Deploy 2 FastAPI microservice in GKE with Ingress Controller and expose them using GCP API Gateway

Deploy 2 FastAPI microservice in GKE with Ingress Controller and expose them using GCP API Gateway

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Aman Ulla

Table of contents

Deploy 2 FastAPI microservice in GKE with Ingress Controller and expose them using GCP API Gateway

1 (1).png

In this POC we will deploy two different Service in GKE (Google Kubernetes Service) and route it using api gateway and ingress controller

GCP Services used

  • GKE
  • API Gateway

Steps Summary

  • Create two sample service
  • Build Docker Image for both the service
  • Push the Docker image to dockerhub
  • Create deployment.yaml file for GKE Service
  • Create ingress.yaml file for ingress rules for route mapping to the service
  • Create gateway.yaml file for routes rules and services for each route

Step 1 Create two sample service using FlaskAPI In your care we created two different services namely notes and products notes service First create or install required packages from requirements.txt

pip install -r requirements.txt

requirements.txt

Flask
gunicorn

main.py

from flask import Flask,jsonify,request
import json
app = Flask(__name__)


data = [{
    "id":1,
    "notes":"sample notes",
    "completed":"true",
    }]


@app.route("/",methods=['GET'])
def health():
    return jsonify("healthy")

@app.route('/notes',methods = ['GET'])
def get_notes():
    return jsonify(data)

@app.route("/notes",methods=["POST"])
def add_notes():
    record = request.get_json()
    data.append({"id":record["id"],"notes":record["notes"],"completed":record["completed"]})
    return jsonify("data added success")

@app.route("/notes/<note_id>",methods=["GET"])
def get_note_by_id(note_id):
    print(note_id)
    for d in data:
        if d["id"] == int(note_id):
            return jsonify(d)
    return jsonify("no such notes found with id")

if __name__ == '__main__':
    app.run(host="0.0.0.0")

Once the required packages and code is ready, run it locally and test

python main.py

product service First create or install required packages from requirements.txt

pip install -r requirements.txt

requirements.txt

Flask
gunicorn

main.py

from flask import Flask,jsonify,request
import json
app = Flask(__name__)


data = [{
    "id":1,
    "product":"laptop",
    }]


@app.route("/",methods=['GET'])
def health():
    return jsonify("healthy")

@app.route('/products',methods = ['GET'])
def get_notes():
    return jsonify(data)

@app.route("/products",methods=["POST"])
def add_notes():
    record = request.get_json()
    data.append({"id":record["id"],"product":record["product"]})
    return jsonify("data added success")

@app.route("/products/<note_id>",methods=["GET"])
def get_note_by_id(note_id):
    print(note_id)
    for d in data:
        if d["id"] == int(note_id):
            return jsonify(d)
    return jsonify("no such products found with id")

if __name__ == '__main__':
    app.run(host="0.0.0.0")

Once the required packages and code is ready, run it locally and test

python main.py

Step 2 notes-service Create Docker file and build the docker image Place all the codes and files in the following structure

notes-service/
    --Dockerfile
    --requirements.txt
    --app/
       --main.py

2.png Create a docker file and place the below code Dockerfile

# Select Image
FROM python:3.7.12-slim

# mode to code dir
WORKDIR /code

# copy the requirement.txt file
COPY ./requirements.txt /code/requirements.txt

# run the pip install command
RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt

# copy the app dir 
COPY ./app /code/app

# expose the port 
EXPOSE 5000

# run the service using uvicorn
CMD ["python","app/main.py"]

to build the docker image run the command , make sure to be in the same directory as the Dockerfile

sudo docker build -t notes:0.1 .

check if the image is build

sudo docker images

to run the docker image and test

sudo docker run -d -p 5000:5000 notes:0.1

a container will be created and to check and list the container id, run the command

sudo docker ps

then to test the api run the curl command

curl -v http://0.0.0.0/notes

the curl will respond back with 

{
            "id":1,
            "note":"sample note",
            "completed":"true"
 }

if you get similar response then the docker image is built and running successfully

product-service Create Docker file and build the docker image Place all the codes and files in the following structure

products-service/
    --Dockerfile
    --requirements.txt
    --app/
       --main.py

