15 AWS Interview Questions for Hiring AWS Developers

Hiring skilled AWS developers is crucial for organizations leveraging cloud computing to build scalable, secure, and cost-effective applications. AWS offers a vast ecosystem of services, and an ideal candidate should demonstrate expertise in designing, deploying, and managing cloud-based applications. Below is a set of 15 insightful interview questions to assess an AWS developer’s technical proficiency and practical experience.

AWS Interview Questions

1. What are the key components of AWS and how do they interact?

Question Explanation:

AWS provides a wide range of cloud services categorized into compute, storage, networking, security, and management. Understanding how these components interact is crucial for building scalable and efficient cloud applications. This AWS Interview question will assist with further knowledge.

Expected Answer:

AWS consists of several core services that interact to provide a fully managed cloud environment. Some key components include:

• Compute: Amazon EC2 (Elastic Compute Cloud) provides virtual servers, while AWS Lambda enables serverless execution of code.
• Storage: Amazon S3 (Simple Storage Service) for object storage, EBS (Elastic Block Store) for persistent disk storage, and Glacier for archival storage.
• Networking: Amazon VPC (Virtual Private Cloud) allows users to define their own network configurations, while Route 53 provides DNS management.
• Databases: Amazon RDS (Relational Database Service) supports managed databases, DynamoDB for NoSQL, and Redshift for data warehousing.
• Security & IAM: AWS IAM (Identity and Access Management) manages user permissions, AWS WAF for web application security, and AWS Shield for DDoS protection.

These services interact by integrating via IAM roles, API gateways, event-driven architectures (e.g., S3 triggering Lambda functions), and networking configurations (e.g., EC2 instances in VPCs accessing RDS databases).

Evaluating Responses:

A strong candidate should not only list AWS services but also explain their interactions. Look for examples like how EC2 instances access S3 using IAM roles or how Lambda functions process events from SQS or DynamoDB streams.

2. Explain the differences between EC2 instance types and their use cases.

Question Explanation:

Amazon EC2 provides various instance types optimized for different workloads. Understanding these types ensures cost-effective and efficient resource allocation. This AWS Interview question will assist with further knowledge.

Expected Answer:

EC2 instances are categorized into different families based on performance characteristics:

• General Purpose (T, M series): Balanced compute, memory, and networking, suitable for web servers and application hosting.
• Compute Optimized (C series): High CPU performance, best for data analysis, game servers, and high-performance computing.
• Memory Optimized (R, X series): More RAM, suited for in-memory databases like Redis or applications needing large caches.
• Storage Optimized (I, D series): High-speed disk storage, best for NoSQL databases and real-time big data processing.
• Accelerated Computing (P, G series): Equipped with GPUs for AI, machine learning, and video rendering.

Example: If a workload requires high computational power, a C5 instance is ideal. For a database-heavy application, an R5 instance would be a better choice.

Evaluating Responses:

Candidates should explain why different instance types are used in real scenarios. A strong answer will include specific workload examples and mention cost considerations.

3. How would you set up auto-scaling for a web application in AWS?

Question Explanation:

Auto-scaling ensures that a web application can dynamically adjust to changing traffic loads, improving availability and cost efficiency. This AWS Interview question will assist with further knowledge.

Expected Answer:

Setting up auto-scaling for a web application involves the following steps:

1. Create an Amazon EC2 Auto Scaling Group: Define the minimum, desired, and maximum number of instances.
2. Attach an Elastic Load Balancer (ELB): Distribute traffic across multiple instances to ensure availability.
3. Define Scaling Policies: Use metrics from Amazon CloudWatch (e.g., CPU utilization) to automatically add or remove instances.
4. Configure Health Checks: Ensure that unhealthy instances are terminated and replaced.
5. Use Spot or Reserved Instances (Optional): Optimize cost by selecting appropriate EC2 pricing models.

Example: A web application experiencing high traffic during business hours and lower traffic at night can have a policy to scale between 2 to 10 EC2 instances based on CPU utilization exceeding 60%.

Evaluating Responses:

A good answer should demonstrate understanding of CloudWatch metrics, ELB integration, and cost efficiency. Candidates should also mention best practices like grace periods, instance warm-up times, and monitoring for scaling events.

