Top 10 high-level EC2 scenario-based questions to challenge your AWS & DevOps skills

 🔹 Understanding Kubernetes Architecture 🔹

🚀 Kubernetes Architecture Explained! 

Kubernetes is a container orchestration platform that helps manage and scale containerized applications efficiently. This image provides an overview of its key components and how they interact. 

🔹 control plane 

The control plane is responsible for managing the cluster and ensuring everything runs smoothly. It includes: 

- api server: the central component that handles all communication within the cluster. It processes requests from users and other Kubernetes components. 

- scheduler: assigns workloads (pods) to worker nodes based on resource availability and requirements. 

- controller-manager: maintains the desired state of the cluster by running controllers that manage nodes, deployments, and other resources. 

- etcd: a distributed key-value store that stores all cluster data, such as configurations and state information. 

🔹 worker nodes 

Worker nodes run application workloads and provide the computing resources for containers. Each worker node consists of: 

- pods: the smallest deployable unit in Kubernetes, containing one or more containers. 

- containers: application workloads running inside pods. 

- container runtime (e.g., docker): executes and manages containers on the node. 

- kubelet: an agent running on each worker node that ensures containers are running and healthy. 

- kube-proxy: manages networking between different pods and services within the cluster. 

🔹 user interface and cli 

- kubectl: a command-line tool used to interact with the Kubernetes API for deploying and managing applications. 

- ui dashboards: graphical interfaces that allow monitoring and management of the Kubernetes cluster. 

Kubernetes provides scalability, self-healing, and automation for modern cloud-native applications. It is widely used in cloud computing environments such as AWS, Azure, and Google Cloud. 

What challenges have you faced while working with Kubernetes? Let’s discuss! 

Kubernetes isn’t just a container orchestration tool — it’s a powerful distributed system designed to manage workloads at scale. 🚀

At a high level, the architecture is divided into two main components:

✅ Control Plane – The “brain” of Kubernetes, responsible for maintaining the desired state of the cluster. Key components include:

API Server → Front door to the cluster

etcd → Stores cluster state & configuration

Scheduler → Assigns workloads (Pods) to nodes

Controller Manager → Ensures system health & scaling

✅ Worker Nodes – Where applications actually run. Each node hosts:

Kubelet → Communicates with control plane

Kube-Proxy → Handles networking & service routing

Container Runtime → Runs containers (Docker, containerd, etc.)

Together, the Control Plane & Worker Nodes form a self-healing, scalable, and resilient system that powers modern cloud-native applications. 🌐

👉 Mastering this architecture is the first step toward understanding advanced Kubernetes features like AutoScaling, Service Mesh, and Multi-Cluster management.

✅ Kubernetes Architecture Simplified 

Understanding Kubernetes architecture is foundational before diving into deploying or managing clusters. Here's a quick breakdown: 

 

🔹 What is Kubernetes Architecture? 

Kubernetes follows a master-worker model: 

• Control Plane (Master Node): Manages the cluster 

• Worker Nodes: Run your application workloads 

 

🧩 Key Components 

🔸 Control Plane (Master Node): 

1. API Server – Entry point (receives kubectl commands) 

2. Controller Manager – Maintains desired state (e.g., restarts pods) 

3. Scheduler – Assigns pods to nodes 

4. etcd – Stores all cluster data 

5. Cloud Controller Manager – Manages cloud provider logic 

🔸 Worker Nodes: 

1. kubelet – Runs containers and talks to the API server 

2. kube-proxy – Manages service networking 

3. Container Runtime – Executes containers (e.g., containerd, Docker) 

 

❓ Why Does It Matter? 

• Helps in debugging and tuning clusters 

• Enables better scaling and security 

• Clarifies control plane vs. data plane roles 

 

⏰ When to Learn This? 

• Before cluster deployments or operations 

• Before configuring custom networking or schedulers 

• Must-know for certifications like CKA 

 

📖 Quick Summary Table: 

Layer Component Responsibility

 

Control Plane --> API ->Server Cluster entry point 

 Controller Manager -> Reconciles state 

 Scheduler ->Pod assignment 

 etcd ->Cluster data store 

Worker Node-- ->kubelet -> Manages containers 

 kube-proxy ->Service networking 

 Container Runtime -> Runs containers