Develop and deploy Python REST API with Kubernetes, Docker in SAP BTP Kyma Environment

[SaiNithesh_Gajula]

Hi Everyone,

Hope everyone is doing great.

In this blog we will learn how to create small Python REST API and deploy the same to SAP BTP, Kyma Environment using Kubernetes, and Docker containerized.

There are 2 different options so far I have learned.

1. Using GitHub Package Registry


2. Using Docker

Pre-requisites

1. Create SAP BTP Trial/Tier Account


2. Enable SAP BTP Kyma Environment


3. Git Hub Account /Docker Account – Will be used for container registry.


4. Visual Studio (VS) Code Setup or Any IDE of your choice


5. Python Setup


6. Install & Set up Kubernetes


7. Docker Desktop Set up for Mac or Windows


8. Docker Hub (Optional)

Step 1: Now let us start creating our python application. Create a new folder, here I am naming it as py-flask-kubernetes and open the same folder in the VS Code and start running docker locally.

Step 2: Now, create Python file app.py with below code.

from flask import Flask, jsonify

import time



PORT = 8080



app = Flask(__name__)





@app.route("/")

def root():

    return jsonify({"App Status" : "Running"})



@app.route("/getTime")

def getTime():

    seconds = time.time()

    local_time = time.localtime(seconds)

    return jsonify({"Year" : local_time.tm_year,"Seconds" : seconds, "Local Time" : local_time})





if __name__ == "__main__":

    app.run(debug=True, host="0.0.0.0", port=PORT)

 

Step 3: Test the python app locally using python3 app.py

Step 4: Create requirements.txt which holds the information about the dependency libraries, modules, and packages for the project.

flask

Step 5: To containerize the application lets us create Dockerfile from which generates docker image for this application.

FROM python:3.7

RUN mkdir /app

WORKDIR /app

ADD . /app/

RUN pip install -r requirements.txt

CMD ["python", "/app/app.py"]

Step 6: (Consider if you want to publish to GitHub Package Registry) Now lets us create Personal Access Token (PAT) to login to Git Account

Login to Git Hub Account => Go to Settings à Developer Settings => Personal Access Tokens (PAT).

Click on Generate new token.

Provide the token name and check repo and packages access and click on Generate Token below and token will get generated. Copy and save this token so that we will be using this in next steps

Step 7: (Consider if you want to publish to GitHub Package Registry) git login

git config --global user.name <<GitHubUserName>>

git config --global user.email <<GitHubEmailID>>

git config --global user.password <<GitHubAccessToken>>

 

Step 8: Now let’s create Kubernetes Secret Key in the SAP BTP, Kyma Environment. Make sure you have configured local workspace to BTP Kyma Environment while Kubernetes setup. Here I am going with default namespace

kubectl config set-context --current --namespace=<insert-namespace-name-here>

kubectl config view --minify | grep namespace:

GitHub Registry

kubectl create secret docker-registry py-regcred\

--namespace default \

--docker-server=ghcr.io \

--docker-email=<<GitHubEmailID>> \

--docker-username=<<GitHubUserName>> \

--docker-password=<<GitHubAccessToken>>

 

Docker Registry

kubectl create secret docker-registry regcred \

--namespace default \

--docker-server=docker.io \

--docker-email=<<DockerEmailID>> \

--docker-username=<<DockerUserName>> \

--docker-password=<<DockerPassword>>

On successful creation we can see secret key got created in the BTP Kyma Environment. To check it, open Kyma Dashboard è choose default namespace on the top right => Configuration => Secrets

Step 9: Now will generate the docker image for this app.

GitHub Registry

docker build . --tag ghcr.io/<<GITHubUserID>>/py-flask-kubernetes:latest

docker build . --tag ghcr.io/sainithesh/py-flask-kubernetes:latest

docker run ghcr.io/sainithesh/py-flask-kubernetes:latest

Docker Registry

docker build . --tag docker.io/sainithesh/py-flask-kubernetes:latest

docker run docker.io/sainithesh21/py-flask-kubernetes:latest

 

Step 10: Publish to Package Registry

GitHub Registry

docker push ghcr.io/sainithesh/py-flask-kubernetes:latest

Docker Registry

docker push docker.io/sainithesh21/py-flask-kubernetes:latest

Step 11: Now we want to deploy this containerized application which is there in the image. Create deployment.yaml with below code.

