Locally install Kubernetes with essential components

This procedure is working on macOS indeed - and it's a great deal. Hope this work on others systems with some modification, but I can't guarantee.

I kept all YAML configuration files in the k8s directory. I will specify where they come from and what modification has been included when necessary.

Kubernetes

• I'm using Docker for Desktop which you can find obviously at https://www.docker.com/products/docker-desktop

  

• After installation, you can grapple basic information from your cluster:

% kubectl cluster-info

% kubectl get ns

• Or even:

% kubectl get all -A

Note the -A

Since Kube 1.14, we don't have to use the --all-namespaces anymore! So don't...

Kubernetes Dashboard

Dashboard is a web UI of k8s API and provide an easy way to visualize and debug things: https://github.com/kubernetes/dashboard

Installation

By default, Dashboard is protected by a token, and each time you'll access it, you'll be asked to provide one. It could really be annoying in the long run. Fortunately, Kubernetes Dashboard allows you to bypass the login page by adding --enable-skip-login to the configuration.

The repository configuration file is patched with this instruction (line 198)

Obviously this is only for local platform!

To deploy Dashboard - with no authentication - execute the following command:

% kubectl apply -f ./k8s/dashboard-v2.2.0-recommended.yaml

Then access your dashboard from your local workstation by creating a secure channel to your Kubernetes cluster. To do so, run the following command:

% kubectl proxy

The address is now:

http://localhost:8001/api/v1/namespaces/kubernetes-dashboard/services/https:kubernetes-dashboard:/proxy/

Don't forget to bookmark the URL!

You'll see this login page at first:

Just push the skip button to bypass authentication.

Metrics-Server

Metrics-Server is used to crop metrics from k8s components and expose them to k8s API: https://github.com/kubernetes-sigs/metrics-server

Metrics Server serves the goals of core metrics pipelines: CPU and RAM. It's a cluster level component which periodically scrapes metrics from all Kubernetes nodes served by Kubelet. When installed, Kubernetes Dashboard displays this metrics.

To allow Metrics Server to collect its data over https, the original script has been modified to accept insecure TLS connections by adding - --kubelet-insecure-tls at line 133.

Once again, don't do this on your public servers!

Apply the configuration by entering :

% kubectl apply -f k8s/metrics-server-components-v0.4.2.yaml

When reloading the Dashboard, you should now see CPU and Memory Usages 🌈

You can try the Pods section, that's my favorite!

Kube State Metrics

Unlike Metrics Server, Kube State Metrics is focused on generating numerous metrics from Kubernetes' object state (e.g. metrics based on deployments, replica sets, pods, etc.). It holds an entire snapshot of Kubernetes state in memory and generates new metrics based off of it.

Having Kube State Metrics enables access to these metrics from monitoring systems such as Prometheus.

To install Kube State Metrics, launch the following:

% kubectl apply -f k8s/kube-state-metrics-v2.0.0-rc.1.yaml

Prometheus

As specified in the documentation, Metrics Server is useful for:

• CPU/Memory based horizontal autoscaling
• Automatically adjusting/suggesting resources needed by containers

But when its comes to:

• Have an accurate source of resource usage metrics
• Manage Horizontal autoscaling based on other resources than CPU/Memory

You should check out full monitoring solutions like Prometheus https://prometheus.io.

In a few words, Prometheus is a monitoring and alerting system which:

• Collects data identified by a metric name
• Stores time-series in memory and on local disk for efficiency
• Allows notifications and alerting depending on data queries

Installation

Prometheus' maintainers provide binaries and Docker images for Prometheus components. With a bit of elbow grease, it is possible to create a k8s configuration file with everything we need:

• Access to resources we want to monitor at cluster level
• Role dedicated to Prometheus
• Prometheus executable configuration
• Docker image deployment
• Exposition through service
• And some specific paths due to Docker Desktop for Mac! 🥵

To run the Prometheus configuration, run the command:

% kubectl apply -f k8s/prometheus.yaml

You can now access Prometheus interface at: http://localhost:30000/... but wait and see!!

Grafana

Grafana https://grafana.com/grafana/ allows you to « query, visualize and alert on metrics through a powerful user interface » as the site puts.

In practice, you will develop your query in Prometheus, and when you're satisfied with, run on Grafana to monitor your service.

As you can see, the Grafana graphical interface offers numerous possibilities:

To install Grafana, run the command:

% kubectl apply -f k8s/grafana-datasource.yaml
% kubectl apply -f k8s/grafana.yaml

Grafana will be listening on http://localhost:3000. The default login is "admin" / "admin".

Note:

Configuring a dashboard in Grafana could be long, costly, and time-consuming. Collecting metrics depends on your host, VM/Virtualization Framework and the OS on your pod.

You own a Mac, you're running Docker Desktop and have followed this guide : you can import this [dashboard](./k8s/Docker Desktop Kubernetes All-in-one-1618321310777.json) right now to start monitoring your K8S cluster!