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

2. 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

2. 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

3. 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