well as the IP it should listen on. This may be different for every node in the cluster. Is there a good way to make these config files pod specific, so that I do not have to do bash text processing to insert the correct contents into each pod's config files?
You can use Terraform for all of your on-premise Infra. Automation, and Ansible for configuration management.
Let's say you have three HPE servers, Install K8s or VMware on them using Ansible, then you can treat them as three Avvaliabilty zones in one region, same as AWS. from this you can start deploying dockerize apps, or helm charts using Terraform.
Summary:
Ansbile for installing and configuration K8s.
Terraform for provisioning K8s.
Helm for installing apps on K8s.
After this you gonna have a base automated on-premise Infra.
I'm looking for a way to create a live Kubernetes cluster without too much hassle.
I've got a nice HP server, which could run a few VM's with kubernetes on top. The reason for VM's is to isolate this from the host machine. Ideally, the VMs should only run containerd and kubelet and are essentially disposable for node-upgrades.
However, I get lost in what tooling would provide this. minikube? microk8s? k3s? rancher? charmed kubernetes? some existing qemu image? some existing vagrant config? The more managed it is, the better. So far I liked minikube, but it doesn't have "start on reboot" for example, nor the flexibility for node upgrades.
I have tried a lot of tools to train for the CKAD certification. For my usage, the better option for a local cluster was k3s and multipass (for online clusters, I have used Civo). Both are very fast to proceed their respective tasks, so it allows me to create clusters at will and dispose them to be able to work on clean environments.
multipass to create VM quickly
k3s which is nothing else than a lightweight kubernetes
You can find easily some tutorials to automate the creation of clusters for example:
https://betterprogramming.pub/local-k3s-cluster-made-easy-with-multipass-108bf6ce577c
https://medium.com/#yankee.exe/setting-up-multi-node-kubernetes-cluster-with-k3s-and-multipass-d4efed47fed5
https://github.com/superseb/multipass-k3s
I am already running a single master kubernetes cluster now and I am doing research about setting up Highly available Kubernetes clusters. I was thinking of Multi master cluster setup then realized self-hosted cluster might be a better option to go future ready.
Additional challenge is I am doing it in Bare Metal (Meaning, I am going to use cloud vms from these cloud provider, Hetzner, Linode, DigitialOcean and they have CSI driver, cloud controller manager etc., )
In this case, I see 2 options.
Setup with bootkube (https://github.com/kubernetes-sigs/bootkube)
Setup with kubeadm self-hosting. (https://kubernetes.io/docs/setup/production-environment/tools/kubeadm/self-hosting/)
I assume this is still an early topic hence I am not able to find guidance to choose the right approach and then correct documentation. I need this for a scalable production environment where I will start small with at least 8 nodes and can grow faster.
Is bootkube considerable for future readiness?
or kubeadm self-hosting is still in alpha stage, am I getting into a risk running a production environment?
Any good, documentation, blog, article to go in this direction?
I use Keepalived + Haproxy and Ansible to deploy HA kubernetes cluster. Now kubeadm supports join control plane command, so it easy to integrate with ansible.
You can also refer: https://github.com/kubernetes-sigs/kubespray.
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I am trying to change my deploy scenario from docker to Kubernetes. Now I explored the architecture of Kubernetes - Cluster, Nodes, Pods, Services, replica Sets/controller, Kubernetes-cni, kube-ctl etc. Now I need to begin with deployment into Kubernetes cluster. When I am exploring, I found documentations and discussions that can create single node and master in same machine or possible in VMs. Also found kubespray and minikube documentations for cluster creation.
Here I am adding my confusions about hands on with Kubernetes.
For creating and working with Kubernetes, why there is a variation like single node and master in same or in VMs? Why there is a deviation in cluster container?
How I can decide whether I need to choose single node and master in same machine or I need to use Vms for different nodes?
How the Minikube and Kubespray is providing different methodology in Kubernetes architecture?, Since Kubernetes are product of one single source - Google.
If I am installing kubeadm, kubernetes-cni and kubelet in my ubuntu 16.04, Can I initiate nodes in the same machine ?
How can I clarify these confusions?
The taxonomy of concepts and terms is very complicated, and the documentation is still pretty sparse.
1. For creating and working with kubernetes,
why there is a variation like single node and master in same or in VMs?
Why there is a deviation in cluster container?
The deviation is to support many distinct use cases- container workload developers working on their laptops needing what amounts to a fake cluster without a lot of operational ceremony; kubernetes ops folks learning and testing on a small but real clusters; and real production workloads for varyingly-sized plants.
For the first case, for container workload development, there is a piece of software called minikube, which is like a distribution of kubernetes that automates creating a single virtual machine- using VirtualBox or other desktop-class virtual machine tooling- that is preconfigured to run a combined kubernetes master and node, sufficient to be able to run real kubernetes workloads, but on a laptop.
For the second case, for non production purposes, the master and worker functions can be run on a single machine, or a single master machine can be used with a small number of worker machines.
A production kubernetes cluster will usually have 3 or 5 or 7 master machines- VMs or bare metals. Multiple masters are needed to maintain quorum for etcd- where kubernetes stores all runtime state- in the case of machine failures. 3 master machines allow for 1 master machine to fail without disrupting the cluster. 5 masters will tolerate 2 master machine failures, etc.
This number of masters can support a large number of worker machines- dozens to hundreds- running the container workloads. In a production environment, one would not want to run client workloads on master machines.
2. How I can decide whether I need to choose single node and master
in same machine. Or do I need to use Vms for different nodes?
See above- for development, use minikube. For production, plan to use multiple redundant masters if you are running the cluster yourself, or use a cloud provider's managed kubernetes offering.
3. How the Minikube and Kubespray is providing different methodology
in kubernetes architecture?
Minikube is for development only. Kubespray is one of many tools that provides some automation help when building a production cluster. Kubespray's distinguishing feature is the use of Ansible for machine setup and automation. This may or may not be desirable, depending on your comfort and interest in Ansible and/or its competitors.
4. Why have so many options when kubernetes is the product of a
single source - google.
Kubernetes certainly originated in Google, but now there are hundreds or more engineers across many companies, including Microsoft, Amazon, RedHat, Oracle, and tons of tiny companies, actively working on it. It is a remarkable project.
5. If I am installing kubeadm, kubernetes-cni and kubelet in my ubuntu 16.04
Can I initiate nodes in the same machine ?
Kubeadm is a setup tool, not a production runtime tool, but yes, you can run containers on the same machine as the bits that are needed for a kubernetes master. In addition to etcd, kubelet, apiserver, controller manager, you need to run Docker as well- Kubelet talks to Docker to schedule containers. I would only advise NOT running anything else on this machine- improper configuration can cause problems with the machine serving as master/worker so any other work will be lost.