GKE sticky connections makes autoscaling uneffective because of limited pod ports (API to database)

Question

I have an API to which I send requests, and this API connects to MongoDB through MongoClient in PyMongo. Here is a scheme of my system that I deployed in GKE:

The major part of the calculations needed for each request are made in the MongoDB, so I want the MongoDB pods to be autoscaled based on CPU usage. Thus I have an HPA for the MongoDB deployment, with minReplicas: 1.

When I send many requests to the Nginx Ingress, I see that my only MongoDB pod has 100% CPU usage, so the HPA creates a second pod. But this second pod isn't used.

After looking in the logs of my first MongoDB pod, I see that all the requests have this : "remote":"${The_endpoint_of_my_API_Pod}:${PORT}", and the PORT only takes 12 different values (I counted them, they started repeating so I guessed that there aren't others).

So my guess is that the second pod isn't used because of sticky connections, as suggested in this answer https://stackoverflow.com/a/73028316/19501779 to one my previous questions, where there is more detail on my MongoDB deployment.

I have 2 questions :

• Is the second pod not used in fact because of sticky connections between my API Pod and my first MongoDB Pod?
• If this is the case, how can I overcome this issue to make the autoscaling effective?

Thanks, and if you need more info please ask me.

EDIT

Here is my MongoDB configuration:

Its Dockerfile, from which I create my MongoDB image from the VM where my original MongoDB is. A single deployment of this image works in k8s.

FROM mongo:latest
EXPOSE 27017
COPY /mdb/ /data/db

The deployment.yml:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: mongodb
  labels:
    app: mongodb
spec:
  replicas: 1
  selector:
    matchLabels:
      app: mongodb
  template:
    metadata:
      labels:
        app: mongodb
    spec:
      containers:
      - name: mongodb
        image: $My_MongoDB_image
        ports:
        - containerPort: 27017
        resources:
          requests:
            memory: "1000Mi"
            cpu: "1000m"
      imagePullSecrets:   #for pulling from my Docker Hub
      - name: regcred

and the service.yml and hpa.yml:

apiVersion: v1
kind: Service
metadata:
  name: mongodb-service
  labels:
    app: mongodb
spec:
  selector:
    app: mongodb
  ports:
    - protocol: TCP
      port: 27017
      targetPort: 27017
---
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
    name: mongodb-hpa
spec:
    scaleTargetRef:
      apiVersion: apps/v1
      kind: Deployment
      name: mongodb
    minReplicas: 1
    maxReplicas: 70
    targetCPUUtilizationPercentage: 85

And I access to this service from my API Pod with PyMongo:

def get_db(database: str):
    client = MongoClient(host="$Cluster_IP_of_{mongodb-service}",
                         port=27017,
                         username="...",
                         password="...",
                         authSource="admin")
    return client.get_database(database)

And moreover, when a second MongoDB Pod is created thanks to autoscaling, its endpoint appears in my mongodb-service:

• the HPA created a second Pod

• the new Pod endpoints appears in the mongodb-service