Demo Configure a backend service based external load balancer

In this guide, you will learn how to set up a backend service–based external (Layer 4) load balancer on Google Kubernetes Engine (GKE). We’ll walk through configuring your gcloud defaults, creating a GKE cluster with HTTP load balancing, deploying an echo server, exposing it via an annotated Service, and verifying traffic distribution across Pods.

Table of Contents

1. Set the Default Region and Zone
2. Create the GKE Cluster
3. Prepare the Deployment Manifest
4. Prepare the Service Manifest
5. Deploy the Application and Service
6. Verify the External Load Balancer
7. Inspect the Service Configuration
8. Links and References

1. Set the Default Region and Zone

Configure your default compute zone so that all subsequent gcloud commands target us-west1-a:

gcloud config set compute/zone us-west1-a

2. Create the GKE Cluster

Create a cluster named gke-deep-dive with HTTP load balancing enabled:

gcloud container clusters create gke-deep-dive \
  --num-nodes=1 \
  --disk-type=pd-standard \
  --disk-size=10 \
  --enable-ip-alias \
  --addons=HttpLoadBalancing

This step can take several minutes. Once complete, verify the HTTP load balancing add-on:

gcloud container clusters describe gke-deep-dive \
  --format="yaml(addonsConfig.httpLoadBalancing)"

Expected output snippet:

addonsConfig:
  httpLoadBalancing: {}

3. Prepare the Deployment Manifest

Save the following Deployment in gke-deep-dive-app.yaml. It launches two replicas of an echo server on port 8080 and configures a readiness probe.

# gke-deep-dive-app.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: gke-deep-dive-app
spec:
  replicas: 2
  selector:
    matchLabels:
      app: online
  template:
    metadata:
      labels:
        app: online
    spec:
      containers:
      - name: gke-deep-dive-app
        image: gcr.io/google-containers/echoserver:1.10
        ports:
        - name: http
          containerPort: 8080
        readinessProbe:
          httpGet:
            path: /healthz
            port: 8080
          scheme: HTTP

4. Prepare the Service Manifest

Save the following Service definition in gke-deep-dive-svc.yaml. The annotation cloud.google.com/l4-rbs: "true" requests a backend service–based external L4 load balancer.

# gke-deep-dive-svc.yaml
apiVersion: v1
kind: Service
metadata:
  name: gke-deep-dive-svc
  annotations:
    cloud.google.com/l4-rbs: "true"
spec:
  type: LoadBalancer
  externalTrafficPolicy: Cluster
  selector:
    app: online
  ports:
    - name: tcp-port
      protocol: TCP
      port: 1729
      targetPort: 8080

5. Deploy the Application and Service

Apply both manifests and verify resources:

kubectl apply -f gke-deep-dive-app.yaml
kubectl apply -f gke-deep-dive-svc.yaml

Check Pods and Services:

kubectl get pods
kubectl get svc

Example output:

Wait for the Service’s EXTERNAL-IP to appear (this may take a few minutes).

6. Verify the External Load Balancer

Retrieve the external IP and test connectivity:

EXTERNAL_IP=$(kubectl get svc gke-deep-dive-svc \
  --output=jsonpath='{.status.loadBalancer.ingress[0].ip}')

curl ${EXTERNAL_IP}:1729

A successful response looks like:

Hostname: gke-deep-dive-app-xxx
...
client_address=10.64.0.1
...

Multiple curl requests should alternate between Pod backends.

7. Inspect the Service Configuration

Describe the Service to confirm load balancer details:

kubectl describe svc gke-deep-dive-svc

Key fields:

• Type: LoadBalancer
• Annotations: cloud.google.com/l4-rbs: "true"
• Port Mapping: 1729/TCP → 8080/TCP
• Endpoints: Pod IPs on port 8080
• External Traffic Policy: Cluster

Sample excerpt:

Name:                     gke-deep-dive-svc
Type:                     LoadBalancer
LoadBalancer Ingress:     35.227.179.152
Port:                     tcp-port 1729/TCP → 8080/TCP
Endpoints:                10.68.132.199:8080,10.68.132.200:8080

Your backend service–based external load balancer is now active and distributing traffic across your GKE Pods.

8. Links and References

• Google Kubernetes Engine Documentation
• Kubernetes Services
• kubectl Reference