AKS + Azure Kubernetes: 5‑Day Professional Training Program

Day 1: Kubernetes & AKS Fundamentals

Day 1 of the program lays a solid foundation: Kubernetes architecture, container orchestration, and the managed Azure Kubernetes Service. Participants will begin with a conceptual walkthrough of Kubernetes—Pods, Deployments, Services and the control plane. We'll contrast the DIY Kubernetes model with AKS, highlighting how AKS abstracts and automates cluster management, upgrades, and integration with other Azure services.

We'll explore tools: using kubectl to interact with pods and deployments, configuring your context via kubeconfig, and using the Azure CLI (az aks) or Azure Portal to provision and manage clusters. Responsibilities such as updating node pools, scale settings, and cluster access are covered.

The hands‑on lab involves creating your first AKS cluster, deploying a simple sample microservice (e.g. Node.js or .NET), and verifying rollouts and rollbacks. You'll instrument liveness/readiness probes and practice basic scaling. This sets the stage for deeper architecture topics on Day 2.

• What is Kubernetes? Understanding container orchestration.
• Azure Kubernetes Service (AKS): managed Kubernetes on Azure.
• kubectl, kubeconfig, az aks CLI, and Azure Portal access.
• Hands‑on: create an AKS cluster, deploy a microservice.

Day 2: Cluster Architecture & Networking

On Day 2, we dive into AKS cluster internals. We’ll discuss node pools—why you might use different VM types, spot instances, or GPU nodes—and how auto‑scaling of node pools via VM Scale Sets helps handle variable demand. We cover the trade‑offs of Azure CNI (direct VNet injection) vs Kubenet, understanding how networking mode affects IP addressing, performance, and network policy enforcement.

We’ll demonstrate Service types: ClusterIP, NodePort, LoadBalancer, and using an Ingress controller (NGINX) for routing HTTP/HTTPS traffic. Internal‑only ingress and Azure Firewall rules for securing cluster access will be implemented in a guided lab. Participants will also explore network policies with Calico and enforcement of microsegmentation.

• Node pools, VM scale sets, autoscaling nodes.
• Azure CNI vs Kubenet, Network Policies.
• Service types: ClusterIP, NodePort, LoadBalancer, Ingress with NGINX.
• Hands‑on: setup internal ingress controller + firewall rules.

Day 3: Storage, Security & Azure AD

Storage is critical for stateful workloads. On Day 3, we’ll cover persistent volumes using Azure Disks and Azure Files via PersistentVolumeClaims (PVCs), StorageClasses, ReadWriteOnce/Many semantics, and dynamic provisioning. Case studies include hosting databases or shared file systems in a containerized architecture.

Security is tackled at multiple layers: Kubernetes RBAC, Azure AD integration for authenticating users and pods, and Azure Key Vault for storing secrets securely. We'll demonstrate how to map Azure AD groups into Kubernetes roles, configure pod MSI (Managed Service Identity) to fetch secrets at runtime, and use ConfigMaps vs Secrets appropriately.

In the lab, participants will enable Azure AD–based cluster RBAC, deploy an app that uses Key Vault via CSI secret store, and restrict resource access based on identity. We’ll also explore best practices for namespace isolation, Pod Security Policies, and role-based access control across teams.

• Mount Azure Disks and Azure Files using PVCs.
• RBAC in Kubernetes and integration with Azure AD identities.
• Secrets, ConfigMaps, and Key Vault integration.
• Hands‑on: secure an app with RBAC, secret mounts, and identity‑based access.

Day 4: CI/CD with Azure DevOps & GitHub

Day 4 brings workflows for shipping applications. We’ll integrate Docker builds with Azure Container Registry (ACR), manage versioning, and define image scanning policies. Participants learn to write YAML pipelines in Azure DevOps (Classic or YAML pipelines) that build and push container images, and deploy them to AKS using Helm charts.

We'll also demonstrate GitHub Actions CI/CD workflows: building containers, triggering image pushes to ACR or GitHub Packages, and deploying via Helm or Kubectl to AKS. Advanced deployment strategies such as Blue/Green and Canary using Helm and Argo Rollouts or Flagger will be explored.

The hands‑on includes creating a full pipeline from code commit to deployment: build Docker container, push to ACR, deploy safely to AKS, rollbacks, and automated test gates. You'll compare Azure Pipelines vs GitHub Actions and how to choose the right tool for your enterprise setup.

