yatharth0045/test-docker-image-autobuild repository overview

⁠Operationalize ML Microservice API

⁠A Udacity Project for containerizing a ML Microservice written in python and running it over kubernetes

⁠Steps to be followed

⁠1. Clone this repo

git clone https://github.com/Yatharth0045/operationalize-ml-microservice-api.git

⁠2. Run Make rules

1. This will create and activate the virtual envrironment

make setup

1. This will install the dependencies mentioned in the requirements.txt

make install

⁠3. Install other libraries

⁠Note: These commands are for ubuntu amd64

1. Install docker

sudo apt-get update && sudo apt-get install apt-transport-https ca-certificates curl gnupg-agent software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo add-apt-repository "deb [arch=arm64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"
sudo docker --version

For any other Linux distribution or OS, refer to docker docs⁠

1. Install Hadolint

sudo wget -O /bin/hadolint https://github.com/hadolint/hadolint/releases/download/v1.16.3/hadolint-Linux-x86_64 && sudo chmod +x /bin/hadolint
hadolint --version

For any other distribution or OS, refer to hadolint README⁠

1. Install Minikube (Kubernetes)

Refer to official Kubernetes documentation⁠ for install minikube and kubectl. After install, verify the version using minikube version

⁠4. Verify Dockerfile lint

hadolint Dockerfile

⁠Running the application

⁠1. Run application over docker

./run_docker.sh
./make_prediction.sh

⁠2. Run application over minikube

minikube start
./run_kubernetes.sh
./make_prediction.sh