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Top 32 AWS Interview Questions and Answers For 2024

A complete guide to exploring the basic, intermediate, and advanced AWS interview questions, along with questions based on real-world situations. It covers all the areas, ensuring a well-rounded preparation strategy.
Feb 2024  · 15 min read

Navigating through the complex landscape of Amazon Web Services (AWS) can be tough, especially when getting ready for an important interview.

This journey can feel even more daunting for junior data practitioners who are just starting their careers in the vast field of data science, as well as for seasoned data experts who are always looking for the latest updates to enhance their skills.

The core of this guide is to make the AWS interview process easier to understand by offering a carefully selected list of interview questions and answers. This range includes everything from the basic principles that form the foundation of AWS's extensive ecosystem to the detailed, scenario-based questions that test your deep understanding and practical use of AWS services.

Whether you're at the beginning of your data career or are an experienced professional, this article aims to provide you with the knowledge and confidence needed to tackle any AWS interview question. By exploring basic, intermediate, and advanced AWS interview questions, along with questions based on real-world situations, this guide aims to cover all the important areas, ensuring a well-rounded preparation strategy.

Why AWS?

Before exploring the questions and answers, it is important to understand why it is worth considering the AWS Cloud as the go-to platform.

The following graphic provides the worldwide market share of leading cloud infrastructure service providers for the second quarter (Q2) of 2023. Below is a breakdown of the market shares depicted:

  • Amazon Web Services (AWS) has the largest market share at 32%.
  • Microsoft Azure follows with 22%.
  • Google Cloud holds 11% of the market.
  • Alibaba Cloud has a 4% share.
  • Both IBM Cloud and Salesforce each have 3%.
  • Oracle and Tencent Cloud are at the bottom, with 2% each.


Source (Statista)

The graphic also includes a note that the data includes platform as a service (PaaS) and infrastructure as a service (IaaS) as well as hosted private cloud services. Additionally, there's a mention that the cloud infrastructure service revenues in Q2 2023 amounted to $65 billion.

Amazon Web Services (AWS) continues to be the dominant player in the cloud market as of Q2 2023, holding a significant lead over its closest competitor, Microsoft Azure.

AWS's leadership in the cloud market highlights its importance for upskilling and offers significant career advantages due to its wide adoption and the value placed on AWS skills in the tech industry.

Our cheat sheet AWS, Azure and GCP Service comparison for Data Science & AI provides a comparison of the main services needed for data and AI-related work from data engineering to data analysis and data science to creating data applications.

Basic AWS Interview Questions

Starting with the fundamentals, this section introduces basic AWS interview questions essential for building a foundational understanding. It's tailored for those new to AWS or needing a refresher, setting the stage for more detailed exploration later.

1. What is cloud computing?

Cloud computing provides on-demand access to IT resources like compute, storage, and databases over the internet. Users pay only for what they use instead of owning physical infrastructure.

Cloud enables accessing technology services flexibly as needed without big upfront investments. Leading providers like AWS offer a wide range of cloud services via the pay-as-you-go consumption model. Our AWS Cloud Concepts course covers many of these basics.

2. What is the problem with the traditional IT approach compared to using the Cloud?

Multiple industries are moving away from traditional IT to adopt cloud infrastructures for multiple reasons. This is because the Cloud approach provides greater business agility, faster innovation, flexible scaling and lower total cost of ownership compared to traditional IT. Below are some of the characteristics that differentiate them:

Traditional IT

Cloud computing

  • Requires large upfront capital expenditures
  • Limited ability to scale based on demand
  • Lengthy procurement and provisioning cycles
  • Higher maintenance overhead
  • Limited agility and innovation
  • No upfront infrastructure investment
  • Pay-as-you-go based on usage
  • Rapid scaling to meet demand
  • Reduced maintenance overhead
  • Faster innovation and new IT initiatives
  • Increased agility and responsiveness

3. How many types of deployment models exist in the cloud?

There are three different types of deployment models in the cloud, and they are illustrated below:

  • Private cloud: this type of service is used by a single organization and is not exposed to the public. It is adapted to organizations using sensitive applications.
  • Public cloud: these cloud resources are owned and operated by third-party cloud services like Amazon Web Services, Microsoft Azure, and all those mentioned in the AWS market share section.
  • Hybrid cloud: this is the combination of both private and public clouds. It is designed to keep some servers on-premises while extending the remaining capabilities to the cloud. Hybrid cloud provides flexibility and cost-effectiveness of the public cloud.