Here we must use ghcr.io if you deploy image to GitHub or use docker.io and append with image path.

image: ghcr.io/sainithesh/py-flask-kubernetes:latest

Or

image: docker.io/sainithesh/py-flask-kubernetes:latest

Service kind: Act as load balancer

Deployment kind: Act as application

API Rules: which helps in adding rules to the applications like restricting methods (GET, POST, PUT, etc), authentications and other rules.

apiVersion: apps/v1

kind: Deployment

metadata:

  name: py-flask-kubernetes

  labels:

    app: py-flask-kubernetes

spec:

  selector:

    matchLabels:

      app: py-flask-kubernetes

  replicas: 1

  template:

    metadata:

      labels:

        app: py-flask-kubernetes

    spec:

      containers:

      - name: py-flask-kubernetes

        image: ghcr.io/sainithesh/py-flask-kubernetes:latest 

        imagePullPolicy: Always

        ports:

        - containerPort: 8080

        resources:

            limits:

              ephemeral-storage: 256M

              memory: 256M

              cpu: 100m

            requests:

              ephemeral-storage: 256M

              memory: 256M

              cpu: 100m

      imagePullSecrets:

      - name: py-regcred

status: {}

        

---

apiVersion: v1

kind: Service

metadata:

  name: py-flask-kubernetes

spec:

  selector:

    app: py-flask-kubernetes

  ports:

  - protocol: "TCP"

    port: 8081

    targetPort: 8080





---

apiVersion: gateway.kyma-project.io/v1alpha1

kind: APIRule

metadata:

  name: py-flask-kubernetes

spec:

  gateway: kyma-gateway.kyma-system.svc.cluster.local

  service:

    name: py-flask-kubernetes

    port: 8081

    host: py-flask-kubernetes

  rules:

    - path: /.*

      methods: ["GET"]

      accessStrategies:

        - handler: noop

          config: {}

 

Step 12: Deploy to Kyma Environment

kubectl apply -n default -f deployment.yaml

 

Step 13: Manual Deployment to Kyma Environment

Deployment

Workloads => Deployments => Create Deployment

Go to YAML tab and copy the deployment Code and click on Create.

Once Deployment object is created, we can see it running as below

Service: To create service for an application

Discovery and Network => Services => Create Service

API Rules:

Step 14: Pods, here we can see multiple instances for the same application which depends on the replica attribute value which is part of Service. Multiple instances here helps application to keep running even if one of the instance breaks down or crash because of any reason like heavy traffic or others.

Step 15: Service Details, here we can see the application url.

Step 16: (Consider if you published image to GitHub Registry Package) Let us push the code to the Git repo so that we can update image using GitHub Actions whenever we push new build to Git repo.

Let us create workflow file (here docker_build_and_push.yml) in the Git repo under github/workflows folder. We need to collaborate package and repo to make workflow enabled.

name: Build and Push Docker Imag



on: [push]



env:

  REGISTRY: ghcr.io

  IMAGE_NAME: ${{ github.repository }}



jobs:

  build_and_push:

    runs-on: ubuntu-latest

    permissions:

      contents: read

      packages: write

    steps:

    - uses: actions/checkout@v3



   

    - name: Set up QEMU

      uses: docker/setup-qemu-action@v2



    - name: Set up Docker Buildx

      uses: docker/setup-buildx-action@v2

      with:

        buildkitd-flags: --debug



    - name: Login to GitHub Container Registry

      uses: docker/login-action@v2

      with:

        registry: ${{ env.REGISTRY }}

        username: ${{ github.actor }}

        password: ${{ secrets.PKG_SECRET }}



    - name: Extract metadata (tags, labels) for Docker

      id: meta

      uses: docker/metadata-action@v4

      with:

       images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}



    - name: Build the py-flask-kubernetes Docker image

      uses: docker/build-push-action@v3.0.0

      with:

       context: .

       push: true

       tags: ${{ steps.meta.outputs.tags }}

       labels: ${{ steps.meta.outputs.labels }}

 

Step 17:  We can see all the GitHub Actions under Action Tab. On successful completion of workflow on every push to Git repo, new docker image will get updated.

Hope this blog helps you. Feel free to add comment and suggestions.

Git Repo: https://github.com/SaiNithesh/py-flask-kubernetes/

 

Regards,

Sai Nithesh