3.png Create a docker file and place the below code Dockerfile

# Select Image
FROM python:3.7.12-slim

# mode to code dir
WORKDIR /code

# copy the requirement.txt file
COPY ./requirements.txt /code/requirements.txt

# run the pip install command
RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt

# copy the app dir 
COPY ./app /code/app

# expose the port 
EXPOSE 5000

# run the service using uvicorn
CMD ["python","app/main.py"]

to build the docker image run the command , make sure to be in the same directory as the Dockerfile

sudo docker build -t products:0.1 .

check if the image is build

sudo docker images

to run the docker image and test

sudo docker run -d -p 5000:5000 products:0.1

a container will be created and to check and list the container id, run the command

sudo docker ps

then to test the api run the curl command

curl -v http://0.0.0.0/products

the curl will respond back with 

{
            "id":1,
            "note":"sample note",
            "completed":"true"
 }

if you get similar response then the docker image is built and running successfully

Step 3 Deploy Both the services to DockerHub to push first you should have a account in dockerhub is not use the link and create an account hub.docker.com notes-service create a new public repository named notes in my case the repo name is : amanulla1997/notes:0.1

to push docker image to dockerhub run the command

# sudo docker tag local-image:tag docker-repo/repo-name:tag
sudo docker tag notes:0.1 amanulla1997/notes:0.1

# sudo docker push docker-repo/repo-name:tag
sudo docker push amanulla1997/notes:0.1

product-service create a new public repository named products in my case the repo name is : amanulla1997/products:0.1

to push docker image to dockerhub run the command

# sudo docker tag local-image:tag docker-repo/repo-name:tag
sudo docker tag products:0.1 amanulla1997/products:0.1

# sudo docker push docker-repo/repo-name:tag
sudo docker push amanulla1997/products:0.1

Screenshot of DockerHub Repo

4.png

step 4 Create deployment.yaml file for each service and deploy it as a GKE Service notes-service

apiVersion: apps/v1
kind: Deployment
metadata:
  creationTimestamp: null
  labels:
    app: notes-gateway
  name: notes-gateway
spec:
  replicas: 1
  selector:
    matchLabels:
      app: notes-gateway
  strategy: {}
  template:
    metadata:
      creationTimestamp: null
      labels:
        app: notes-gateway
    spec:
      containers:
      - name: sample-notes
        image: amanulla1997/notes:0.1
---
apiVersion: v1
kind: Service
metadata:
  name: gateway-notes-service
spec:
  ports:
  - port: 80
    targetPort: 5000
    protocol: TCP
    name: http
  selector:
    app: notes-gateway
  type: NodePort

deploy the notes-service-deployment.yaml file

kubectl apply -f notes-service-deployment.yaml

products-service

apiVersion: apps/v1
kind: Deployment
metadata:
  creationTimestamp: null
  labels:
    app: products-gateway
  name: products-gateway
spec:
  replicas: 1
  selector:
    matchLabels:
      app: products-gateway
  strategy: {}
  template:
    metadata:
      creationTimestamp: null
      labels:
        app: products-gateway
    spec:
      containers:
      - name: sample-products
        image: amanulla1997/products:0.1
---
apiVersion: v1
kind: Service
metadata:
  name: gateway-products-service
spec:
  ports:
  - port: 80
    targetPort: 5000
    protocol: TCP
    name: http
  selector:
    app: products-gateway
  type: NodePort

deploy the products-service-deployment.yaml file

kubectl apply -f products-service-deployment.yaml

step 5 Create and deploy ingress yaml file maping the routes with their respective services ingress.yaml

apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: my-ingress
spec:
  rules:
  - http:
      paths:
      - pathType: Prefix
        path: /products
        backend:
          service:
            name: gateway-products-service
            port:
              number: 80
      - pathType: Prefix
        path: /notes
        backend:
          service:
            name: gateway-notes-service
            port:
              number: 80