4. What are the five characteristics of cloud computing?

Cloud computing is composed of five main characteristics, and they are illustrated below:

  • On-demand self-service: Users can provision cloud services as needed without human interaction with the service provider.
  • Broad network access: Services are available over the network and accessed through standard mechanisms like mobile phones, laptops, and tablets.
  • Multi-tenacy and resource pooling: Resources are pooled to serve multiple customers, with different virtual and physical resources dynamically assigned based on demand.
  • Rapid elasticity and scalability: Capabilities can be elastically provisioned and scaled up or down quickly and automatically to match capacity with demand.
  • Measured service: Resource usage is monitored, controlled, reported, and billed transparently based on utilization. Usage can be managed, controlled, and reported, providing transparency for the provider and consumer.

5. What are the main types of Cloud Computing?

There are three main types of cloud computing: IaaS, PaaS, and SaaS

  • Infrastructure as a Service (IaaS): Provides basic building blocks for cloud IT like compute, storage, and networking that users can access on-demand without needing to manage the underlying infrastructure. Examples: AWS EC2, S3, VPC.
  • Platform as a Service (PaaS): Provides a managed platform or environment for developing, deploying, and managing cloud-based apps without needing to build the underlying infrastructure. Examples: AWS Elastic Beanstalk, Heroku
  • Software as a Service (SaaS): Provides access to complete end-user applications running in the cloud that users can use over the internet. Users don't manage infrastructure or platforms. Examples: AWS Simple Email Service, Google Docs, Salesforce CRM.

You can explore these in more detail in our Understanding Cloud Computing course.

6. What is Amazon EC2, and what are its main uses?

Amazon EC2 (Elastic Compute Cloud) provides scalable virtual servers called instances in the AWS Cloud. It is used to run a variety of workloads flexibly and cost-effectively. Some of its main uses are illustrated below:

  • Host websites and web applications
  • Run backend processes and batch jobs
  • Implement hybrid cloud solutions
  • Achieve high availability and scalability
  • Reduce time to market for new use cases

7. What is Amazon S3, and why is it important?

Amazon Simple Storage Service (S3) is a versatile, scalable, and secure object storage service. It serves as the foundation for many cloud-based applications and workloads. Below are a few features highlighting its importance:

  • Durable with 99.999999999% durability and 99.99% availability, making it suitable for critical data.
  • Supports robust security features like access policies, encryption, VPC endpoints.
  • Integrates seamlessly with other AWS services like Lambda, EC2, EBS, just to name a few.
  • Low latency and high throughput make it ideal for big data analytics, mobile applications, media storage and delivery.
  • Flexible management features for monitoring, access logs, replication, versioning, lifecycle policies.
  • Backed by the AWS global infrastructure for low latency access worldwide.

8. Explain the concept of ‘Regions’ and ‘Availability Zones’ in AWS

  • AWS Regions correspond to separate geographic locations where AWS resources are located. Businesses choose regions close to their customers to reduce latency, and cross-region replication provides better disaster recovery.
  • Availability zones consist of one or more discrete data centers with redundant power, networking, and connectivity. They allow the deployment of resources in a more fault-tolerant way.

Our course AWS Cloud Concepts provides readers with a complete guide to learning about AWS’s main core services, best practices for designing AWS applications, and the benefits of using AWS for businesses.

AWS Interview Questions for Intermediate and Experienced

AWS DevOps interview questions

Moving to specialized roles, the emphasis here is on how AWS supports DevOps practices. This part examines the automation and optimization of AWS environments, challenging individuals to showcase their skills in leveraging AWS for continuous integration and delivery.

