15 AWS Cloud Interview Questions and Answers

AWS Cloud has become a cornerstone in the realm of cloud computing, offering scalable, reliable, and cost-effective solutions for businesses of all sizes. With a comprehensive suite of services ranging from computing power and storage to machine learning and analytics, AWS enables organizations to innovate and scale rapidly. Its robust infrastructure and extensive global network make it a preferred choice for enterprises looking to enhance their cloud capabilities.

This article provides a curated selection of AWS Cloud interview questions designed to help you demonstrate your expertise and understanding of AWS services. By familiarizing yourself with these questions, you can confidently showcase your knowledge and problem-solving skills in your upcoming interviews.

AWS Cloud Interview Questions and Answers

1. Describe the architecture of an AWS VPC and its components.

An AWS Virtual Private Cloud (VPC) is a logically isolated section of the AWS cloud where you can launch resources in a virtual network. Key components include:

• Subnets: Segments of the VPC’s IP address range for grouping resources. They can be public, private, or VPN-only.
• Route Tables: Sets of rules that direct network traffic. Each subnet must be associated with a route table.
• Internet Gateway (IGW): Enables communication between instances in your VPC and the internet, providing access to public subnets.
• NAT Gateway: Allows instances in a private subnet to connect to the internet while preventing inbound connections.
• Security Groups: Virtual firewalls for instances to control traffic at the instance level.
• Network Access Control Lists (NACLs): Provide an additional security layer at the subnet level.
• Elastic IP Addresses: Static IPs that can be moved between instances.
• VPC Peering: Connects one VPC with another using private IP addresses.
• Endpoints: Enable private connections to supported AWS services without requiring an internet gateway.

2. How would you set up a highly available web application using EC2 instances?

To set up a highly available web application using EC2 instances, leverage several AWS services for redundancy, fault tolerance, and scalability:

• EC2 Instances: Launch multiple instances across different availability zones to ensure availability during zone failures.
• Elastic Load Balancer (ELB): Distributes incoming traffic across instances, providing fault tolerance by routing traffic to healthy instances.
• Auto Scaling Group: Automatically adjusts the number of instances based on demand, maintaining performance.
• Multiple Availability Zones: Deploy instances across zones to protect against data center failures.
• RDS Multi-AZ Deployment: For relational databases, use Amazon RDS with Multi-AZ for high availability and failover support.
• Route 53: Manage DNS and route traffic to healthy endpoints.

3. How do you configure auto-scaling for an application hosted on EC2?

Auto-scaling in AWS allows applications to adjust the number of EC2 instances based on demand. Key components include:

• Launch Configuration or Launch Template: Defines instance settings.
• Auto Scaling Group (ASG): Manages a group of instances, defining minimum, maximum, and desired numbers.
• Scaling Policies: Rules for scaling based on metrics like CPU utilization.

To configure auto-scaling:

• Create a Launch Configuration or Template with desired settings.
• Create an ASG and associate it with the Launch Configuration or Template.
• Define Scaling Policies based on metrics or CloudWatch alarms.
• Optionally, configure notifications for scaling events.

4. What are the different types of storage classes in S3 and their use cases?

Amazon S3 offers several storage classes for different use cases and cost requirements:

• S3 Standard: For frequently accessed data, offering low latency and high throughput.
• S3 Intelligent-Tiering: Automatically moves data between access tiers based on access patterns.
• S3 Standard-IA (Infrequent Access): For less frequently accessed data, with lower storage costs and retrieval fees.
• S3 One Zone-IA: Similar to Standard-IA but stored in a single availability zone.
• S3 Glacier: For long-term archival storage with low costs and retrieval times from minutes to hours.
• S3 Glacier Deep Archive: Lowest-cost storage for rarely accessed data with retrieval times of 12 hours or more.

5. Explain the concept of eventual consistency in DynamoDB.

Eventual consistency in DynamoDB means that all replicas of data will converge to the same value over time. DynamoDB offers:

• Eventually Consistent Reads: Default model, providing high availability and throughput but may return stale data.
• Strongly Consistent Reads: Ensures reads return the most recent write, with higher latency and lower throughput.

The choice depends on application requirements for data freshness versus availability and performance.

6. How do you monitor and optimize costs in AWS?

Monitoring and optimizing costs in AWS involves using tools and best practices for efficient resource utilization:

• AWS Cost Explorer: Visualize and analyze spending.
• AWS Budgets: Set custom cost and usage budgets with alerts.
• AWS CloudWatch: Monitor resources and set alarms for unexpected changes.
• AWS Trusted Advisor: Provides recommendations for cost optimization.

Strategies for cost optimization include:

• Right-sizing: Adjust resource sizes to match needs.
• Reserved Instances and Savings Plans: Purchase for predictable workloads to save costs.
• Auto Scaling: Adjust instances based on demand.
• Spot Instances: Use for non-critical workloads at a discount.
• Resource Tagging: Categorize resources for cost management.

