In this article we will build a Python FastAPI application with a single API which will return the sentiment (Postivie, Negative or Neutral) of the text given as input using Vader Sentiment Analysis. We will deploy the service in Kubernetes locally using minikube. If you are new to FastAPI please refer here. If you want to install minikube refer here.

Note: Installing minikube is out-of-scope of this article.

Build Sentiment service API

This application contains a single API which will return the sentiment of the text provided as input. The other API we have is to check the health of the application. You can download the complete source code of this application from my Github repo. Run the following commands to execute the application locally:

$ git clone
$ cd  vader-sentiment-service
$ python3 -m venv .venv --prompt ss
$ source .venv/bin/activate
$ pip install pip --upgrade
$ pip install -r requirements.txt
$ uvicorn service.main:app --reload

Go to to see the Swagger API and try the sentiment API.

Vader sentiment service

Build the Docker in minikube

There are multiple ways to push the docker image into minikube. Refer this link for more information. I have used the first one Pushing directly to the in-cluster Docker daemon (docker-env). It worked for me. I built my docker images as:

$ cd vader-sentiment-service
$ docker build -t vader-sentiment .

The docker image build directly in to minikube.

Run our application

Now it’s time to create deployment and service to run our docker in minikube. We will keep it simple for this article. Will explore more options on scaling the application in future articles. The api.yaml file in the Github repo contain service and deployment template.

Service template

# vader-sentiment LoadBalancer Service
# Enables the pods in a deployment to be accessible from outside the cluster
apiVersion: v1
kind: Service
  name: vader-sentiment-svc
    app: vader-sentiment
    - protocol: "TCP"
      port: 8080
      targetPort: 8080
  type: LoadBalancer

Deployment template - we will have only one replica for now.

# vader-sentiment Deployment
# Defines the deployment of the app running in a pod on any worker node
apiVersion: apps/v1
kind: Deployment
  name: vader-sentiment
    app: vader-sentiment
  replicas: 1
      app: vader-sentiment
        app: vader-sentiment
        - name: vader-sentiment
          image: vader-sentiment:latest
            - containerPort: 8080
          imagePullPolicy: IfNotPresent

Use the below command to deploy service:

$ kubectl apply -f api.yaml 
service/vader-sentiment-svc created
deployment.apps/vader-sentiment created
$ kubectl get pods
NAME                              READY   STATUS    RESTARTS   AGE
vader-sentiment-8f5bfc566-wk9p9   1/1     Running   0          2s

Make sure you have the status running as shown above. Now we want the public IP so that we can test our API. Run the following command to get it:

$ kubectl get svc vader-sentiment-svc
NAME                  TYPE           CLUSTER-IP      EXTERNAL-IP   PORT(S)          AGE
vader-sentiment-svc   LoadBalancer   <pending>     8080:30498/TCP   25s

The EXTERNAL-IP is showing as <pending>. Open another terminal and run the command:

$ minikube tunnel
	machine: minikube
	pid: 1612721
	route: ->
	minikube: Running
	services: [vader-sentiment-svc]
		minikube: no errors
		router: no errors
		loadbalancer emulator: no errors

Now again run the get svc command:

$ kubectl get svc vader-sentiment-svc
NAME                  TYPE           CLUSTER-IP      EXTERNAL-IP     PORT(S)          AGE
vader-sentiment-svc   LoadBalancer   8080:30498/TCP   22m

Now you see the EXTERNAL-IP. Ofcourse, the CLUSTER-IP and EXTERNAL-IP are same as we are running Kubernetes locally. Our application is deployed in minikube successfully.

Test our application

I use cURL command to test my APIs. You can use postman as well. To test the sentiment API use the following cURL command:

curl -X 'POST' \
  '' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
  "sentence": "The ice cream tastes delicious"

You will get the following response:

  "sentence": "The ice cream tastes delicious",
  "sentiment": "Positive"


We have learnt how to deploy a simple service built with Python FastAPI into a Kubernetes (minikube) cluster using Docker. In future articles we will see how to deploy the same service on to public clouds like AWS, GCP and Azure. Thank you for reading.