9. How do you use AWS CodePipeline to automate a CI/CD pipeline for a multi-tier application?

CodePipeline can be used to automate the flow from code check-in to build, test, and deployment across multiple environments to streamline the delivery of updates while maintaining high standards of quality.

The following steps can be followed to automate a CI/CD pipeline:

  • Create a Pipeline: Start by creating a pipeline in AWS CodePipeline, specifying your source code repository (e.g., GitHub, AWS CodeCommit).
  • Define Build Stage: Connect to a build service like AWS CodeBuild to compile your code, run tests, and create deployable artifacts.
  • Setup Deployment Stages: Configure deployment stages for each tier of your application. Use AWS CodeDeploy to automate deployments to Amazon EC2 instances, AWS Elastic Beanstalk for web applications, or AWS ECS for containerized applications.
  • Add Approval Steps (Optional): For critical environments, insert manual approval steps before deployment stages to ensure quality and control.
  • Monitor and Iterate: Monitor the pipeline's performance and adjust as necessary. Utilize feedback and iteration to continuously improve the deployment process.

10. What key factors should be considered in designing a deployment solution on AWS to effectively provision, configure, deploy, scale, and monitor applications?

Creating a well-architected AWS deployment involves tailoring AWS services to your app's needs, covering compute, storage, and database requirements. This process, complicated by AWS's vast service catalog, includes several crucial steps:

  • Provisioning: Set up essential AWS infrastructure such as EC2, VPC, subnets or managed services like S3, RDS, CloudFront for underlying applications.

  • Configuring: Adjust your setup to meet specific requirements related to the environment, security, availability, and performance.

  • Deploying: Efficiently roll out or update app components, ensuring smooth version transitions.

  • Scaling: Dynamically modify resource allocation based on predefined criteria to handle load changes.

  • Monitoring: Keep track of resource usage, deployment outcomes, app health, and logs to ensure everything runs as expected.

11. What is Infrastructure as a Code? Describe in your own words

Infrastructure as Code (IaC) is a method of managing and provisioning computer data centers through machine-readable definition files, rather than physical hardware configuration or interactive configuration tools.

Essentially, it allows developers and IT operations teams to automatically manage, monitor, and provision resources through code, rather than manually setting up and configuring hardware.

Also, IaC enables consistent environments to be deployed rapidly and scalably by codifying infrastructure, thereby reducing human error and increasing efficiency.

12. What is your approach to handling continuous integration and deployment in AWS DevOps?

In AWS DevOps, continuous integration and deployment can be managed by utilizing AWS Developer Tools. Begin by storing and versioning your application's source code with these tools.

Then, leverage services like AWS CodePipeline for orchestrating the build, test, and deployment processes. CodePipeline serves as the backbone, integrating with AWS CodeBuild for compiling and testing code, and AWS CodeDeploy for automating the deployment to various environments. This streamlined approach ensures efficient, automated workflows for continuous integration and delivery.

13. How does Amazon ECS benefit AWS DevOps?

Amazon ECS is a scalable container management service that simplifies running Docker containers on EC2 instances through a managed cluster, enhancing application deployment and operation.

14. Why might ECS be preferred over Kubernetes?

ECS offers greater flexibility, scalability, and simplicity in implementation compared to Kubernetes, making it a preferred choice for some deployments.

AWS solution architect interview questions

For solution architects, the focus is on designing AWS solutions that meet specific requirements. This segment tests the ability to create scalable, efficient, and cost-effective systems using AWS, highlighting architectural best practices.

15. What is the role of an AWS solution architect?

AWS Solutions Architects design and oversee applications on AWS, ensuring scalability and optimal performance. They guide developers, system administrators, and customers on utilizing AWS effectively for their business needs and communicate complex concepts to both technical and non-technical stakeholders.

16. What are the key security best practices for AWS EC2?

Essential EC2 security practices include using IAM for access management, restricting access to trusted hosts, minimizing permissions, disabling password-based logins for AMIs, and implementing multi-factor authentication for enhanced security.

17. What is AWS VPC and its purpose?

Amazon VPC enables the deployment of AWS resources within a virtual network that is architecturally similar to a traditional data center network, offering the advantage of AWS's scalable infrastructure.

