Although most of the content in this repository is still valid, it is now superseded by the BigBitBus Kubernetes Automation Toolkit. We encourage you to visit that github project for the latest code changes and documentation.

Welcome to the Kubernetes 101 for Python Programmers tutorial. This repository contains a sample Django application that can be deployed into a Kubernetes (abbreviated k8s) cluster using the included k8s spec files.

The application can be launched on your local laptop in development mode using a Minikube k8s cluster. We have also included Terraform scripts, here, that can help you spin up a k8s cluster in Amazon cloud EKS to highlight a few integration points between your k8s resident application and the underlying cloud provider.

You can download the slides accompanying the code.

1. Browse through the slides in this tutorial to get a condensed start to the concepts around Docker and k8s, and understanding how a Python/Django application can live inside k8s.
2. If you want to try out k8s without installing anything or creating a cloud provider account, spend time on the official Kubernetes tutorials; these include interactive tools to let you actually play with a k8s cluster without spinning one up on your own machine/cloud account:
   • Create a k8s cluster
   • Deploy a nodejs app
   • Other basic k8s operations such as scaling, rolling versions etc.
3. If you are ready to take the next step - and commit to installing a k8s-all-in-one VM on your PC, head over to the Minikube installation page to install the single-node k8s instance on your PC. This is useful for development work. You can then try to deploy the django application included in this tutorial on your local PC k8s cluster.
4. The next step is moving toward Kubernetes for production. We strongly recommend creating a cloud-provider-managed k8s cluster unless you have a strict requirement for an in-house production-grade do-it-yourself k8s cluster.
5. We have included Terraform scripts to create a Amazon cloud EKS cluster. You will need AWS credentials and a credit card - warning: running a k8s cluster is not cheap (see our slides for an example).

Here are links to key resources in this repository

• Slides for the tutorial.
• Demo video - Jenkins + Kubernetes demo to help you visualize a devops/infrastructure-as-code approach to Python development and operations-as-code using Kubernetes.
• Minikube installation instructions
• Docker setup and commands and the Dockerfile to create the django application container image from a standard base python image.
• Amazon AWS EKS k8s setup - you will need an AWS account (credit card required).
• Using the k8s cluster This is the meat of the tutorial - things to do with the k8s cluster.
• Amazon AWS RDS setup to create a simple postgres database instance - you will need an AWS account (credit card required). We separated the terraform scripts for EKS and RDS setup because you probably don't want to create and tear down your production database and EKS cluster at the same time!
• Sample django poll application, the settings.py may be of particular interest. The README describes the docker commands to package the application into a container.
• The Jenkins pipeline files contain shell scripts, executed in stages by Jenkins. This gives you ideas about how to use a CI/CD tool with Kuberetes workflows; see the demo video to see these Jenkins pipelines in action.

1. Why did you choose AWS EKS and not Google or Azure as the managed k8s cluster provider? And why not Flask instead of Django?

   K8s evolved from an internal project in Google, and it is widely believed that the Google cloud managed k8s product is the most polished and easy to use (as of late 2018). Google has also done a phenomenal job of creating documentation for Python developers using their k8s product (see: a Python Flask app on Google cloud k8s).

   We decided to go with AWS EKS for this tutorial to complement Google's K8s + Flask example. In addition, there is a large installed base of AWS users who may find this tutorial helpful.

2. What are the costs associated with running the AWS EKS cluster?

   You pay for the k8s management plane (~$0.20 per hour), the number of worker nodes (EC2 pricing), and the load balancer cost. If you use other services like RDS or S3, those are extra.

We welcome contributions through pull requests to keep this tutorial accurate and up-to-date.

This repository is licensed under the Apache License - see the LICENSE.md file for details

Copyright 2018 BigBitBus Inc. http://bigbitbus.com

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.