4. What is the difference between AWS Lambda and EC2, and when should you use each?

Question Explanation:

AWS Lambda and EC2 both provide compute resources but serve different purposes. Understanding when to use each is critical for cost optimization and architectural decisions. This AWS Interview question will assist with further knowledge.

Expected Answer:

• AWS Lambda: Serverless, event-driven compute service where code runs in response to triggers. It automatically scales and charges only for execution time.
• Amazon EC2: Provides virtual servers where users have full control over the OS, storage, and networking. Requires manual scaling and ongoing management.

Use Cases:

• Use AWS Lambda when running short-lived functions, processing S3 events, API Gateway requests, or automating tasks. Example: Resizing images uploaded to S3.
• Use EC2 when you need persistent workloads, full OS control, custom software installations, or high-performance computing. Example: Hosting a web application backend.

Evaluating Responses:

Candidates should highlight scalability, pricing differences, and operational overhead. The best answers will include specific real-world scenarios demonstrating when to use each service effectively.

5. How does AWS IAM (Identity and Access Management) enhance security in AWS?

Question Explanation:

AWS IAM is a fundamental security service that controls access to AWS resources. Understanding IAM helps ensure secure user authentication, authorization, and access management. This AWS Interview question will assist with further knowledge.

Expected Answer:

AWS IAM enhances security through the following key features:

• Users, Groups, and Roles: IAM allows you to create users, assign them to groups, and define roles to manage permissions.
• Policies and Permissions: Policies are JSON-based documents that define access rules. They can be attached to users, groups, or roles to enforce least privilege access.
• Multi-Factor Authentication (MFA): Adding MFA increases security by requiring a second authentication factor.
• Federated Access and Single Sign-On (SSO): IAM supports federated identity providers like Google, Okta, and Active Directory.
• Temporary Security Credentials: AWS Security Token Service (STS) provides short-term credentials for secure, temporary access to resources.

Example: To allow an EC2 instance to access an S3 bucket securely, you create an IAM role with an S3 access policy and attach it to the EC2 instance, preventing the need for hardcoded credentials.

Evaluating Responses:

Candidates should explain how IAM supports principle of least privilege, the role of policies, and how it integrates with AWS services. Strong responses may include real-world IAM policies or mention AWS Organizations for multi-account management.

6. Can you describe how to configure and use AWS CloudFront for content delivery?

Question Explanation:

Amazon CloudFront is AWS’s Content Delivery Network (CDN) that accelerates content delivery worldwide. Understanding how to configure it ensures better performance and lower latency for applications. This AWS Interview question will assist with further knowledge.

Expected Answer:

To configure AWS CloudFront:

1. Create a CloudFront Distribution: Choose an origin (e.g., S3 bucket, EC2, or an ALB).
2. Set Up Behaviors: Define caching rules, allowed HTTP methods, and security settings (e.g., HTTPS enforcement).
3. Configure Edge Locations: CloudFront distributes content across AWS edge locations to reduce latency.
4. Enable Caching & Compression: Use TTL (Time-to-Live) settings for efficient caching and enable Gzip or Brotli compression.
5. Restrict Access (Optional): Use signed URLs or signed cookies to control access to restricted content.
6. Monitor Performance: Use AWS CloudWatch and AWS Shield (for DDoS protection) to track usage and security metrics.

Example: A video streaming platform can use CloudFront with an S3 bucket as an origin, ensuring global delivery while reducing load on the origin server.

Evaluating Responses:

A good response should include caching strategies, security mechanisms (signed URLs, WAF), and performance benefits. Strong candidates might also mention custom SSL certificates or Lambda@Edge for advanced request handling.

7. What strategies can be used to optimize AWS costs?

Question Explanation:

AWS provides various pricing models and cost management tools. Understanding how to optimize costs ensures efficient cloud spending. This AWS Interview question will assist with further knowledge.