18. What are the strategies to create a highly available and fault-tolerant AWS architecture for critical web applications?

Building a highly available and fault-tolerant architecture on AWS involves several strategies to reduce the impact of failure and ensure continuous operation. Key principles include:

  • Implementing redundancy across system components to eliminate single points of failure
  • Using load balancing to distribute traffic evenly and ensure optimal performance
  • Setting up automated monitoring for real-time failure detection and response. Systems should be designed for scalability to handle varying loads, with a distributed architecture to enhance fault tolerance.
  • Employing fault isolation, regular backups, and disaster recovery plans are essential for data protection and quick recovery.
  • Additionally, designing for graceful degradation maintains functionality during outages, while continuous testing and deployment practices improve system reliability.

19. Explain how you would choose between Amazon RDS, Amazon DynamoDB, and Amazon Redshift for a data-driven application.

Choosing between Amazon RDS, DynamoDB, and Redshift for a data-driven application depends on your specific needs:

  • Amazon RDS is ideal for applications that require a traditional relational database with standard SQL support, transactions, and complex queries.
  • Amazon DynamoDB suits applications needing a highly scalable, NoSQL database with fast, predictable performance at any scale. It's great for flexible data models and rapid development.
  • Amazon Redshift is best for analytical applications requiring complex queries over large datasets, offering fast query performance by using columnar storage and data warehousing technology.

20. What considerations would you take into account when migrating an existing on-premises application to AWS? Use an example of choice.

When moving a company's customer relationship management (CRM) software from an in-house server setup to Amazon Web Services (AWS), it's essential to follow a strategic framework similar to the one AWS suggests, tailored for this specific scenario:

  • Initial Preparation and Strategy Formation
    • Evaluate the existing CRM setup to identify limitations and areas for improvement.
    • Set clear migration goals, such as achieving better scalability, enhancing data analysis features, or cutting down on maintenance costs.
    • Identify AWS solutions required, like leveraging Amazon EC2 for computing resources and Amazon RDS for managing the database.
  • Assessment and Strategy Planning
    • Catalog CRM components to prioritize which parts to migrate first.
    • Select appropriate migration techniques, for example, moving the CRM database with AWS Database Migration Service (DMS).
    • Plan for a steady network connection during the move, potentially using AWS Direct Connect.
  • Execution and Validation
    • Map out a detailed migration strategy beginning with less critical CRM modules as a trial run.
    • Secure approval from key stakeholders before migrating the main CRM functions, employing AWS services.
    • Test the migrated CRM's performance and security on AWS, making adjustments as needed.
  • Transition to Cloud Operation
    • Switch to fully managing the CRM application in the AWS environment, phasing out old on-premises components.
    • Utilize AWS's suite of monitoring and management tools for continuous oversight and refinement.
    • Apply insights gained from this migration to inform future transitions, considering broader cloud adoption across other applications.

This approach ensures the CRM migration to AWS is aligned with strategic business objectives, maximizing the benefits of cloud computing in terms of scalability, efficiency, and cost savings.

21. Describe how you would use AWS services to implement a microservices architecture.

Implementing a microservice architecture involves breaking down a software application into small, independent services that communicate through APIs. Here’s a concise guide to setting up microservices:

  • Adopt Agile Development: Use agile methodologies to facilitate rapid development and deployment of individual microservices.
  • Embrace API-First Design: Develop APIs for microservices interaction first to ensure clear, consistent communication between services.
  • Leverage CI/CD Practices: Implement continuous integration and continuous delivery (CI/CD) to automate testing and deployment, enhancing development speed and reliability.
  • Incorporate Twelve-Factor App Principles: Apply these principles to create scalable, maintainable services that are easy to deploy on cloud platforms like AWS.
  • Choose the Right Architecture Pattern: Consider API-driven, event-driven, or data streaming patterns based on your application’s needs to optimize communication and data flow between services.
  • Leverage AWS for Deployment: Use AWS services such as container technologies for scalable microservices or serverless computing to reduce operational complexity and focus on building application logic.
  • Implement Serverless Principles: When appropriate, use serverless architectures to eliminate infrastructure management, scale automatically, and pay only for what you use, enhancing system efficiency and cost-effectiveness.
  • Ensure System Resilience: Design microservices for fault tolerance and resilience, using AWS's built-in availability features to maintain service continuity.
  • Focus on Cross-Service Aspects: Address distributed monitoring, logging, tracing, and data consistency to maintain system health and performance.
  • Review with AWS Well-Architected Framework: Use the AWS Well-Architected Tool to evaluate your architecture against AWS’s best practices, ensuring reliability, security, efficiency, and cost-effectiveness.

