According to the minikube handbook the configuration commands are used to "Configure your cluster". But what does that mean?
If I set cpus and memory then are these the max values the cluster as a whole can ever consume?
Are these the values it will reserve on the host machine in preparation for use?
Are these the values that are handed to the control plane container/VM and now I have to specify more resources when making a worker node?
What if I want to add another machine (VM or bare metal) and add its resources in the form of a worker node to the cluster? From the looks of it I would have to delete that cluster, change the configuration, then start a new cluster with the new configuration. That doesn't seem scalable.
Thanks for the help in advance.
Answering the question:
If I set cpus and memory then are these the max values the cluster as a whole can ever consume?
In short. It will be a limit for the whole resource (either a VM, a container, etc. depending on a --driver used). It will be used for the underlying OS, Kubernetes components and the workload that you are trying to run on it.
Are these the values it will reserve on the host machine in preparation for use?
I'd reckon this would be related to the --driver you are using and how its handling the resources. I personally doubt it's reserving the 100% of CPU and memory you've passed in the $ minikube start and I'm more inclined to the idea that it uses how much it needs during specific operations.
Are these the values that are handed to the control plane container/VM and now I have to specify more resources when making a worker node?
By default, when you create a minikube instance with: $ minikube start ... you will create a single node cluster capable of being a control-plane node and a worker node simultaneously. You will be able to run your workloads (like an nginx-deployment without adding additional node).
You can add a node to your minikube ecosystem with just: $ minikube node add. This will make another node marked as a worker (with no control-plane components). You can read more about it here:
Minikube.sigs.k8s.io: Docs: Tutorials: Multi node
What if I want to add another machine (VM or bare metal) and add its resources in the form of a worker node to the cluster? From the looks of it I would have to delete that cluster, change the configuration, then start a new cluster with the new configuration. That doesn't seem scalable.
As said previously, you don't need to delete the minikube cluster to add another node. You can run $ minikube node add to add a node on a minikube host. There are also options to delete/stop/start nodes.
Personally speaking if the workload that you are trying to run requires multiple nodes, I would try to consider other Kubernetes cluster built on top/with:
Kubeadm
Kubespray
Microk8s
This would allow you to have more flexibility on where you want to create your Kubernetes cluster (as far as I know, minikube works within a single host (like your laptop for example)).
A side note!
There is an answer (written more than 2 years ago) which shows the way to add a Kubernetes cluster node to a minikube here :
Stackoverflow.com: Answer: How do I get the minikube nodes in a local cluster
Additional resources:
Kubernetes.io: Docs: Setup: Production environment: Tools: Kubeadm: Create cluster kubeadm
Github.com: Kubernetes sigs: Kubespray
Microk8s.io
Related
I have a k8s cluster that runs the main workload and has a lot of nodes.
I also have a node (I call it the special node) that some of special container are running on that that is NOT part of the cluster. The node has access to some resources that are required for those special containers.
I want to be able to manage containers on the special node along with the cluster, and make it possible to access them inside the cluster, so the idea is to add the node to the cluster as a worker node and taint it to prevent normal workloads to be scheduled on it, and add tolerations on the pods running special containers.
The idea looks fine, but there may be a problem. There will be some other containers and non-container daemons and services running on the special node that are not managed by the cluster (they belong to other activities that have to be separated from the cluster). I'm not sure that will be a problem, but I have not seen running non-cluster containers along with pod containers on a worker node before, and I could not find a similar question on the web about that.
So please enlighten me, is it ok to have non-cluster containers and other daemon services on a worker node? Does is require some cautions, or I'm just worrying too much?
Ahmad from the above description, I could understand that you are trying to deploy a kubernetes cluster using kudeadm or minikube or any other similar kind of solution. In this you have some servers and in those servers one is having some special functionality like GPU etc., for deploying your special pods you can use node selector and I hope you are already doing this.
Coming to running separate container runtime on one of these nodes you need to consider two points mainly
This can be done and if you didn’t integrated the container runtime with
kubernetes it will be one more software that is running on your server
let’s say you used kubeadm on all the nodes and you want to run docker
containers this will be separate provided you have drafted a proper
architecture and configured separate isolated virtual network
accordingly.
Now comes the storage part, you need to create separate storage volumes
for kubernetes and container runtime separately because if any one
software gets failed or corrupted it should not affect the second one and
also for providing the isolation.
If you maintain proper isolation starting from storage to network then you can run both kubernetes and container runtime separately however it is not a suggested way of implementation for production environments.
I have a node mistakenly registered on a cluster B while it is actually serving for cluster A.
Here 'registered on a cluster B' means I can see the node from kubectl get node from cluster B.
I want to deregister this node from cluster B, but keep the node intact.
I know regular process to delete a node is:
kubectl drain node xxx
kubectl delete node xxx
# on node
kubeadm reset
But I do not want pods on the node from cluster A to be deleted or transfered. And I want to make sure the node would not self-register to cluster B afterwards.
To be clear, let's say, cluster A has Pod A on the node, cluster B has Pod B on the node as well, I want to delete node from cluster B, but keep Pod A intact. (By the way, can I see Pod A from cluster B?)
Thank you in advance!
To deregister the node without removing any pod you run below command
kubectl delete node nodename
After this is done the node will not appear in kubectl get nodes
For the node to not self register again stop the kubelet process on that node by logging into that node and using below command.
systemctl stop kubelet
As this case has been already clarified I decided to publish a Community Wiki answer based on the following comment:
#mario nvm, I thought different clusters in one node affect each
other, actually they do not, they just share container runtime which
is more like 'read-only', and they have different kubelets of
themselves listening on different port. – Li Ziyan Aug 17 at 5:29
to make it clear also for other users what was actually the issue here and how it has been solved or simply clarified.