Expected Answer:

AWS cost optimization strategies include:

1. Right-Sizing Resources: Choose appropriate instance types and sizes to avoid overprovisioning. Use AWS Compute Optimizer for recommendations.
2. Use Reserved or Spot Instances: Reserved Instances (RI) offer up to 75% savings for long-term commitments. Spot Instances provide discounted compute power for fault-tolerant workloads.
3. Implement Auto Scaling: Scale resources dynamically based on demand to reduce unused capacity.
4. Leverage AWS Savings Plans: Commit to a one- or three-year plan for lower pricing across EC2, Lambda, and Fargate.
5. Use S3 Lifecycle Policies & Storage Classes: Move infrequently accessed data to S3 Glacier or S3 Infrequent Access for cost savings.
6. Monitor and Analyze Costs: Use AWS Cost Explorer, AWS Budgets, and AWS Trusted Advisor to track and optimize spending.
7. Turn Off Unused Resources: Identify and shut down idle EC2 instances, RDS databases, and Elastic Load Balancers.
8. Use Serverless Architectures: AWS Lambda and Fargate eliminate the need for always-on compute resources, reducing costs.

Example: A startup reducing cloud costs by switching from On-Demand EC2 to Reserved Instances and moving archival data to S3 Glacier can save thousands per year.

Evaluating Responses:

Candidates should demonstrate awareness of pricing models, automation tools, and best practices. The best answers will include practical examples and AWS-specific cost management tools.

8. How does Amazon RDS differ from DynamoDB, and when would you choose one over the other?

Question Explanation:

Amazon RDS (Relational Database Service) and DynamoDB serve different database needs. Understanding their differences helps in selecting the right solution for a given use case. This AWS Interview question will assist with further knowledge.

Expected Answer:

Amazon RDS (Relational Database Service):

• Managed relational database service supporting MySQL, PostgreSQL, SQL Server, Oracle, and MariaDB.
• Suitable for applications requiring structured data, transactions, and complex queries.
• Supports ACID compliance and SQL-based queries.
• Requires instance provisioning and maintenance (backups, scaling).

Amazon DynamoDB:

• Fully managed NoSQL database optimized for key-value and document storage.
• Supports millisecond latency at any scale using SSD storage.
• Ideal for highly scalable applications, IoT, gaming leaderboards, and real-time analytics.
• Serverless (scales automatically with demand).

When to Choose Each:

• Use RDS when you need structured data, complex relationships, and transactions (e.g., banking, CRM).
• Use DynamoDB when you need fast, scalable, and schema-less data storage (e.g., real-time messaging, IoT, recommendation engines).

Example: A financial application requiring complex SQL queries would use RDS, while a social media platform tracking user likes and comments would use DynamoDB for fast performance.

Evaluating Responses:

Candidates should articulate ACID compliance vs NoSQL flexibility, scalability differences, and real-world use cases. The best answers may discuss read/write throughput pricing or multi-region replication in DynamoDB.

9. What are the key differences between S3 storage classes, and how do they impact cost and performance?

Question Explanation:

Amazon S3 offers multiple storage classes designed for different use cases. Understanding these classes helps optimize cost while ensuring performance and durability. This AWS Interview question will assist with further knowledge.

Expected Answer:

S3 provides several storage classes with different pricing and performance characteristics:

• S3 Standard: High availability (99.99%) and durability (99.999999999%, or 11 nines). Best for frequently accessed data.
• S3 Intelligent-Tiering: Automatically moves data between frequent and infrequent access tiers based on usage patterns, reducing costs.
• S3 Standard-IA (Infrequent Access): Lower cost than Standard, but retrieval fees apply. Suitable for less frequently accessed data.
• S3 One Zone-IA: Cheaper than Standard-IA but stored in a single AWS Availability Zone, making it less durable.
• S3 Glacier: Low-cost storage for archival data, with retrieval times ranging from minutes to hours.
• S3 Glacier Deep Archive: Lowest-cost option, with retrieval times of 12 hours or more.

Cost and Performance Impact:

• Frequently accessed data (e.g., web assets, logs) should use S3 Standard.
• Backup or disaster recovery files should use S3 Standard-IA or One Zone-IA.
• Long-term archives should use Glacier or Glacier Deep Archive to minimize costs.

Example: A video streaming company storing thumbnails for fast access uses S3 Standard, while storing older raw footage in Glacier to cut costs.