By carefully considering these points, teams can effectively implement a microservice architecture that is scalable, flexible, and suitable for their specific application needs, all while leveraging AWS’s extensive cloud capabilities.

22. What is the relationship between AWS Glue and AWS Lake Formation?

AWS Lake Formation builds on AWS Glue's infrastructure, incorporating its ETL capabilities, control console, data catalog, and serverless architecture. While AWS Glue focuses on ETL processes, Lake Formation adds features for building, securing, and managing data lakes, enhancing Glue's functions.

For AWS Glue interview questions, it's important to understand how Glue supports Lake Formation. Candidates should be ready to discuss Glue's role in data lake management within AWS, showing their grasp of both services' integration and functionalities in the AWS ecosystem. This demonstrates a deep understanding of how these services collaborate to process and manage data efficiently.

Advanced AWS Interview Questions and Answers

AWS data engineer interview questions

Addressing data engineers, this section dives into AWS services for data handling, including warehousing and real-time processing. It looks at the expertise required to build scalable data pipelines with AWS.

23. Describe the difference between Amazon Redshift, RDS, and S3, and when should each one be used?

  • Amazon S3 is an object storage service that provides scalable and durable storage for any amount of data. It can be used to store raw, unstructured data like log files, CSVs, images, etc.
  • Amazon Redshift is a cloud data warehouse optimized for analytics and business intelligence. It integrates with S3 and can load data stored there to perform complex queries and generate reports.
  • Amazon RDS provides managed relational databases like PostgreSQL, MySQL, etc. It can power transactional applications that need ACID-compliant databases with features like indexing, constraints, etc.

24. Describe a scenario where you would use Amazon Kinesis over AWS Lambda for data processing. What are the key considerations?

Kinesis can be used to handle large amounts of streaming data and allows reading and processing the streams with consumer applications.

Some of the key considerations are illustrated below:

  • Data volume: Kinesis can handle up to megabytes per second of data vs Lambda's limit of 6MB per invocation, which is useful for high throughput streams.
  • Streaming processing: Kinesis consumers can continuously process data in real-time as it arrives vs Lambda's batch invocations, and this helps with low latency processing.
  • Replay capability: Kinesis streams retain data for a configured period, allowing replaying and reprocessing if needed, whereas Lambda not suited for replay.
  • Ordering: Kinesis shards allow ordered processing of related records. Lambda on the other hand may process out of order.
  • Scaling and parallelism: Kinesis shards can scale to handle load. Lambda may need orchestraation.
  • Integration: Kinesis integrates well with other AWS services like Firehose, Redshift, EMR for analytics.

Furthermore, for high-volume, continuous, ordered, and replayable stream processing cases like real-time analytics, Kinesis provides native streaming support compared to Lambda's batch approach.

To learn more about data streaming, our course Streaming Data with AWS Kinesis and Lambda helps users learn how to leverage these technologies to ingest data from millions of sources and analyze them in real-time. This can help better prepare for AWS lambda interview questions.

25. What are the key differences between batch and real-time data processing? When would you choose one approach over the other for a data engineering project?

Batch processing involves collecting data over a period of time and processing it in large chunks or batches. This works well for analyzing historical, less frequent data.

Real-time streaming processing analyzes data continuously as it arrives in small increments. It allows for analyzing fresh, frequently updated data.

For a data engineering project, real-time streaming could be chosen when:

  • You need immediate insights and can't wait for a batch process to run. For example, fraud detection.
  • The data is constantly changing and analysis needs to keep up, like social media monitoring.
  • Low latency is required, like for automated trading systems.