• Docker + ACR (Azure Container Registry) integration.
• GitHub Actions / Azure Pipelines to deploy containers to AKS.
• Blue/Green & Canary deployments with Helm and Argo Rollouts.
• Hands‑on: deploy using GitHub Actions and Azure DevOps YAML pipeline.

Day 5: Monitoring, Auto‑Scaling & Troubleshooting

Day 5 equips you with observability and operational readiness. We begin by enabling Azure Monitor for containers, viewing performance metrics, node and pod utilization, and setting up alerts. We'll also deploy Prometheus and Grafana (self‑managed or Azure Managed Grafana) for custom dashboards, query metrics, and visualize cluster health.

Autoscaling is key to resilient cloud-native systems. You'll configure Horizontal Pod Autoscaler (HPA) based on CPU/memory or custom metrics, and enable the Cluster Autoscaler on AKS to manage node pool scale. We'll simulate load and observe how the system responds.

Troubleshooting modules cover examining pod logs, events, and using kubectl debug features; draining nodes, taints and tolerations, liveness/readiness probe misconfiguration, and recovering unhealthy nodes. A fault injection lab helps you practice failover and resilience drills.

• Enable Azure Monitor, Prometheus, and Grafana dashboards.
• HPA (Horizontal Pod Autoscaler) and Cluster Autoscaler.
• Pod log tracing, node draining, liveness probes.
• Hands‑on: simulate outages, scale services, and recover cluster nodes.

Conclusion & Next Steps

Over the five days, you will have built a deep, end‑to‑end mastery of AKS—from provisioning a managed cluster, architecting secure and efficient network and storage, integrating with Azure AD, constructing CI/CD pipelines, to implementing observability and autoscaling strategies. You’ll complete labs replicating real‑world enterprise scenarios, enabling operational Kubernetes environments that follow best practices.

Why this training matters: AKS is Azure’s flagship Kubernetes service, used by enterprises worldwide. This training is built around hands‑on labs and expert guidance, ensuring you don’t just learn theory, but build real‑world deployment pipelines and cluster operations. You’ll graduate with confidence to manage production‑grade clusters, optimize resource usage, and deliver scalable containerized workloads securely.

Next steps: After training, you’ll be well‑prepared to pursue the Certified Kubernetes Administrator (CKA) exam, or the Azure‑specific AKS Engineer Associate certification. You may also join advanced bootcamps covering topics like GitOps with Flux or Argo CD, service mesh with Istio or Linkerd, and multi‑cluster federation. Organizations can work with us to implement AKS in production, adopt Terraform or Bicep IaC patterns, and embed DevSecOps pipelines.

What past participants say: “This training gave us the confidence to migrate our legacy workloads into AKS. The hands‑on parts were especially useful.” “I now lead AKS deployments in my team, secure cluster with AD integration, and manage CI/CD pipelines fluent in Azure DevOps.”

Enroll today to start your journey:

List of Kubernetes Courses

Whether you're just starting with Kubernetes or looking to advance your skills with Azure-specific cloud-native architectures, Eduarn offers a range of expert-led training programs. These courses are designed for DevOps engineers, cloud architects, and IT professionals looking to deliver scalable, secure, and production-ready Kubernetes solutions.

• AKS + Azure: Kubernetes on the Microsoft Cloud
  
A comprehensive 5-day hands-on course covering AKS fundamentals, CI/CD pipelines, cluster security, monitoring, and real-world deployment strategies on Microsoft Azure.

Top 25 Docker and Kubernetes Interview Questions (With Answers)

Below is a curated list of commonly asked technical questions for professionals preparing for interviews in Kubernetes and Docker. These questions are designed to test your understanding of core concepts, architecture, and real-world scenarios.