Evaluating Responses:

Look for candidates who understand trade-offs between cost, durability, and retrieval times. Strong answers will include real-world storage scenarios and mention lifecycle policies for automatic transitions.

10. Explain the purpose of AWS CloudFormation and how it helps in infrastructure management.

Question Explanation:

AWS CloudFormation enables infrastructure as code (IaC), allowing developers to define and automate AWS resources. Understanding CloudFormation is crucial for managing large-scale deployments. This AWS Interview question will assist with further knowledge.

Expected Answer:

AWS CloudFormation is a service that helps automate and manage AWS infrastructure by defining resources in a declarative JSON or YAML template. Benefits include:

• Infrastructure as Code (IaC): Define and version-control infrastructure for consistency.
• Automated Deployment: Deploy multiple resources (EC2, RDS, VPC) as a single stack.
• Rollback and Change Management: Updates can be reviewed before execution using Change Sets.
• Cross-Region and Multi-Account Deployment: Templates can be used across AWS accounts.

Example Use Case:

A DevOps team managing multi-tier applications can define a CloudFormation template to launch an EC2 Auto Scaling Group, RDS database, and IAM roles in a single deployment.

Evaluating Responses:

Look for candidates who understand version-controlled infrastructure, CloudFormation stacks, and rollback mechanisms. Strong responses may mention Terraform as an alternative IaC tool.

11. How would you implement a serverless architecture using AWS services?

Question Explanation:

Serverless computing reduces operational overhead by eliminating infrastructure management. Understanding AWS serverless services is essential for building scalable applications. This AWS Interview question will assist with further knowledge.

Expected Answer:

A serverless architecture in AWS typically consists of:

• Compute: AWS Lambda executes functions in response to events (S3 uploads, API Gateway requests).
• API Management: Amazon API Gateway provides REST/GraphQL APIs to interact with serverless backends.
• Storage: Amazon S3 (object storage) and DynamoDB (NoSQL database) handle data persistence.
• Messaging & Event-Driven Processing:
  • Amazon SQS & SNS for queuing and notifications.
  • Amazon EventBridge for event-driven workflows.
  • AWS Step Functions for orchestrating microservices.
• Security: AWS IAM for role-based access control, AWS WAF for application security.

Example Implementation:

A photo-sharing application could:

1. Use API Gateway to handle requests.
2. Store uploaded images in S3.
3. Trigger a Lambda function to resize images and save them to a different S3 bucket.
4. Store metadata in DynamoDB.

Evaluating Responses:

Candidates should discuss stateless computing, event-driven workflows, and cost advantages. The best responses will mention cold starts, monitoring with AWS X-Ray, and avoiding vendor lock-in.

12. Describe how VPC (Virtual Private Cloud) networking works in AWS.

Question Explanation:

Amazon VPC allows users to create isolated network environments within AWS. Understanding VPC is crucial for setting up secure, scalable architectures. This AWS Interview question will assist with further knowledge.

Expected Answer:

An AWS VPC (Virtual Private Cloud) is a logically isolated network within AWS where users can define their own:

• Subnets: Divide the VPC into public and private subnets.
• Route Tables: Control how traffic flows within the VPC and to the internet.
• Internet Gateway (IGW): Enables public internet access for instances in public subnets.
• NAT Gateway (NGW): Allows private subnets to access the internet while keeping resources hidden.
• Security Groups & Network ACLs: Define firewall rules at the instance and subnet levels.

Example Use Case:

A web application architecture might have:

• A public subnet with an EC2 web server behind an Elastic Load Balancer.
• A private subnet with an RDS database, accessible only from the web tier.
• A NAT Gateway to allow outgoing traffic for security patches.

Evaluating Responses:

Look for explanations of subnet segmentation, route table management, and security best practices. Advanced responses may discuss VPC Peering, Transit Gateway, or hybrid connectivity (VPN, Direct Connect).

13. What is AWS Step Functions, and how does it help in workflow automation?

Question Explanation:

AWS Step Functions is a serverless workflow orchestration service that simplifies complex, multi-step processes by coordinating AWS services and custom logic. Understanding Step Functions is crucial for automating workflows and microservices orchestration. This AWS Interview question will assist with further knowledge.