Batch processing may be better when:

  • Historical data needs complex modeling or analysis, like demand forecasting.
  • Data comes from various sources that only provide periodic dumps.
  • Lower processing costs are critical over processing speed.

So real-time is best for rapidly evolving data needing continuous analysis, while batch suits periodically available data requiring historical modeling.

26. What is an operational data store, and how does it complement a data warehouse?

An operational data store (ODS) is a database designed to support real-time business operations and analytics. It acts as an interim platform between transactional systems and the data warehouse.

While a data warehouse contains high-quality data optimized for business intelligence and reporting, an ODS contains up-to-date, subject-oriented, integrated data from multiple sources.

Below are the key features of an ODS:

  • It provides real-time data for operations monitoring and decision-making
  • Integrates live data from multiple sources
  • It is optimized for fast queries and analytics vs long-term storage
  • ODS contains granular, atomic data vs aggregated in warehouse

An ODS and data warehouse are complementary systems. ODS supports real-time operations using current data, while the data warehouse enables strategic reporting and analysis leveraging integrated historical data. When combined, they provide a comprehensive platform for both operational and analytical needs.

AWS Scenario-based Questions

Focusing on practical application, these questions assess problem-solving abilities in realistic scenarios, demanding a comprehensive understanding of how to employ AWS services to tackle complex challenges.

Case Type



Application migration

A company plans to migrate its legacy application to AWS. The application is data-intensive and requires low-latency access for users across the globe. What AWS services and architecture would you recommend to ensure high availability and low latency?

  • EC2 for compute
  • S3 for storage
  • CloudFront for content delivery
  • Route 53 for DNS routing

Disaster recovery

Your organization wants to implement a disaster recovery plan for its critical AWS workloads with an RPO (Recovery Point Objective) of 5 minutes and an RTO (Recovery Time Objective) of 1 hour. Describe the AWS services you would use to meet these objectives.

  • Backup for regular backups of critical data and systems with a 5-minute recovery points objective (RPO)
  • CloudFormation to define and provision the disaster recovery infrastructure across multiple regions
  • Enable Cross Region Replication in S3 to replicate backups across regions
  • Setup CloudWatch alarms to monitor systems and automatically trigger failover if there are issues

DDos attacks protection

Consider a scenario where you need to design a scalable and secure web application infrastructure on AWS. The application should handle sudden spikes in traffic and protect against DDoS attacks. What AWS services and features would you use in your design?

  • CloudFront and Route 53 for content delivery
  • Auto Scaling group of EC2 across multiple availability zones for scalability
  • Shield for DDoS protection
  • CloudWatch for monitoring
  • Web Application Firewall (WAF) for filtering malicious requests

Real-time data analytics

An IoT startup wants to process and analyze real-time data from thousands of sensors across the globe. The solution needs to be highly scalable and cost-effective. Which AWS services would you use to build this platform, and how would you ensure it scales with demand?

  • Kinesis for real-time data ingestion
  • EC2 and EMR for distributed processing
  • Redshift for analytical queries
  • Auto Scaling to help scale up and scale down resources based on demand

Large-volume data analysis

A financial services company requires a data analytics solution on AWS to process and analyze large volumes of transaction data in real time. The solution must also comply with stringent security and compliance standards. How would you architect this solution using AWS, and what measures would you put in place to ensure security and compliance?

  • Kinesis and Kafka for real-time data ingestion
  • EMR for distributed data processing
  • Redshift for analytical queries
  • CloudTrail and Config to provide compliance monitoring and configuration management
  • Leverage multiple availability zones and IAM policies for access control.

Non-Technical AWS Interview Questions

Besides technical prowess, understanding the broader impact of AWS solutions is vital to a successful interview, and below are a few questions, along with their answers. These answers can be different from one candidate to another, depending on their experience and background.

27. How do you stay updated with AWS and cloud technology trends?

  • Expected from candidate: The interviewer wants to know about your commitment to continuous learning and how they keep your skills relevant. They are looking for specific resources or practices they use to stay informed.
  • Example answer: "I stay updated by reading AWS official blogs and participating in community forums like the AWS subreddit. I also attend local AWS user group meetups and webinars. These activities help me stay informed about the latest AWS features and best practices."

