Good afternoon!
In my study of Kubernetes, I got to the practice of deploying Kuber on the server. There are different deployment scenarios. I chose kubespray. Can you tell me if you can somehow deploy kuber on a host? Or is it necessary to create virtual machines, set up a network between them and only then deploy the cluster?
Node: A node may be a virtual or physical machine, depending on the cluster. Each node is managed by the control plane and contains the services necessary to run Pods.
You can deploy single Node Kubernetes
For local (development, test etc) purposes:
minikube
kind
...
For production:
k3s
k0s
...
And, of course, you can create separate nodes under one "machine." And use them as worker nodes, but the above solutions are simpler.
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 am trying to create Kubernetes cluster having 1 master and 2 worker nodes by using the tool kubeadm in my on-premise machines. I am following the Kubernetes official documentation for forming the cluster from the following url:
https://kubernetes.io/docs/setup/production-environment/tools/kubeadm/high-availability/
After installing all the runtime and completing before begin pre-requistics steps, I found in the document as the first step of forming the cluster is Create load balancer for kube-apiserver.
My Doubt
When I created the single master 3 worker nodes cluster using kubespray tool, I did not created any separate load balancer for that. So here when I am following the kubeadm tool, Do I need to create the load balancer actually for forming ?
Why are both tools showing different way, Since I did not created load balancer by using kubespray tool. Now I am trying to create cluster with kubeadm tool.
Speaking of load balancers creation during Kubernetes deployment using Kubeadm it depends on your setup. It is not mandatory to setup load balancer. Your cluster will still work, but without load balancing, it's going to be hard to qualify this cluster as HA.
In a single master setup as it is in your case, the master node manages the etcd database, API server, controller manager and scheduler, along with the worker nodes. However, if that single master node fails, all the worker node fail as well and entire cluster will be lost.
Learn more here: kubernetes-ha-kubeadm.
Kubeadm covers the needs of a life-cycle management for Kubernetes clusters, including self-hosted layouts, dynamic discovery services, etc. Kubespray is more about generic configuration, initial clustering, and bootstrapping.
Kubespray is a good choice when you either are familiar with Ansible or seek a possibility to switch between multiple platforms. If your priority is tight integration with unique features offered by the supported clouds, and you plan to stick with your provider, kops may be a better option.
Deploying a loadbalancer is up to a user and is not covered by ansible roles in Kubespray. By default, it only configures a non-HA endpoint, which points to the access_ip or IP address of the first server node in the kube-master group. It can also configure clients to use endpoints for a given loadbalancer type. More information you can find here: kubespray-lb.
Here you have comparision of Kubernetes deployment tools: Kubernetes Deployment Tools.
I managed to install a 3-node cluster on VMs within the same network.
But is there a way to install a multi-node K8S cluster on VMs with different IP ranges? (VMs which are not located in the same network)
The reason for this question is the scenario that I have in mind:
I need to deploy a micro-service application (written in Java) with K8S. I made docker images from each service in my application and its working locally.
I plan to have each service to be run in a separate physical location (within different networks)
For this I need a multi-node cluster, but each node will get different IP range. Is this possible?
if there is a connectivity among the three nodes then i dont see any reason why you cant setup multi node cluster.
note that kubernetes needs the machines to be closer. because lot of calls happen between api server, kubelet, kube-proxy. it would hit cluster and application performance.
I have played around a little bit with docker and kubernetes. Need some advice here on - Is it a good idea to have one POD on a VM with all these deployed in multiple (hybrid) containers?
This is our POC plan:
Customers to access (nginx reverse proxy) with a public API endpoint. eg., abc.xyz.com or def.xyz.com
List of containers that we need
Identity server Connected to SQL server
Our API server with Hangfire. Connected to SQL server
The API server that connects to Redis Server
The Redis in turn has 3 agents with Hangfire load-balanced (future scalable)
Setup 1 or 2 VMs?
Combination of Windows and Linux Containers, is that advisable?
How many Pods per VM? How many containers per Pod?
Should we attach volumes for DB?
Thank you for your help
Cluster size can be different depending on the Kubernetes platform you want to use. For managed solutions like GKE/EKS/AKS you don't need to create a master node but you have less control over our cluster and you can't use latest Kubernetes version.
It is safer to have at least 2 worker nodes. (More is better). In case of node failure, pods will be rescheduled on another healthy node.
I'd say linux containers are more lightweight and have less overhead, but it's up to you to decide what to use.
Number of pods per VM is defined during scheduling process by the kube-scheduler and depends on the pods' requested resources and amount of resources available on cluster nodes.
All data inside running containers in a Pod are lost after pod restart/deletion. You can import/restore DB content during pod startup using Init Containers(or DB replication) or configure volumes to save data between pod restarts.
You can easily decide which container you need to put in the same Pod if you look at your application set from the perspective of scaling, updating and availability.
If you can benefit from scaling, updating application parts independently and having several replicas of some crucial parts of your application, it's better to put them in the separate Deployments. If it's required for the application parts to run always on the same node and if it's fine to restart them all at once, you can put them in one Pod.
I'm trying to use the Kubernetes to deploy Docker Container and I found this tutorial.
So according to this tutorial, what is the prerequisites?
They said that "services that are typically on a separate Kubernetes master system and two or more Kubernetes node systems are all running on a single system."
But I don't understand how we run both master and nodes on a single system (for example I have one instance EC2 with IP address 52.192.x.x)
That is a guide about running Kubernetes specifically on RedHat Atomic nodes. There are lots of guides about running Kubernetes on other types of nodes; see the Creating a Kubernetes Cluster page on docs.k8s.io.
One of the guides on the Kubernetes site shows how to run a local docker-based cluster, which should also work for you on a single node in the cloud.