Deploying workloads to AKS in Azure - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ service_behavior

intermediate

Understanding Pod Scheduling in AKS

You deploy a workload to AKS with a pod that requests 2 CPU cores and 4 GB memory. The cluster has nodes with 1 CPU core and 3 GB memory each. What will happen when you apply the deployment?

A The pod will remain pending because no single node has enough resources to satisfy the request.

B The pod will be scheduled but will be throttled to fit the node resources.

C The pod will be scheduled across multiple nodes to meet the resource request.

D The pod will be scheduled on a single node because AKS automatically splits resource requests.

💡 Hint

Think about how Kubernetes schedules pods based on node resources.

Kubernetes schedules pods on a single node that can satisfy the resource requests. Since no node has enough CPU and memory, the pod stays pending until resources are available.

❓ Configuration

intermediate

Correct YAML for Deploying a Container to AKS

Which YAML snippet correctly deploys a single container named webapp using the image nginx:latest in AKS?

A

apiVersion: v1
kind: Pod
metadata:
  name: webapp
spec:
  containers:
  - name: webapp
    image: nginx:latest

B

apiVersion: apps/v1
kind: Deployment
metadata:
  name: webapp
spec:
  replicas: 1
  template:
    metadata:
      labels:
        app: webapp
    spec:
      containers:
      - name: webapp
        image: nginx:latest

C

apiVersion: apps/v1
kind: Pod
metadata:
  name: webapp
spec:
  containers:
  - name: webapp
    image: nginx:latest

D

apiVersion: v1
kind: Deployment
metadata:
  name: webapp
spec:
  replicas: 1
  containers:
  - name: webapp
    image: nginx:latest

💡 Hint

Deployments use apps/v1 and have a template section.

Option B correctly defines a Deployment with replicas, metadata labels, and container spec under the pod template.

❓ Architecture

advanced

Designing AKS Cluster for High Availability

You need to design an AKS cluster that remains available even if one node fails. Which configuration best supports this requirement?

A Create one node pool with 3 nodes all in the same availability zone.

B Create a single node pool with 1 node and enable auto-scaling.

C Create three node pools each with 1 node in the same availability zone.

D Create a single node pool with 3 nodes spread across 3 availability zones.

💡 Hint

Think about spreading nodes to avoid single points of failure.

Spreading nodes across availability zones ensures the cluster remains available if one zone or node fails.

❓ security

advanced

Securing Container Images in AKS

You want to ensure only trusted container images are deployed to your AKS cluster. Which approach enforces this best?

A Allow any image from public registries to speed up deployment.

B Manually review images before deployment without automation.

C Use Azure Policy to enforce image source and scan images for vulnerabilities.

D Use Kubernetes Network Policies to restrict image downloads.

💡 Hint

Consider automated policies and scanning tools.

Azure Policy can enforce allowed image sources and integrate vulnerability scanning to ensure security.

✅ Best Practice

expert

Optimizing AKS Cluster Cost and Performance

You manage an AKS cluster with variable workloads. What is the best practice to optimize cost without sacrificing performance?

A Use cluster autoscaler with multiple node pools of different VM sizes and spot instances for non-critical workloads.

B Use a fixed-size node pool with the largest VM size to handle peak loads at all times.

C Disable autoscaling and manually add nodes during high demand periods.

D Use only spot instances for all workloads to minimize cost.

💡 Hint

Think about balancing cost savings and workload reliability.

Using autoscaling with mixed node pools and spot instances for flexible workloads optimizes cost and maintains performance.