28. Describe a time when you had to explain a complex AWS concept to someone without a technical background. How did you go about it?

  • Expected from candidate: This question assesses your communication skills and ability to simplify complex information. The interviewer is looking for evidence of your teaching ability and patience.
  • Example answer: "In my previous role, I had to explain cloud storage benefits to our non-technical stakeholders. I used the analogy of storing files in a cloud drive versus a physical hard drive, highlighting ease of access and security. This helped them understand the concept without getting into the technicalities."

29. What motivates you to work in the cloud computing industry, specifically with AWS?

  • Expected from candidate: The interviewer wants to gauge your passion for the field and understand what drives you. They're looking for genuine motivations that align with the role and company values.
  • Example answer: "What excites me about cloud computing, especially AWS, is its transformative power in scaling businesses and driving innovation. The constant evolution of AWS services motivates me to solve new challenges and contribute to impactful projects."

30. Can you describe a challenging project you managed and how you ensured its success?

  • Expected from candidate: Here, the focus is on your project management and problem-solving skills. The interviewer is interested in your approach to overcoming obstacles and driving projects to completion.
  • Example answer: "In a previous project, we faced significant delays due to resource constraints. I prioritized tasks based on impact, negotiated for additional resources, and kept clear communication with the team and stakeholders. This approach helped us meet our project milestones and ultimately deliver on time."

31. How do you handle tight deadlines when multiple projects are demanding your attention?

  • Expected from candidate: This question tests your time management and prioritization skills. The interviewer wants to know how you manage stress and workload effectively.
  • Example answer: "I use a combination of prioritization and delegation. I assess each project's urgency and impact, prioritize accordingly, and delegate tasks when appropriate. I also communicate regularly with stakeholders about progress and any adjustments needed to meet deadlines."

32. What do you think sets AWS apart from other cloud service providers?

  • Expected from candidate: The interviewer is looking for your understanding of AWS's unique value proposition. The goal is to see that you have a good grasp of what makes AWS a leader in the cloud industry.
  • Example answer: "AWS sets itself apart through its extensive global infrastructure, which offers unmatched scalability and reliability. Additionally, AWS's commitment to innovation, with a broad and deep range of services, allows for more flexible and tailored cloud solutions compared to its competitors."

Preparing for Your AWS Interview

Preparing for an AWS interview involves more than just brushing up on technical skills. It's about showcasing your interest in the role, demonstrating your ongoing commitment to learning, and articulating your past achievements. Below are some tips to help you stand out in your AWS interview.

  • Research Role and Company: Prepare questions about the role's future, daily activities, growth opportunities, and how the company stands out. This shows enthusiasm and a proactive mindset.

  • Practice Out Loud: Rehearse answers to common questions aloud to improve fluency and confidence. Practicing with a partner can help refine your responses and ensure you cover all key points.

  • Stay Informed on AWS: Keep up with AWS's latest features and innovations. Being able to discuss recent updates demonstrates your commitment to staying current in your field.

  • Highlight Your Experience: Prepare detailed examples of how you've successfully implemented AWS in past projects, including specific outcomes and benefits, such as efficiency gains or productivity increases.


This article has offered a comprehensive roadmap of AWS interview questions for candidates at various levels of expertise—from those just starting to explore the world of AWS to seasoned professionals seeking to elevate their careers.

Whether one is preparing for your first AWS interview or aiming to secure a more advanced position, this guide serves as an invaluable resource. It prepares you not just to respond to interview questions but to engage deeply with the AWS platform, enhancing your understanding and application of its vast capabilities.

Photo of Zoumana Keita
Zoumana Keita

Zoumana develops LLM AI tools to help companies conduct sustainability due diligence and risk assessments. He previously worked as a data scientist and machine learning engineer at Axionable and IBM. Zoumana is the founder of the peer learning education technology platform ETP4Africa. He has written over 20 tutorials for DataCamp.


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