What i want do is deployment of multiple container application in...
In RHEL os
RedHat Supportable product (if possible)
In single node K8S cluster (Bare metal machine)
So I found several way but I concerned about..
minikube, minishift, OKD, CodeReady Container
First, they run in VM but what I want is run in HOST.
Second, their doc said they are not for production environment.
So, Is there any PaaS for single-node cluster as production environment?
Docker, Docker-compose
Deployment target OS should maybe RHEL8. I guess it is not good idea to use docker because RedHat product is moving away from docker. Even in RHEL8 repository, there is no docker rpm for el8 yet.
My question is
Is there any PaaS for single-node cluster as production environment?
If not exist, docker-compose is best?
It was already mentioned, you should not use single node setup in production environment.
You should not do that because, if your servers drops you have service offline. There is nothing to switch to, nothing that might continue the process that was being worked on.
If you still want to setup a single node Kubernetes cluster you can do that using kubeadm. I think this would be closest to production grade as you can get.
Other then that as an alternative you can play with Installing Kubernetes with Minikube or Install a local Kubernetes with MicroK8s.
It's up to you which one you will choose but you need to remember this should not be running as a production, this should be a lab or a test environment which if works as expected will be migrated into few node production grade cluster.
As for PaaS as a single node there is Dokku.
Docker powered mini-Heroku. The smallest PaaS implementation you've ever seen.
And if you would consider using a cloud for PaaS, you can choose from AWS Cloud9, Azure App Service or Google App Engine.
Single node cluster is not recommended for production applications. You need scalability, high availability, fault tolerance for production apps. You must have more than one node to have these features.
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've found a partial answer Difference between Minikube, Kubernetes, Docker Compose, Docker Swarm, etc here, but I still do not completely get it:
In my understanding, kubernetes is a container-orchestration system. However, Minikube looks very similar to me.
Can somebody explain me when you would use minikube versus when you would use minikube, and why?
I think your question should have been "Can somebody explain me when you would use minikube versus when you would use Kubernetes, and why?"
Minikube is a small and easy Kubernetes setup for your Work-PC. You can install and configure a Kubernetes cluster very easily with it. However, for a production environment it is not the best choice. Minikube normally starts a virtual machine on your PC witch will affects the performance of your cluster other than Kubernetes which will run directly with your kernel if you use linux. Furthermore, like Butuzov already answered, it is only one node, not a "real" cluster.
So you use Kubernetes if you are in a production environment where you need distributed systems and workload as well as redundancy and failure safety.
Hope that helps for your understanding.
Edit: Use cases
Minikube:
Developer or DevOps who trying to execute a complex distributed system locally for testing purposes but with deployment over Helm.
Developer or DevOps who tries to create a deployment with Helm locally.
Kubernetes (standalone):
Execute complex distributed system on production systems.
Execute heavy workload (multiple products, distributed systems) in production
minikube - is one node cluster, with a master that can get loads, with a lot of solved and automated issues. designated to test, learn things from kubernetes ecosystem.
kubernetes itself is orchestrator that can come to you as managed service with a lot of problems (pv or loadbalancers) solved or like a lego, or you will tune here and there... well thing we called production ready.
minikube is ok to learn (not always but in 90% of cases) or experiment with tiny loads.
Our company use Kubernetes in all our environments. as well as on our local Macbook using minikube.
We have many microservices and most of them are running JVM which require a large amount of memory. We started to face an issue that we cannot run our stack on minikube due to out of memory of the local machine.
We thought about multiple solutions:
the first was to create a k8s cloud development environment and when a developer is working on a single microservice on his local macbook he will redirect the outbound traffic into the cloud instead of the local minikube. but this solution will create new problems:
how a pod inside the cloud dev env will send data to the local developer machine? its not just a single request/response scenario
We have many developers, they can overlap each other with different versions of each service they need to be deploy on the cloud. (We can set each developer separate namespace but we will need a huge cluster to support it)
The second solution was maybe we should use a tools like skaffold or draft to deploy our current code into the cloud development environment. that will solve issue #1 but again we see problems:
Slow development cycle - building a java image and push to remote cloud and wait for init will take too much time for developer to work.
And we still facing issue #2
Antoher though was, kubernetes support multiple nodes, why won't we just add another node, a remote node that sit on the cloud, to our local minikube? The main issue is that minikube is a single node solution. Also, we didn't find any resources for it on the web.
Last thought was to connect minikube docker daemon to a remote machine. so we will use minikube on the local machine but the docker will run the containers on a remote cloud server. But no luck so far, minikube crush when we do this manipulate. and we didn't find any resources for it on the web as well.
Any thought how to solve our issue? Thank you!
I am trying to install kubernetes on Self-hosted production environment running on Ubuntu 16.04. I am not able to find any helpful guide to setup production grade kubernetes master and connect worked nodes to it.
any help is much appreciated.
you can use the kubespray to self Host production environment.
https://github.com/kubernetes-incubator/kubespray
Depends on what you understand by saying "self-host". The most people think it's about deploying kubernetes in the own environment.
If you want to compare different approaches to deploy k8s in a custom environment, refer to this article which covers a bunch of options suitable for that.
If you are interested in how to set up an HA Kubernetes cluster using kubeadm, refer to this article.
However, in kubernetes, there is a different definition of "self-hosted". It means running kubernetes itself as a workload in kubernetes. If you are interested in a real self-hosted approach (on a custom environment), refer to this article
Hope this helps
You can use typhoon which can be used to provision an HA kubernetes cluster.
Here is a sample configuration which I used to bring up my own home cluster.
A few advantages of typhoon are that you have the option of choosing your choice of a cloud provider for provisioning your infrastructure, which is done using terraform and the fact that it gives you upstream k8s is a big plus too.
Internally, it uses bootkube to bring up the temporary control plane, which would consist of
api-server
controller-manager
scheduler
and then when we have the temporary control plane object, we inject the objects to the API server to have our k8s cluster.
Have a look at this kubecon talk given by CoreOS which explains how this is working.