I know nothing (or very little) about Kubernetes. It is high time I do something to learn more about it. Kubernetes is a powerful tool for managing containerized applications, and it’s becoming a must-have skill for developers and DevOps engineers. In this blog, I’ll share my journey as a beginner exploring Kubernetes, from running a simple Grafana pod to understanding the basics of kubectl. Let’s dive in!
What is Kubernetes?
Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. If you want to run your containerized applications, you probably want to learn Kubernetes.
I have worked at least two companies so far in my career that have made use of Kubernetes to run their microservice architecture. Let’s take a look at how to use it.
Why Learn Kubernetes?
Kubernetes is widely used in modern software development for:
- Microservices: Manage and scale multiple services independently.
- CI/CD Pipelines: Automate deployments and rollbacks.
- Scalability: Handle traffic spikes by scaling pods up or down.
Docker Desktop
Docker Desktop is a tool for running containers, but it also allows running of Kubernetes.
I am not going to talk through installing docker desktop and getting a Kubernetes cluster set up, for that check out the documentation however I found it very straightforward.
kubectl
kubectl is the command line tool for doing everything with Kubernetes.
kubectl version
This prints out basic version information, if this works you know Kubernetes must be working.
kubectl config get-contexts
kubectl config use-context docker-desktop
This command allows you to switch contexts, to use with docker desktop you want to use the docker-desktop context. At work we have dev and test contexts that can be selected in a similar way.
- Context: A Kubernetes context is a set of access parameters for a cluster. It allows you to switch between different clusters or environments (e.g., dev, test, production).
kubectl get all
This gives you a list of everything that is running in the default namespace, pods, services, deployments etc For a complete list, you can add the –all-namespaces flag.
- Namespace: A namespace is a way to organize resources in a Kubernetes cluster, providing isolation between different projects or teams.
Hello World
Now what is the equivalent of “Hello World” for Kubernetes? I think getting a container to run in Kubernetes is a pretty good test.
Open up VS Code and create a yaml file called grafana.yaml
apiVersion: v1 # Specifies the API version for the resource
kind: Pod # Defines the resource type as a Pod
metadata:
name: grafana # The name of the pod
spec:
containers:
- name: grafana # The name of the container
image: grafana/grafana:12.0.0 # The container image to use
ports:
- containerPort: 3000 # The port exposed by the container
This file uses the Grafana container image, which I am familiar with (see my previous blog posts ) It’s default port is 3000 which you can see is defined in this file.
kubectl apply -f grafana.yaml
This deploys a pod, using the above yaml file.
You can run the following to find out more about the pod.
kubectl describe pod grafana
From what I have discovered so far, Kubernetes runs in its own network. So going to localhost:3000 won’t work. But you can use port forward to get round this issue.
- Port-Forwarding: This allows you to access a pod’s service on your local machine by forwarding a port from the pod to your localhost.
kubectl port-forward pod/grafana 3000:3000
Now if I try http://localhost:3000/login I see the login page for the Grafana container. A pretty good first test of using Kubernetes.
Whats next?
I want to replace my local deployment of containers that is currently using a docker compose file with Kubernetes. I also want to learn more about Helm charts as I believe these are an excellent way of packaging up changes to Kubernetes.
Have you tried running a pod in Kubernetes? What challenges did you face, and how did you overcome them? Share your thoughts in the comments below!
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