So if you design your infrastructure in such a way that you use one physical (or virtual) machine as Node for more than one kubernetes clusters (which I believe is not very common case) the infrastructure looks as follows:
Components that are shared:
physical (or virtual) node
common container runtime environment (e.g. docker)
Components that are separate:
two separate kubelets. Although they are running on the same physical/virtual node they are configured to listen on different ports and are registered within two master Nodes (or more specifically two different kube-apiservers being part of two different kubernetes control planes)
two logically separate, independent kubernetes Nodes which, although they are configured on the same physical node/host, are logically completely separate kubernetes Nodes, being part of two completely different kubernetes clusters that don't interfere with each other in any way.
I hope it helps to clarify possible confusion about this question and maybe help someone in case they have similar doubts.
I am searching for a solution that enables me to set up a single node K8s cluster and if I needed I add nodes to it later.
I am aware of solutions such as minikube and microk8s but they are not expandable. I am trying k3s at the moment exactly because it is offering this feature but I have some problems with storage and other stuff that I am working on them.
Now my questions:
What other solution for this exists?
What are the disadvantages if I untaint the master node and run everything there (for a long period and not just for test)?
You can use kubeadm to setup a single node "cluster". Then you can use the join command to add more nodes
You can expand k3s cluster via k3sup join.Here is guide.
Key Kubernetes services such as kube-apiserver, kube-scheduler should be available and running smoothly at all times on master nodes. Therefore, it is essential to have dedicated resources for the master nodes, and avoid having other non-critical workloads interfere with the functioning of the master services
What are the disadvantages if I untaint the master node and run everything there (for a long period and not just for test)?
Failure of the worker will of course bring down your applications. When you recover it or spin up another one, K8s will recover your apps for you.
Failure of the master will not adversely affect your systems only the cluster's ability to manage itself and its self-healing capabilities (which will affect uptime at some point).
I am searching for a solution that enables me to set up a single node K8s cluster and if I needed I add nodes to it later.
To the best of my knowledge, there is no such thing as single node production ready k8s cluster.
For something small and simple you can check Rancher.
What other solution for this exists?
kubeadm allows you to install everything on a single node. Install kubeadm on the node, "kubeadm init", install a pod network, then remove the master taint.
Another solution you may be interested in is the Kubespray.
Some "honorable mentions" are:
Charmed Kubernetes by Canonical allows you to do everything on one node; however it should be quite a big node, so may be not the case here (but still worth mentioning).
If you don't really require all the k8s power (with only one small node), then Nomad could be an alternative.
Let me know if that helps.
is it possible to run k8s on single node without using minikube? Today I use kubeadm with 2 hosts, but I would like to know if it is possible to run using only one host.
You can run kubeadm init command to initialize single node cluster. You can add/remove nodes to the cluster.
taint the master so that it can run containers using the below command
kubectl taint nodes --all node-role.kubernetes.io/master-
You need to look into the hardware requirements for running a single node cluster. You would need to run
etcd which is the backing store for all cluster data.
Control plane software(scheduler, controller manager, api-server, kubeadm)
Worker node software(kubectl, kube-proxy)
all on one node.
When installing kube-adm I see the hardware requirements(https://kubernetes.io/docs/setup/production-environment/tools/kubeadm/install-kubeadm/) as
2 GB or more of RAM per machine (any less will leave little room for your apps)
and 2 CPUs or more
Example configurations for etcd (https://github.com/etcd-io/etcd/blob/master/Documentation/op-guide/hardware.md#example-hardware-configurations).
For the CKA exam training material the recommended node setting for a single machine is 2 vcpu's and 7.5 GB memory with a note of caution that you may experience slowness.
I am going by Ubuntu 18.04 Linux for my recommendations. Another thing you need to do is disable the swap(https://serverfault.com/questions/881517/why-disable-swap-on-kubernetes). It is necessary since kubernetes makes maximum use of disk and cpu resources provided.
So if it for your learning. Go ahead and start with 2 vcpu's and 7.5 GB memory.
You could check
k3s
KinD
MicroK8s
for single-node Kubernetes installations.
I am new to the Kubernetes and cluster.
I would like to bring up an High Availability Master Only Kubernetes Cluster(Need Not to!).
I have the 2 Instances/Servers running Kubernetes daemon, and running different kind of pods on both the Nodes.
Now I would like to somehow create the cluster and if the one of the host(2) down, then all the pods from that host(2) should move to the another host(1).
once the host(2) comes up. the pods should float back.
Please let me know if there is any way i can achieve this?
Since your requirement is to have a 2 node master-only cluster and also have HA capabilities then unfortunately there is no straightforward way to achieve it.
Reason being that a 2 node master-only cluster deployed by kubeadm has only 2 etcd pods (one on each node). This gives you no fault tolerance. Meaning if one of the nodes goes down, etcd cluster would lose quorum and the remaining k8s master won't be able to operate.
Now, if you were ok with having an external etcd cluster where you can maintain an odd number of etcd members then yes, you can have a 2 node k8s cluster and still have HA capabilities.
It is possible that master node serves also as a worker node however it is not advisable on production environments, mainly for performance reasons.
By default, kubeadm configures master node so that no workload can be run on it and only regular nodes, added later would be able to handle it. But you can easily override this default behaviour.
In order to enable workload to be scheduled also on master node you need to remove from it the following taint, which is added by default:
kubectl taint nodes --all node-role.kubernetes.io/master-
To install and configure multi-master kubernetes cluster you can follow this tutorial. It describes scenario with 3 master nodes but you can easily customize it to your needs.