Expected Answer:

AWS Step Functions allows developers to create state machines that define workflows as a series of steps, executing functions in order with conditional logic.

Key Features:

• Orchestration: Manages the execution of AWS Lambda functions, ECS tasks, and more.
• State Management: Maintains workflow progress and automatically retries failed steps.
• Parallel Execution: Supports branching logic to run multiple tasks simultaneously.
• Error Handling & Retries: Automatically retries failed steps based on defined policies.
• Visual Workflow Designer: Provides a graphical representation of the workflow.

Example Use Case:
A data processing pipeline could use Step Functions to:

1. Retrieve data from S3.
2. Run transformations using AWS Lambda.
3. Store processed data in DynamoDB.
4. Notify users via SNS upon completion.

Evaluating Responses:

A strong answer should highlight state management, fault tolerance, and integration with AWS services. Advanced candidates may mention Express Workflows for high-throughput scenarios.

14. How would you implement logging and monitoring for an AWS application using CloudWatch and AWS X-Ray?

Question Explanation:

Logging and monitoring are essential for diagnosing issues, tracking performance, and ensuring security. AWS CloudWatch and AWS X-Ray provide monitoring and tracing capabilities for AWS applications. This AWS Interview question will assist with further knowledge.

Expected Answer:

• Amazon CloudWatch collects and monitors logs, metrics, and alarms for AWS services.
  • CloudWatch Logs: Stores logs from EC2, Lambda, RDS, and more.
  • CloudWatch Metrics: Monitors CPU usage, memory, request latency, etc.
  • CloudWatch Alarms: Sends notifications or triggers auto-scaling actions based on thresholds.
• AWS X-Ray provides distributed tracing for debugging complex applications.
  • Tracks requests across services (e.g., API Gateway → Lambda → DynamoDB).
  • Identifies latency bottlenecks and errors in microservices architectures.

Implementation Example:
For a serverless web application:

1. Enable CloudWatch Logs for API Gateway and Lambda functions.
2. Use X-Ray to trace HTTP requests from API Gateway through backend services.
3. Set up CloudWatch Alarms for high error rates.

Evaluating Responses:

Look for a solid understanding of CloudWatch Logs, Alarms, Metrics, and X-Ray tracing. Strong candidates may mention Log Insights for querying logs or AWS Config for compliance monitoring.

15. What best practices should be followed when designing a high-availability system on AWS?

Question Explanation:

High availability (HA) ensures applications remain operational even in case of failures. AWS provides multiple services and architectures to achieve HA. This AWS Interview question will assist with further knowledge.

Expected Answer:

To design a highly available system, follow these best practices:

1. Multi-AZ Deployment:
   • Use RDS Multi-AZ for database failover.
   • Deploy EC2 instances across multiple Availability Zones (AZs).
2. Auto Scaling & Load Balancing:
   • Use an Elastic Load Balancer (ELB) to distribute traffic.
   • Implement Auto Scaling Groups (ASG) to dynamically adjust capacity.
3. Data Redundancy & Backup:
   • Store data in S3 (which has 99.999999999% durability).
   • Enable point-in-time recovery for RDS and DynamoDB backups.
4. Failover & Disaster Recovery:
   • Use AWS Route 53 health checks and failover routing.
   • Consider AWS Global Accelerator for low-latency global failover.
5. Decouple Components:
   • Use SQS, SNS, and EventBridge to prevent dependency failures.
6. Monitor & Automate Recovery:
   • Use CloudWatch Alarms to trigger recovery actions.
   • Implement AWS Lambda for self-healing automation.

Example Use Case:
A multi-tier web application could use:

• ALB + Auto Scaling across multiple AZs for the web tier.
• RDS Multi-AZ for database failover.
• S3 + CloudFront for static content delivery.

Evaluating Responses:

Candidates should discuss fault tolerance, redundancy, scalability, and automation. Advanced responses may include multi-region failover and chaos engineering techniques.

AWS Interview Questions Conclusion

Assessing AWS developers requires evaluating their understanding of cloud services, security, cost optimization, and architectural best practices. These 15 questions help identify candidates who can efficiently design and manage AWS solutions, ensuring optimal performance and scalability for your applications.