Full Stack Developer Interview Questions 2024 — (Part 8— Cloud Concepts)

Souvik Majumder

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Nov 10, 2024

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1. What is AWS EC2, and how would you use it in a full-stack application?

• Answer: Amazon EC2 (Elastic Compute Cloud) is a service that provides resizable compute capacity in the cloud. It allows you to launch virtual servers (instances) and manage them as needed.
• Example: For a full-stack application, you could use EC2 to host your backend API server (e.g., Node.js or Django) and manage scaling based on demand. You could use EC2 to host a database as well, although a managed database service (e.g., Amazon RDS) is often preferred.

2. Explain how S3 works and how you would use it in a full-stack project.

• Answer: Amazon S3 (Simple Storage Service) is an object storage service that allows you to store and retrieve any amount of data. It’s often used for storing static assets, backups, and media files.
• Example: In a full-stack application, you could use S3 to store user-uploaded files, such as profile pictures, documents, or media. For example, when a user uploads a photo, the server could save it directly to an S3 bucket and return the file URL to be displayed on the frontend.

3. What is AWS Lambda, and how could it benefit a full-stack application?

• Answer: AWS Lambda is a serverless compute service that runs code in response to events and automatically manages the compute resources. It’s suitable for lightweight or asynchronous tasks.
• Example: In a full-stack application, you could use Lambda for tasks like processing images after they are uploaded, sending notifications, or handling background jobs (e.g., processing user analytics data). You could trigger a Lambda function to process an image stored in S3, resize it, and save the result back to S3.

4. How would you set up and use AWS API Gateway in a full-stack application?

• Answer: AWS API Gateway is a fully managed service that allows you to create, publish, and manage APIs. It’s often used with Lambda to build serverless backends.
• Example: In a full-stack application, you could use API Gateway to create RESTful or WebSocket APIs to serve as the backend. API Gateway could handle requests from the frontend and route them to Lambda functions, which process the data and return a response. This setup allows you to have a fully serverless backend.

5. What is Docker, and how would you use it in a full-stack development environment?

• Answer: Docker is a containerization platform that allows you to package applications and their dependencies into containers, ensuring consistent behavior across different environments.
• Example: In a full-stack project, you might use Docker to create containers for your backend API, frontend, and database, enabling isolated development and easy deployment. For instance, you could use a docker-compose.yml file to define and start all the containers for your application with a single command, ensuring that it works consistently on all machines.

version: '3'
services:
  frontend:
    image: node:14
    ports:
      - "3000:3000"
    volumes:
      - ./frontend:/app
    command: npm start
  backend:
    image: node:14
    ports:
      - "5000:5000"
    volumes:
      - ./backend:/app
    command: npm start
  db:
    image: postgres:13
    environment:
      POSTGRES_USER: user
      POSTGRES_PASSWORD: password
      POSTGRES_DB: mydb

6. Explain Kubernetes and its benefits for deploying full-stack applications.

• Answer: Kubernetes is an orchestration platform for managing, scaling, and deploying containerized applications. It automates tasks such as load balancing, scaling, and resource management.
• Example: In a full-stack application, Kubernetes could be used to deploy the frontend, backend, and database as separate pods, allowing for automated scaling and monitoring. For instance, you might use Kubernetes to deploy a Node.js backend service, and if traffic spikes, Kubernetes can automatically scale up additional instances of the backend service to handle the load.

7. How would you store user session data in a distributed environment on AWS?

• Answer: For storing session data in a distributed environment, you can use services like AWS DynamoDB or Elasticache with Redis.
• Example: In a load-balanced environment with multiple EC2 instances, storing session data on each instance could cause inconsistencies. Instead, you can use Redis on Elasticache to store session data centrally, making it accessible to all instances.

8. How would you manage environment variables in AWS for a secure deployment?

• Answer: Use AWS Secrets Manager or AWS Systems Manager Parameter Store to securely store and manage environment variables.
• Example: In a full-stack application, sensitive information like API keys or database credentials can be stored in Secrets Manager and injected into the environment of your EC2 instances or Lambda functions. This approach prevents hardcoding secrets into the codebase.

9. Explain how you would implement CI/CD for a Dockerized application deployed on AWS.

• Answer: AWS CodePipeline or GitHub Actions can be used to implement CI/CD. After pushing changes, CodePipeline can trigger a build in AWS CodeBuild, which builds Docker images and pushes them to Amazon Elastic Container Registry (ECR). Then, the deployment step can update an ECS or Kubernetes cluster with the latest image.
• Example:
• Use CodePipeline to detect commits to the repository.
• CodeBuild builds the Docker image and pushes it to ECR.
• A deployment stage deploys the new image to an ECS service or EKS cluster.

