in order to work with your django application with k8s you need to prepare your environment for development, such as installing docker and minikube for start. so follow along the instructions and make everything.
You'll need to have Docker installed. It's available on Windows, macOS and most distros of Linux.
System requirements To install Docker Desktop successfully, your Linux host must meet the following general requirements:
- 64-bit kernel and CPU support for virtualization.
- KVM virtualization support. Follow the KVM virtualization support instructions to check if the KVM kernel modules are enabled and how to provide access to the kvm device.
- QEMU must be version 5.2 or newer. We recommend upgrading to the latest version.
- systemd init system.
- Gnome, KDE, or MATE Desktop environment.
- For many Linux distros, the Gnome environment does not support tray icons. To add support for tray icons, you need to install a Gnome extension. For example, AppIndicator.
- At least 4 GB of RAM.
- Enable configuring ID mapping in user namespaces, see File sharing.
Docker Desktop for Linux runs a Virtual Machine (VM). For more information on why, see Why Docker Desktop for Linux runs a VM.
If you're using Windows, it will be expected that you have to install wsl too. WSL or WSL 2.
That's because we're going to be running shell commands. You can always modify these commands for PowerShell if you want.
in order to run the kubernetes cluster you need to install one of the following providers for dev environment
docker desktop already has support for windows,linux and mac so its already there all you have to do is to go to docker desktop settings and enable kubernetes, and wait till installation is completed. after that you will see another icon appears beside docker and shows the status of the kubernetes too.
Minikube is Kubernetes tool. It allows you to run Kubernetes locally on your computer. It runs as a single-node Kubernetes cluster within your local computer, making it easy to develop the Kubernetes app. you can follow the instructions provided here to install it based on your os.
https://minikube.sigs.k8s.io/docs/start/
What you’ll need
- 2 CPUs or more
- 2GB of free memory
- 20GB of free disk space
- Internet connection
- Container or virtual machine manager, such as: Docker, QEMU, Hyperkit, Hyper-V, KVM, Parallels, Podman, VirtualBox, or VMware Fusion/Workstation
after installation you have to run the minikube and set it up for usage, so in order to do that just run the following command:
minikube startNote: if you want to change the default driver for minikube you can pass the argument like this:
minikube start --driver=virtualboxwhich will setup minikube with virtualbox as the default driver. for more information see the documentation in here: https://minikube.sigs.k8s.io/docs/drivers/. by default we will use docker.
when its done you will see the details of the steps and informations.
The Kubernetes command-line tool, kubectl, allows you to run commands against Kubernetes clusters. You can use kubectl to deploy applications, inspect and manage cluster resources, and view logs. For more information including a complete list of kubectl operations, see the kubectl reference documentation provided here:
https://kubernetes.io/docs/reference/kubectl/
for installing kubectl, you can head to the link down below and choose the right os and start the installation steps:
https://kubernetes.io/docs/tasks/tools/
Note: for windows users after downloading the file you have to put it in a folder inside C directory and then just add the path to environment variables of the system. then you can access and test it with the following command: shell kubectl version --client
Once you have the PATH ready, run the following command to check if your set Kubectl is ready to execute Kubernetes commands:
kubectl cluster-infofor deployment purposes you need to build the docker image, so it can be used inside the k8s deployment as a refrence. there are two options here:
- build locally and push to docker hub - set
$REPOSITORY_URLequal to your dockerhub username
Run REPOSITORY_URL="petecheslock" ./create-push-docker.sh
to push the containers to dockerhub
- build locally and use it
For local testing, you can run these commands to build the containers.
for building django app:
docker build -t django_app -f ./dockerfiles/dev/django/Dockerfile .and for nginx app:
docker build -t nginx_app -f ./dockerfiles/dev/nginx/Dockerfile .Mount the shared directory
minikube mount tmp/appmap:/appmap-host Apply the k8s configs
kubectl apply -R -f ./k8s$ kubectl get all
NAME READY STATUS RESTARTS AGE
pod/django-5b74bd444-mskdm 1/1 Running 0 2m43s
pod/my-nginx-c7bb68546-64q56 1/1 Running 0 25s
pod/my-nginx-c7bb68546-qrkl2 1/1 Running 0 25s
pod/postgres-6bdb7d69c-2wn9v 1/1 Running 0 7m3s
pod/redis-67b95b7577-2jwv8 1/1 Running 0 4m1s
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/django ClusterIP 10.110.233.36 <none> 8000/TCP 2m21s
service/kubernetes ClusterIP 10.96.0.1 <none> 443/TCP 4d21h
service/nginx-loadbalancer LoadBalancer 10.109.224.172 localhost 80:30362/TCP 20s
service/postgres ClusterIP 10.97.134.246 <none> 5432/TCP 6m58s
service/redis ClusterIP 10.98.178.118 <none> 6379/TCP 3m46s
NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/django 1/1 1 1 2m43s
deployment.apps/my-nginx 2/2 2 2 25s
deployment.apps/postgres 1/1 1 1 7m3s
deployment.apps/redis 1/1 1 1 4m1s
NAME DESIRED CURRENT READY AGE
replicaset.apps/django-5b74bd444 1 1 1 2m43s
replicaset.apps/my-nginx-c7bb68546 2 2 2 25s
replicaset.apps/postgres-6bdb7d69c 1 1 1 7m3s
replicaset.apps/redis-67b95b7577 1 1 1 4m1sRun the following to tunnel to the LB
minikube tunnelopen http://localhost:8888MIT.
Feel free to let me know if something needs to be fixed. or even any features seems to be needed in this repo.