1. What is Docker?
   Answer: Docker is an open-source platform that automates the deployment, scaling, and management of applications in lightweight containers.
2. What is a container?
   Answer: A container is a lightweight, standalone, and executable software package that includes everything needed to run an application—code, runtime, libraries, and system tools.
3. What is Kubernetes?
   Answer: Kubernetes is an open-source container orchestration system for automating deployment, scaling, and management of containerized applications.
4. How does Kubernetes differ from Docker Swarm?
   Answer: Kubernetes is more feature-rich and widely adopted for complex production use-cases. Docker Swarm is simpler but less scalable and lacks features like auto-scaling and advanced networking.
5. What is a Pod in Kubernetes?
   Answer: A Pod is the smallest deployable unit in Kubernetes. It can contain one or more containers that share the same network and storage.
6. What is the difference between a Deployment and a StatefulSet?
   Answer: A Deployment is used for stateless applications, while StatefulSet is used for stateful applications that require persistent identity and storage (e.g., databases).
7. How do you expose a service externally in Kubernetes?
   Answer: You can expose a service externally using a Service of type LoadBalancer, NodePort, or Ingress.
8. What is a Kubernetes Namespace?
   Answer: Namespaces are used to divide cluster resources between multiple users and teams. They help in organizing and isolating workloads.
9. How does Kubernetes handle auto-scaling?
   Answer: Kubernetes supports Horizontal Pod Autoscaler (HPA) to scale pods based on CPU/memory metrics, and Cluster Autoscaler to adjust the number of nodes in the cluster.
10. What is the role of kubelet?
    Answer: Kubelet is an agent that runs on each node and ensures that containers are running as expected in a Pod.
11. What is the function of etcd in Kubernetes?
    Answer: etcd is a distributed key-value store that stores all cluster data, including configurations, state, and metadata.
12. What is the difference between Docker Image and Docker Container?
    Answer: An image is a read-only template used to create containers. A container is a runtime instance of an image.
13. What are Init Containers in Kubernetes?
    Answer: Init containers are specialized containers that run before app containers in a Pod and are used for initialization tasks like configuration or data preparation.
14. What is a Helm chart?
    Answer: Helm is a package manager for Kubernetes. A Helm chart is a set of YAML templates and configurations that define a Kubernetes application.
15. How do ConfigMaps and Secrets differ?
    Answer: ConfigMaps store plain-text configuration data. Secrets are used for storing sensitive information like passwords and tokens in an encoded format.
16. What is the difference between CMD and ENTRYPOINT in a Dockerfile?
    Answer: CMD sets default arguments that can be overridden. ENTRYPOINT defines the executable that cannot be overridden at runtime (unless explicitly using --entrypoint).
17. What is an Ingress in Kubernetes?
    Answer: An Ingress is an API object that manages external access to services in a cluster, typically HTTP/HTTPS, using routing rules.
18. How do you secure communication between Pods?
    Answer: You can secure communication using Kubernetes Network Policies, TLS encryption, and service mesh implementations like Istio or Linkerd.
19. What is Docker Compose?
    Answer: Docker Compose is a tool to define and manage multi-container Docker applications using a YAML file.
20. What are Labels and Selectors in Kubernetes?
    Answer: Labels are key/value pairs attached to objects. Selectors are used to query and filter those objects based on label criteria.
21. How do you roll back a deployment in Kubernetes?
    Answer: You can use the command kubectl rollout undo deployment <deployment-name> to revert to the previous stable state.
22. What is Docker Volumes?
    Answer: Volumes are persistent storage mechanisms in Docker used to store data outside the container's lifecycle.
23. What is a Service Mesh?
    Answer: A service mesh is an infrastructure layer that handles service-to-service communication, observability, and security, often using sidecar proxies (e.g., Istio).
24. How does Kubernetes handle high availability of the Control Plane?
    Answer: Kubernetes supports control plane HA by running multiple API server replicas and etcd nodes with load balancing.
25. How would you troubleshoot a CrashLoopBackOff error?
    Answer: Check the container logs using kubectl logs, inspect readiness/liveness probes, resource limits, and image configurations. The error typically indicates that the container starts and crashes repeatedly.

25 MCQ Questions on Docker and Kubernetes (With Answers)

Test your understanding of Kubernetes and Docker with these multiple-choice questions commonly asked in technical interviews and certification assessments.