10. How does API Gateway handle throttling, and why is it important?

• Answer: API Gateway allows you to set throttling limits on API requests to prevent abuse and excessive load. Throttling limits the number of requests per second and bursts allowed for an API.
• Example: In a full-stack application with a public API, throttling could prevent high traffic from a few users from affecting all users. For instance, setting a rate limit of 1000 requests per second with a burst of 2000 would help manage unexpected traffic spikes.

11. How would you use AWS Lambda and S3 for a static website?

• Answer: You can use S3 to host static files (HTML, CSS, JS), and AWS Lambda for dynamic backend logic.
• Example: Use S3 to store and serve static assets, while using Lambda functions (invoked by API Gateway) to handle dynamic requests, such as form submissions or data processing.

12. What is Elastic Load Balancer (ELB) in AWS, and how would you use it in a full-stack application?

• Answer: An Elastic Load Balancer distributes incoming traffic across multiple EC2 instances, ensuring high availability and fault tolerance.
• Example: In a full-stack application with multiple EC2 instances for the backend, an ELB can route traffic to the healthiest instance and ensure no single instance is overloaded. This setup ensures smooth user experience even during peak traffic.

13. Explain the concept of Auto Scaling and how you would use it in a full-stack application.

• Answer: Auto Scaling automatically adjusts the number of EC2 instances based on demand. It scales up during high traffic and scales down during low traffic to optimize costs.
• Example: In a full-stack application, you could set up an auto-scaling group for the backend servers. If traffic increases, new EC2 instances will automatically be added to handle the load, ensuring the application remains responsive.

14. How would you implement authentication for a serverless application using API Gateway and Lambda?

• Answer: You can use Amazon Cognito or a custom Lambda authorizer for authentication.
• Example: Using Amazon Cognito, users can log in and receive a token. The frontend includes this token in API requests, and API Gateway verifies it with Cognito before allowing access. For custom authentication, use a Lambda authorizer to validate the token before API Gateway forwards requests to backend Lambdas.

15. How would you deploy a microservices architecture using Docker and Kubernetes on AWS?

• Answer: Use Amazon EKS (Elastic Kubernetes Service) to manage a Kubernetes cluster and deploy Dockerized microservices as separate pods, with each service having its deployment and scaling configuration.
• Example: For a full-stack application with separate services for user management, payments, and notifications, each service would be containerized and deployed on EKS. Kubernetes would manage scaling, load balancing, and service discovery across these microservices.

16. How do you use AWS CloudFront with S3, and why would it be beneficial?

• Answer: AWS CloudFront is a content delivery network (CDN) that caches data globally for faster access. When used with S3, it can cache static assets to reduce latency.
• Example: In a full-stack app with an S3-hosted frontend, CloudFront can cache images, CSS, and JS files at edge locations. This setup improves load times for users worldwide and reduces load on the S3 bucket.

17. How would you set up and manage data backups on AWS?

• Answer: Use AWS Backup or scheduled snapshots for databases (e.g., RDS) and storage services.
• Example: For a database hosted on RDS, you can schedule daily backups using automated RDS snapshots. For data stored in S3, use lifecycle policies to periodically archive objects to S3 Glacier as a cost-effective backup solution.

Kubernetes

1. What is Kubernetes, and why is it used?

• Answer: Kubernetes (K8s) is an open-source platform for automating the deployment, scaling, and management of containerized applications. It’s used to manage clusters of nodes and provide a consistent, reliable environment for running applications across different infrastructure. Kubernetes handles aspects like load balancing, self-healing, scaling, and automated deployment, making it an essential tool for managing complex applications in a distributed system.

2. What is a Kubernetes Cluster?

• Answer: A Kubernetes cluster is a collection of nodes that run containerized applications managed by Kubernetes. A cluster consists of a control plane (manages the overall cluster) and worker nodes (run the applications). Together, these provide a platform to deploy, manage, and scale applications.

3. What is a Node in Kubernetes?

• Answer: A node is a machine (physical or virtual) in a Kubernetes cluster that runs application containers. Nodes contain the necessary tools to run containers and are managed by the control plane. Each node runs pods, which are the smallest units in Kubernetes.

4. What is a Pod in Kubernetes?

• Answer: A pod is the smallest deployable unit in Kubernetes and represents a single instance of a running process in a cluster. Pods can contain one or more containers that share the same network namespace and storage resources, allowing them to communicate and work closely together.

