Deploying workloads in GCP - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ service_behavior

intermediate

Understanding GKE Pod Scheduling Behavior

You deploy a Kubernetes Pod on Google Kubernetes Engine (GKE) with a node selector that matches no nodes. What will happen to the Pod?

GCP

apiVersion: v1
kind: Pod
metadata:
  name: test-pod
spec:
  containers:
  - name: nginx
    image: nginx
  nodeSelector:
    disktype: ssd

A The Pod will remain in Pending state indefinitely because no nodes match the selector.

B The Pod will be scheduled on any available node ignoring the nodeSelector.

C The Pod will be deleted automatically by GKE after 5 minutes.

D The Pod will start running on the master node.

💡 Hint

Think about how Kubernetes schedules Pods with node selectors.

If no nodes match the nodeSelector, the Pod cannot be scheduled and stays Pending until a matching node appears.

❓ Architecture

intermediate

Choosing the Right Compute Service for a Stateless Web App

You want to deploy a stateless web application that must scale automatically based on HTTP traffic. Which Google Cloud service is the best choice?

A Google App Engine Standard Environment with automatic scaling.

B Google Compute Engine with manual instance group scaling.

C Google Kubernetes Engine with a single node cluster.

D Cloud Functions triggered by HTTP requests.

💡 Hint

Consider which service offers automatic scaling for web apps without managing infrastructure.

App Engine Standard Environment automatically scales stateless web apps based on traffic without user management of servers.

❓ security

advanced

Securing Workloads with Service Accounts

You deploy a workload on Google Cloud Run that needs to access a Cloud Storage bucket securely. What is the best practice to grant access?

A Use a user’s personal credentials to access the bucket from the Cloud Run service.

B Assign the Cloud Run service's default service account the Storage Object Viewer role on the bucket.

C Embed the Cloud Storage credentials as environment variables in the Cloud Run service.

D Make the Cloud Storage bucket public so Cloud Run can access it without credentials.

💡 Hint

Think about the principle of least privilege and secure identity management.

Assigning the service account the minimal required role is secure and avoids embedding credentials.

❓ Configuration

advanced

Configuring Autoscaling for a GKE Deployment

You want to configure Horizontal Pod Autoscaling (HPA) for a GKE Deployment based on CPU usage. Which YAML snippet correctly defines the HPA?

A

apiVersion: autoscaling/v2beta2
kind: HorizontalPodAutoscaler
metadata:
  name: webapp-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: webapp
  minReplicas: 2
  maxReplicas: 10
  metrics:
  - type: Pods
    pods:
      metric:
        name: cpu
      target:
        type: AverageValue
        averageValue: 50m

B

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: webapp-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: webapp
  minReplicas: 2
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 50

C

apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
  name: webapp-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: webapp
  minReplicas: 2
  maxReplicas: 10
  targetMemoryUtilizationPercentage: 50

D

apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
  name: webapp-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: webapp
  minReplicas: 2
  maxReplicas: 10
  targetCPUUtilizationPercentage: 50

💡 Hint

Look for the correct apiVersion and field names for CPU-based autoscaling.

autoscaling/v1 with targetCPUUtilizationPercentage is the standard way to configure CPU autoscaling in GKE.

✅ Best Practice

expert

Designing a Multi-Region Deployment for High Availability

You need to deploy a web application on Google Cloud to achieve high availability across multiple regions. Which architecture follows best practices?

A Deploy the application in multiple zones within a single region and rely on client-side retries for failover.

B Deploy the application in multiple regions with independent databases and use DNS round-robin to distribute traffic.

C Deploy the application in multiple regions with a global HTTP(S) Load Balancer and a multi-region managed database with replication.

D Deploy the application in a single region with multiple zones and use a global HTTP(S) Load Balancer with Cloud CDN.

💡 Hint

Consider global load balancing and data consistency across regions.

Using a global load balancer with multi-region database replication ensures availability and data consistency.