1. What is the default container orchestration tool for Docker?
   A. Kubernetes
   B. Docker Swarm ✅
   C. Mesos
   D. Marathon
2. What command is used to list all Docker containers (running and stopped)?
   A. docker show
   B. docker list
   C. docker ps -a ✅
   D. docker container list
3. Which component of Kubernetes ensures that containers are running in a pod?
   A. Scheduler
   B. API Server
   C. Controller Manager
   D. Kubelet ✅
4. Which Kubernetes object is used to expose a pod to external traffic?
   A. ReplicaSet
   B. ConfigMap
   C. Service ✅
   D. StatefulSet
5. Which Dockerfile instruction is used to execute a command at container runtime?
   A. RUN
   B. CMD ✅
   C. COPY
   D. EXPOSE
6. What does a Kubernetes Deployment manage?
   A. Persistent Volumes
   B. Application lifecycle ✅
   C. Network policies
   D. User access roles
7. What is a Helm chart?
   A. A container image
   B. A monitoring tool
   C. A package manager for Kubernetes ✅
   D. A load balancer
8. Which command builds a Docker image from a Dockerfile?
   A. docker start
   B. docker run
   C. docker build ✅
   D. docker make
9. What type of volume is used in Kubernetes for dynamic storage provisioning?
   A. HostPath
   B. ConfigMap
   C. PersistentVolumeClaim ✅
   D. Secret
10. Which Kubernetes object runs an init task before the main application starts?
    A. Job
    B. Init Container ✅
    C. Sidecar
    D. CronJob
11. How do you scale a Kubernetes Deployment to 5 replicas?
    A. kubectl update replicas=5
    B. kubectl scale deployment myapp --replicas=5 ✅
    C. kubectl deploy replicas 5
    D. kubectl set scale 5
12. Which Kubernetes object is responsible for storing cluster configuration?
    A. kube-proxy
    B. etcd ✅
    C. kube-scheduler
    D. controller-manager
13. What is the command to view logs of a Kubernetes pod?
    A. kubectl get logs pod-name
    B. kubectl describe pod-name
    C. kubectl logs pod-name ✅
    D. kubectl status pod-name
14. Which of the following is NOT a Docker component?
    A. Docker Engine
    B. Docker Compose
    C. Docker Hub
    D. Docker Mesh ✅
15. What does Kubernetes use for high availability and leader election?
    A. DNS
    B. etcd ✅
    C. kube-proxy
    D. CRI
16. What is a Docker volume primarily used for?
    A. Managing user access
    B. Container orchestration
    C. Persistent data storage ✅
    D. CPU allocation
17. Which command stops a running container in Docker?
    A. docker shutdown
    B. docker stop ✅
    C. docker exit
    D. docker kill-all
18. What does a Kubernetes Service of type NodePort do?
    A. Forwards traffic to internal DNS
    B. Opens a static port on each Node ✅
    C. Creates a persistent volume
    D. Sets resource limits
19. Which Kubernetes controller ensures the desired number of pod replicas are running?
    A. Pod Controller
    B. ReplicaSet ✅
    C. VolumeController
    D. ConfigMap
20. Which command removes a Docker container permanently?
    A. docker stop
    B. docker kill
    C. docker delete
    D. docker rm ✅
21. How does Kubernetes implement load balancing across Pods?
    A. Using kubelet
    B. Using Services ✅
    C. Using Ingress
    D. Using CronJobs
22. What is the role of a Dockerfile?
    A. It defines Kubernetes secrets
    B. It describes how to build a Docker image ✅
    C. It creates a Docker volume
    D. It sets up autoscaling
23. Which service type is used in Kubernetes for ingress routing with rules?
    A. LoadBalancer
    B. Ingress ✅
    C. NodePort
    D. ClusterIP
24. What does the Kubernetes Scheduler do?
    A. Starts and stops containers
    B. Assigns pods to available nodes ✅
    C. Scales the deployment
    D. Stores cluster state
25. Which of the following tools is best for defining infrastructure as code for Kubernetes on Azure?
    A. Azure DevOps
    B. Azure CLI
    C. Terraform ✅
    D. Visual Studio Code

25 True/False Questions on Docker and Kubernetes (With Answers)

Assess your foundational knowledge of Docker and Kubernetes with these True or False questions commonly asked in interviews and certification exams.

1. Docker containers share the host OS kernel. (True)
2. Kubernetes Pods can contain multiple containers. (True)
3. Docker images are mutable after they are built. (False)
4. In Kubernetes, a ReplicaSet ensures a specified number of pod replicas are running at all times. (True)
5. The Kubernetes API Server acts as the frontend for the Kubernetes control plane. (True)
6. Docker Compose can be used to orchestrate multi-node Kubernetes clusters. (False)
7. PersistentVolumes in Kubernetes provide storage that lives beyond the lifecycle of individual pods. (True)
8. Kubernetes automatically scales nodes based on CPU utilization without any additional configuration. (False)
9. Helm is a package manager for Kubernetes that simplifies deployment of complex applications. (True)
10. Docker Swarm and Kubernetes are both container orchestration platforms. (True)
11. A Kubernetes Service of type LoadBalancer exposes the service externally using a cloud provider’s load balancer. (True)
12. Docker containers cannot communicate with each other unless they are in the same Docker network. (True)
13. Kubernetes uses etcd as a distributed key-value store to maintain cluster state. (True)
14. Dockerfiles support running multiple CMD instructions in the same file. (False)
15. In Kubernetes, ConfigMaps are used to manage sensitive information like passwords. (False)
16. Using Kubernetes namespaces helps isolate resources and improve cluster organization. (True)
17. Docker volumes allow data persistence even after a container is deleted. (True)
18. The Kubernetes kubelet runs on the master node only. (False)
19. Pod autoscaling in Kubernetes can be configured based on CPU utilization. (True)
20. Docker Hub is a cloud-based registry for Docker images. (True)
21. Kubernetes Ingress resources control external access to services in a cluster, typically via HTTP. (True)
22. A Docker container’s lifecycle ends when the container process stops. (True)
23. Kubernetes StatefulSets are used to deploy stateless applications. (False)
24. Docker allows running containers without root privileges on the host. (True)
25. Both Kubernetes and Docker are responsible for container runtime management. (False)