7. Write a CloudWatch alarm to monitor CPU utilization of an EC2 instance.

Amazon CloudWatch provides monitoring and management for AWS resources. To monitor CPU utilization of an EC2 instance, create a CloudWatch alarm:

import boto3

cloudwatch = boto3.client('cloudwatch')

cloudwatch.put_metric_alarm(
    AlarmName='EC2_CPU_Utilization_Alarm',
    ComparisonOperator='GreaterThanThreshold',
    EvaluationPeriods=1,
    MetricName='CPUUtilization',
    Namespace='AWS/EC2',
    Period=300,
    Statistic='Average',
    Threshold=70.0,
    ActionsEnabled=False,
    AlarmActions=[
        'arn:aws:sns:us-west-2:123456789012:my-sns-topic'
    ],
    AlarmDescription='Alarm when server CPU exceeds 70%',
    Dimensions=[
        {
            'Name': 'InstanceId',
            'Value': 'i-0123456789abcdef0'
        },
    ],
    Unit='Percent'
)

8. Explain the process of migrating an on-premises database to AWS RDS.

Migrating an on-premises database to AWS RDS involves:

1. Assessment and Planning: Evaluate the current environment and determine the target RDS configuration.
2. Schema Conversion: Use AWS Schema Conversion Tool (SCT) for schema compatibility.
3. Data Migration: Use AWS Database Migration Service (DMS) for data transfer and replication.
4. Testing: Validate data integrity and application performance.
5. Cutover: Switch the application to the new RDS instance.
6. Optimization and Monitoring: Use CloudWatch for performance tracking and adjustments.

9. How do you implement cross-account access in AWS?

Cross-account access in AWS allows resources in one account to access resources in another securely using IAM roles and policies:

• Create an IAM Role in the Target Account: Define permissions and a trust policy for the source account.
• Trust Policy: Specifies which accounts can assume the role.
• AssumeRole API Call: Use AWS STS in the source account to obtain temporary credentials.
• Resource Policies: Optionally, grant access to specific resources without assuming a role.

Example trust policy:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {
        "AWS": "arn:aws:iam::SOURCE_ACCOUNT_ID:root"
      },
      "Action": "sts:AssumeRole"
    }
  ]
}

In the source account, use the AssumeRole API:

import boto3

client = boto3.client('sts')

response = client.assume_role(
    RoleArn='arn:aws:iam::TARGET_ACCOUNT_ID:role/ROLE_NAME',
    RoleSessionName='SessionName'
)

credentials = response['Credentials']

10. Write a Terraform configuration to deploy a simple web server on EC2.

To deploy a simple web server on an EC2 instance using Terraform:

provider "aws" {
  region = "us-west-2"
}

resource "aws_instance" "web" {
  ami           = "ami-0c55b159cbfafe1f0" # Amazon Linux 2 AMI
  instance_type = "t2.micro"

  user_data = <<-EOF
              #!/bin/bash
              yum update -y
              yum install -y httpd
              systemctl start httpd
              systemctl enable httpd
              echo "Hello, World!" > /var/www/html/index.html
              EOF

  tags = {
    Name = "web_server"
  }
}

This configuration specifies the AWS region, defines the EC2 instance, and includes a user data script to install and start Apache.

11. Explain the steps to set up a CI/CD pipeline using AWS CodePipeline and CodeBuild.

To set up a CI/CD pipeline using AWS CodePipeline and CodeBuild:

1. Create a Source Stage: Use CodeCommit, GitHub, or S3 as the source repository.
2. Create a Build Stage: Use CodeBuild to compile code, run tests, and produce artifacts.
3. Create a Deploy Stage: Use CodeDeploy, Elastic Beanstalk, or CloudFormation for deployment.
4. Configure Pipeline Settings: Define the pipeline structure and permissions.
5. Monitor and Manage the Pipeline: Use the AWS Management Console, CLI, or SDKs for monitoring and management.

12. What is AWS Global Accelerator and how does it improve application performance?

AWS Global Accelerator directs traffic to optimal endpoints over the AWS global network, providing static IP addresses as entry points. Benefits include:

• Improved Performance: Reduces latency by routing traffic to the nearest AWS edge location.
• High Availability: Monitors endpoint health and reroutes traffic to healthy endpoints.
• Global Reach: Offers a single entry point for global application management.
• Security: Uses static IPs to reduce DDoS attack risks.

13. Discuss the tools available in AWS for cost management and optimization.

AWS offers tools for cost management and optimization:

• AWS Cost Explorer: Visualize and analyze spending.
• AWS Budgets: Set custom budgets with alerts.
• AWS Cost and Usage Report (CUR): Provides detailed usage and cost data.
• AWS Trusted Advisor: Offers optimization recommendations.
• AWS Compute Optimizer: Analyzes resources for optimal configurations.
• AWS Savings Plans and Reserved Instances: Commit to service usage for discounts.

14. What are some security best practices for AWS environments?

Security best practices for AWS environments include:

• Use IAM Roles and Policies: Implement least privilege access.
• Enable Multi-Factor Authentication (MFA): Add an extra security layer.
• Regularly Rotate Credentials: Minimize risk of compromised credentials.
• Monitor and Audit: Use CloudTrail and AWS Config for activity logging.
• Encrypt Data: Use KMS for data encryption.
• Implement Network Security: Use VPC with security groups and NACLs.
• Regularly Update and Patch: Protect against vulnerabilities.
• Backup and Disaster Recovery: Ensure data availability and integrity.

15. Explain the importance of understanding AWS service limits and how they impact your applications.

AWS service limits, or quotas, are the maximum resources or operations you can use for a service. They ensure platform stability and reliability. Understanding these limits is important for:

• Scalability: Helps design applications to scale efficiently.
• Performance: Prevents throttling and performance degradation.
• Cost Management: Avoids over-provisioning of resources.
• Compliance and Security: Maintains a manageable security posture.

AWS provides tools like Trusted Advisor and Service Quotas to monitor and request limit increases. Implement monitoring and alerting to stay within limits.