I have been working with kubernetes in a staging environment for a couple of month and want to switch to production, I came across a tool called Rancher almost 2 weeks ago and since then am going through their documents.
It was recommended by the developers and also in the community not to use rancher in production kubernete and preferably create a separated cluster for that and add an agent to your main production cluster from that one.
However in the latest stable version, there is actually an option you can tick to use the rancher only for local cluster so this question came to my mind that:
If the latest stable version of rancher is modified to be deployed on production cluster itself rather than having dedicated cluster? and if there is any security or restarting issues can happen that deletes all the configurations for other components on cluster
Note: on another staging environment I installed on the local clustor an instance of wordpress and ghost and both were working fine.
I still think the best option for you would be to have fully accessible own cluster and you wont be dependent to rancher cloud solutions. I am not saying Rancher is bad - no. Just If you are talking about PRODUCTION environment - my personal opinion cluster should be own. Sure arguable topic.
What I can mention also here - you can use any of Useful Interactive Terminal and Graphical UI Tools for Kubernetes . for example Octant
Octant is a browser-based UI aimed at application developers giving
them visibility into how their application is running. I also think
this tool can really benefit anyone using K8s, especially if you
forget the various options to kubectl to inspect your K8s Cluster
and/or workloads. Octant is also a VMware Open Source project and it
is supported on Windows, Mac and Linux (including ARM) and runs
locally on a system that has access to a K8S Cluster. After installing
Octant, just type octant and it will start listening on localhost:7777
and you just launch your web browser to access the UI.
Related
Given a container in a Azure container registry and a kubernetes cluster setup via the portal. Are there any visual tools that I can use so that I don't have to use the command line commands ,for things like add/edit the yaml file and launching the cluster?
For example I found this tool https://k8syaml.com/, but this is only one part of the process and it is also not aware of the existing infrastructure.
What are the visual tools to manage kubernetes end-to-end?
One tool I always work with when dealing with Kubernetes is Lens. Here is a video showing you what it can do. Best of all, it just needs the kube config file and so it is agnostic to where the Kubernetes cluster is (On-Prem, GKE, AKS, EKS)
kubectx for switching between contexts (clusters) & K9s is widely used that is something hybrid between being a cli and visual tool.
Octant is another option - https://github.com/vmware-tanzu/octant, it is similar to lens
I have production stage hosted in Google Kubernetes Engine with Kubernetes version 1.12.9-gke.15.
My team is planning to upgrade it to Kubernetes version 1.13.11-gke.5.
A capture of list of Kubernetes version
I have read some articles to upgrade Kubernetes. However, they use kubeadm not GKE.
How to update api versions list in Kubernetes here's a example that use GKE.
If you guys have experience in upgrading kubernetes cluster in GKE or even kubeadm. Please share what should i do before upgrading the version ?
Should i upgrade the version to 1.13.7-gke.24 and then to 1.13.9-gke.3 and so on ?
You first should check if you are not using any depreciated features. For example check the Changelogs for version 1.12 and 1.13 to make sure you won't loose any functionality after the upgrade.
You will have to remember that if you have just one master node you will loose access to if for few minutes while control plane is being updated. After master node is set then worker nodes will follow.
There is a great post about Kubernetes best practices: upgrading your clusters with zero downtime, which talks about location for nodes and a beta option being Regional
When creating your cluster, be sure to select the “regional” option:
And that’s it! Kubernetes Engine automatically creates your nodes and masters in three zones, with the masters behind a load-balanced IP address, so the Kubernetes API will continue to work during an upgrade.
And they explain how does Rolling update works and how to do them.
Also you might consider familiarizing yourself with documentation for Cluster upgrades, as it discusses how automatic and manual upgrades work on GKE.
As you can see from your current version 1.12.9-gke.15 you cannot upgrade to 1.14.6-gke.1. You will need to upgrade to 1.13.11-gke.5 and once this is done you will be able to upgrade to latest GKE version.
GCP Kubernetes is upgraded manually and generally does not require you to do much. But if you are you looking for manual upgrade options maybe this will help.
https://cloud.google.com/kubernetes-engine/docs/how-to/upgrading-a-cluster
A point worth mentioning is too, make sure you have persistence volumes for services that require to do so viz. like DB, etc And for these, you will have to back them up manually.
Let's say I have a flask app, a PostgreSQL, and a Redis app. what is the best practice way to develop those apps locally which then later be deployed to Kubernetes.
Because, I have tried to develop in minikube with ksync, but I get difficulties in getting detailed debug log information.
Any ideas?
What we do with our systems is that we develop and test them locally. I am not very knowledgeable with Flask and ksyncy, but say for example, you are using Lagom Microservices Framework in Java, you run you app locally using the SBT shell where you can view all your logs. We then automate the deployment using LightBend Orchestration.
When you then decide to test the app on Kubernetes, you can choose to use minikube, but you have to configure the logging properly. You can configure centralised logging for Kubernetes using the EFK stack. This will collect all the logs from the various components of your app and store them in Elastic Search. You can then view these logs using The Kibana Dashboard. You can do a lot with the dashboard, you can view logs for a given period, or search logs by k8s namespace, or by container.
There are multiple solutions for this (aka GitOps with Kubernetes):
Skaffold
Draft
Flux - IMO the most mature.
Ksonnet
GitKube
Argo - A bit more of a workflow engine.
Metaparticle - Deploy with actual code.
I think the solution is using skaffold
I'm new in kubernetes and I have some doubts about the installation of kubernetes on centos 7, I have read some documentation on some links:
https://kubernetes.io/docs/getting-started-guides/kubeadm/
https://kubernetes.io/docs/getting-started-guides/centos/centos_manual_config/
But I not undestanding which procedure to follow, on first link it show how to install it using kubeadm but at the end of the article on "Limitations" appear that this tool "is a work in progress and these limitations will be addressed in due course", on second link I need to have at least 2 machines, so my question is which is better to use if I will to install it like production.
Thanks in advance
kubeadm.
kubeadm now can support for multi masters, which is considerable for production.
The kubeadm also supplies a secure deployment. It automatically configs TLS settings or RBAC for the cluster, which is not included in the "manual installation page".
My advice: play kubeadm in your development environment first, so that you see how kubeadm deploys a Kubernetes cluster, many components can be deployed by Kubernetes itself. Then, you decide whether use it in your production.
You can follow up the repository made by one of our developer with an additional thing of Horizontal Pod autoscaling of stateless application.
https://github.com/vevsatechnologies/Install-Kubernetes-on-CentOs
I'm in the need of learning how to use Kubernetes. I've read the first sentences of a couple of introductory tutorials, and never have found one which explains me, step by step, how to build a simulated real world example on a single computer.
Is Kubernetes by nature so distributed that even the 101-level tutorials can only be performed on clusters?
Or can I learn (execute important examples) the important stuff there is to know by just using my Laptop without needing to use a stack of Raspberry Pi's, AWS or GCP?
The easiest might be minikube.
Minikube is a tool that makes it easy to run Kubernetes locally.
Minikube runs a single-node Kubernetes cluster inside a VM on your
laptop for users looking to try out Kubernetes or develop with it
day-to-day.
For a resource that explains how to use this, try this getting started guide. It runs through an entire example application using a local development environment.
If you are okay with using Google Cloud Platform (I think one gets free credits initially), there is hello-node.
If you want to run the latest and greatest (not necessary stable) and you're using Linux, is also possible to spin up a local cluster on Linux from a cloned copy of the kubernetes sources, using hack/local_up_cluster.sh.