5. What are Deployments in Kubernetes?

• Answer: A deployment is a Kubernetes resource that defines how to manage a set of identical pods. It allows you to specify the desired number of pod replicas and ensures that this number is maintained. Deployments support rolling updates, rollback, and scaling, making it easy to manage application lifecycles.

6. What is the role of the Kubernetes API Server?

• Answer: The API Server is a central component of the Kubernetes control plane and acts as the main entry point for all administrative operations. It exposes the Kubernetes API, which allows users to interact with the cluster, manage resources, and communicate with other control plane components.

7. What is a ReplicaSet, and how does it work?

• Answer: A ReplicaSet ensures that a specified number of pod replicas are running at all times. If a pod fails or is deleted, the ReplicaSet creates a new pod to replace it, maintaining the desired state. Deployments often use ReplicaSets to control the number of replicas.

8. What is a Service in Kubernetes, and why is it needed?

• Answer: A service in Kubernetes provides a stable IP address and DNS name for a set of pods, allowing applications to communicate with each other or external users. Services enable load balancing across pods and maintain connectivity even if individual pods are restarted or replaced.

9. Explain the different types of Services in Kubernetes.

• Answer:
• ClusterIP: Exposes a service internally within the cluster, accessible only from other services.
• NodePort: Exposes a service on a static port on each node’s IP, making it accessible from outside the cluster.
• LoadBalancer: Uses a cloud provider’s load balancer to expose the service externally.
• ExternalName: Maps a service to an external DNS name, allowing it to redirect to services outside the cluster.

10. What is a ConfigMap in Kubernetes?

• Answer: A ConfigMap is a Kubernetes resource used to store non-sensitive configuration data in key-value pairs. ConfigMaps are used to configure applications without embedding configuration data into the container images, allowing greater flexibility.

11. What is a Secret in Kubernetes, and how is it different from a ConfigMap?

• Answer: A Secret is similar to a ConfigMap but is designed for storing sensitive information like passwords, API tokens, and certificates. Secrets are encoded to provide an extra layer of protection compared to plain text data stored in ConfigMaps.

12. What is an Ingress in Kubernetes?

• Answer: An Ingress is a Kubernetes resource that manages external access to services within a cluster, typically HTTP and HTTPS traffic. It provides features like load balancing, SSL termination, and path-based routing.

13. What is the difference between StatefulSets and Deployments?

• Answer: Deployments manage stateless applications, ensuring that all pods are identical and can be replaced easily. StatefulSets, on the other hand, are used for stateful applications that require unique identities and persistent storage, ensuring pods are created and deleted in a specific order and with stable network identities.

14. What is a Persistent Volume (PV) and Persistent Volume Claim (PVC) in Kubernetes?

• Answer: A Persistent Volume (PV) is a storage resource in a Kubernetes cluster, while a Persistent Volume Claim (PVC) is a request for storage by a pod. Pods use PVCs to claim storage provided by PVs, enabling persistent storage even if the pod restarts.

15. How does Kubernetes handle scaling?

• Answer: Kubernetes handles scaling through the Horizontal Pod Autoscaler (HPA) and Cluster Autoscaler. HPA automatically scales the number of pod replicas based on CPU or memory usage, while Cluster Autoscaler adjusts the number of nodes based on the workload requirements.

16. What is kubectl, and why is it important?

• Answer: kubectl is the command-line tool for interacting with Kubernetes clusters. It allows users to deploy applications, inspect resources, manage configurations, and troubleshoot issues within a Kubernetes environment.

17. How does Kubernetes perform self-healing?

• Answer: Kubernetes provides self-healing by automatically restarting failed pods, rescheduling them on other nodes if necessary, and replacing unresponsive nodes or containers, ensuring the application remains highly available.

18. What is a Namespace in Kubernetes, and why would you use it?

• Answer: A Namespace is a logical partition within a Kubernetes cluster used to isolate resources. Namespaces are useful for organizing resources by teams, projects, or environments (e.g., dev, staging, prod), ensuring resource and security boundaries.

19. Explain a DaemonSet in Kubernetes.

• Answer: A DaemonSet ensures that a specific pod runs on all or specific nodes in a cluster. DaemonSets are often used for logging, monitoring, or other system-level tasks that need to run on each node.

20. What is a Helm Chart in Kubernetes?

• Answer: Helm is a package manager for Kubernetes, and Helm Charts are templates that define, install, and manage Kubernetes applications. Charts simplify the deployment of complex applications by bundling configuration and dependencies in a single package.

<- Revise Part 7 (Database)

Continue to Part 9 (Miscellaneous) ->