Deploy the ingress.yaml file

kubectl apply -f ingress.yaml

step 6

Create one single api gateway openAPI swagger yaml file for both the services with all the routes and their mapping with the ingress url/load balancer gateway.yaml

swagger: "2.0"
info:
  description: "API Gatepoints"
  title: "Endpoints for Microservices"
  version: "1.0.0"
consumes:
  - "application/json"
produces:
  - "application/json"
schemes:
  - "http"  
paths:
  "/api/notesservice/notes":
    get:
      description: "Returns the notes information."
      operationId: "get_all_notes"
      x-google-backend:
        address: http://34.110.194.28.nip.io/notes
      produces:
        - "application/json"
      responses:
        200:
          description: "Notes info."
          schema:
            $ref: "#/definitions/notesResponse"
      security:
        - api_key: []
          google_jwt: []
    post:
      description: "Returns the notes information."
      operationId: "create_note"
      x-google-backend:
        address: http://34.110.194.28.nip.io/notes
      produces:
        - "application/json"
      responses:
        200:
          description: "Notes info."
          schema:
            $ref: "#/definitions/notesResponse"
      security:
        - api_key: []
          google_jwt: []
  "/api/productsservice/products":
    get:
      description: "Returns the products information."
      operationId: "get_all_products"
      x-google-backend:
        address: http://34.110.194.28.nip.io/products
      produces:
        - "application/json"
      responses:
        200:
          description: "products info."
          schema:
            $ref: "#/definitions/productsResponse"
      security:
        - api_key: []
          google_jwt: []
    post:
      description: "Returns the products information."
      operationId: "create_Product"
      x-google-backend:
        address: http://34.110.194.28.nip.io/products
      produces:
        - "application/json"
      responses:
        200:
          description: "Products info."
          schema:
            $ref: "#/definitions/productsResponse"
      security:
        - api_key: []
          google_jwt: []

definitions:
  notesResponse:
    type: "object"
    properties:
      id:
        title: Id
        type: integer
      text:
        title: Text
        type: string
      completed:
        title: Completed
        type: string
  productsResponse:
    type: "object"
    properties:
      id:
        title: Id
        type: integer
      product:
        title: Product
        type: string

To deploy the api gateway we can using gcloud cli or the GUI api gateway

  • Deploy using Gcloud
    gcloud api-gateway <api-gateway-name> create <config-name> --api=<api-name>--openapi-spec=<path-to-yaml> --project=<project-id>

    gcloud api-gateway api-configs create my-config   --api=my-api --openapi-spec=gateway.yaml   --project=ml-mps-trl-eps-exp-p-cf46
  • Deploy using API Gateway Service GCP GUI First search for api gateways and redirect to the page Then click on CREATE GATEWAY

5.png Then fill the values API - Display Name : my-api API - API ID : my-api-id API Config - Upload an API Spec : upload the gateway.yaml file API Config - Display Name : my-config API Config - Service Account : select one service account which has required permission Gateway details - Display Name : my-gateway Gateway details - Location : select any one Click on Create Gateway (it takes 3-5 mins to create)

Once Gateway is created click on the gateway and select gateway options

Next to get the API gateway URL

6.png

Copy the Gateway url

step 7

Test the API Gateway url in postman

GET - https://api-gateway-x6pp0r0.uc.gateway.dev/api/notesservice/notes

7.png

GET - https://api-gateway-x6pp0r0.uc.gateway.dev/api/productsservice/products

8.png

POST - https://api-gateway-x6pp0r0.uc.gateway.dev/api/notesservice/notes
DATA - {"id":10,"notes":"sample notes adding","completed":"true"}
HEADER - Content-Type : application/json

9.png

POST - https://api-gateway-x6pp0r0.uc.gateway.dev/api/productsservice/products
DATA - {"id":15,"product":"headphones"}
HEADER - Content-Type : application/json

10.png

FastAPIGCPMicroservicesAPI GatewayAPIs