Real-World Use Case: Modernizing a Large-Scale E-Commerce Platform with Docker, Kubernetes, and Azure

Background

A global e-commerce company wanted to modernize its legacy monolithic application to improve scalability, deployment agility, and operational efficiency. They decided to move to a microservices architecture, leveraging containers and cloud-native technologies to support rapid feature releases and handle fluctuating customer demand.

Challenges

• Monolithic app was difficult to scale and maintain.
• Slow release cycles causing delayed feature rollouts.
• Manual deployments with high error rates.
• Need for better resource utilization and cost control.
• Ensure high availability and fault tolerance during peak shopping seasons.
• Secure sensitive customer data and ensure compliance.

Solution Overview

The company chose to containerize their microservices using Docker, orchestrate and manage them using Kubernetes, and host the entire platform on Microsoft Azure, leveraging Azure Kubernetes Service (AKS).

Step 1: Containerizing Applications with Docker

• Each microservice (e.g., product catalog, user management, order processing, payment gateway) was packaged as a lightweight Docker container.
• Docker images were stored and managed in Azure Container Registry (ACR), enabling secure, scalable image storage close to the deployment environment.
• Developers used Dockerfiles to automate builds, ensuring consistency across development, testing, and production.

Step 2: Orchestrating with Kubernetes on Azure

• Azure Kubernetes Service (AKS) provided a managed Kubernetes cluster, abstracting the complexity of cluster setup, upgrades, and scaling.
• Kubernetes managed deployment, scaling, and self-healing of microservices pods.
• Microservices were deployed as Kubernetes Deployments with ReplicaSets to ensure the desired number of instances were always running.
• Networking was handled using Azure CNI, allowing pods to receive IP addresses from the Azure VNet, improving network isolation and security.
• Kubernetes Services exposed microservices internally and externally using LoadBalancer and Ingress resources.
• Stateful components, like databases and caches, were provisioned using PersistentVolumes backed by Azure Managed Disks and Azure Files.

Step 3: Implementing CI/CD Pipelines

• Continuous Integration pipelines on Azure DevOps or GitHub Actions automated:
  • Building Docker images on code commit.
  • Running automated tests.
  • Pushing images to Azure Container Registry.
• Continuous Deployment pipelines automatically rolled out new versions to AKS with Helm charts, supporting blue/green and canary deployments to minimize downtime and risk.

Step 4: Monitoring, Logging, and Security

• Azure Monitor and Azure Log Analytics collected metrics and logs from the AKS cluster.
• Integration with Prometheus and Grafana dashboards provided detailed insights into pod performance, cluster health, and resource usage.
• Kubernetes RBAC integrated with Azure Active Directory (Azure AD) ensured secure, role-based access to cluster resources.
• Secrets management was handled using Azure Key Vault integrated with Kubernetes secrets for storing sensitive data securely.
• Network policies enforced strict communication rules between microservices, minimizing attack surface.

Benefits Realized

• Scalability: The system automatically scales microservices up/down based on demand with Kubernetes Horizontal Pod Autoscaler and AKS node autoscaling.
• Reliability: Kubernetes ensures self-healing and zero-downtime deployments.
• Faster Time to Market: CI/CD pipelines enable multiple daily releases with automated quality checks.
• Cost Efficiency: Pay-as-you-go Azure resources combined with Kubernetes resource quotas optimize infrastructure costs.
• Security & Compliance: Azure AD integration, Key Vault secrets management, and network policies enhance security posture.
• Operational Simplicity: AKS abstracts cluster management complexity, enabling the DevOps team to focus on application delivery.

Summary

By leveraging Docker for containerization, Kubernetes for orchestration, and Azure’s managed services, the e-commerce company successfully modernized its infrastructure to be cloud-native, resilient, scalable, and secure — positioning itself for rapid growth and competitive advantage.