Recently I have investigated container orchestration solutions on Azure. The main competitors in this area are Azure Kubernetes Service and Azure Service Fabric. Both have their place, advantages and downsides. This is a small smackdown of those two based on my research and experience with Kubernetes. Unfortunately I have not had practical experience with Service Fabric so far. Please let me know your thoughts in the comments section. Let’s start then.
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Introduction I have been playing a bit more with Python recently. I wanted to test out some algorithms using this awesome tool called Project Jupyter. I also did not want to drain battery of my laptop while doing this, as I have a powerful machine at home running single node Kubernetes cluster.
If you are interested in learning how to install such single-node-cluster on your old desktop, you can Find it here.
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In this blog post I will show you how to get started with grafana custom dashboard for Kubernetes. We will also be learning basics of Prometheus query language. Both of those tools are very useful in everyday of cluster admin’s and user’s life.
Why you should learn Prometheus query language Grafana and Prometheus are very powerful tools that enable you to monitor almost anything about your Kubernetes cluster. They are, though, difficult to master.
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These are a few quirks you might encounter when you deploy Kubernetes using acs-engine onto Azure cloud with pre-defined custom vNet. Deploying custom vNet is a common scenario in most of the use-cases. You usually want to run Kubernetes along other services on your Azure cloud, such as legacy applications. This article is intended to provide you with some guidance on how to avoid the same issues I have experienced during acs-engine deployments.
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Summary
Recently I've worked on deploying Kubernetes clusters using Azure acs-engine as a part of our automation effort at the firm. It is a very useful tool that generates ARM (Azure Resource Manager) templates with ready to-use deployments of Virtual Machines and Kubernetes components on them. It also supports other container orchestrators, such as DC/OS or Swar. However, I will focus only on Kubernetes in this article as this is the only ochestrator I use.
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Summary
I've been fighting for the whole day with Prometheus and Grafana. It turns out the documentation about Prometheus and Grafa get outdated very quickly. Let me shed some light on both the problem and the solution.
Intro
I've been trying very hard to setup perfect grafana/prometheus configuration that I can apply to all of my clusters. This requires me to configure both of those services from YAML files, so that both prometheus and grafana start with prope configuration in place that are ready to be used.
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My Kubernetes cluster is down
My single-node baremetal cluster using kubeadm and on calico networking plugin is down (link to the article here). The machine won't startup anymore and there is very mysterius error from cephlib reporting that it was unable to start. Few days ago I was playing with rook (https://github.com/rook/rook). Rook uses ceph to give you easy to use persistent volume experience.
Everything was fine at this point until I started doing research on advanced Prometheus configuration.
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Summary
We will deploy rook cluster storage service into the baremetal cluster.
Prerequisites
You should have a Baremetal Kubernetes cluster at least version 1.8. If you don't, I recommend taking a look at:
Home Kubernetes cluster in 15 minutes with kubeadm and calico
According to rook's documentation you should also have at least 5GB of disk space on the drive you want to use for storage.
Let's do it
First we need to prepare the baremetal machine for rook's persistent volumes:
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