AWS interview questions explained by service group

Cracking an AWS interview isn’t about memorizing obscure features or reciting the names of all 200+ services. It’s about knowing what actually matters—how the core AWS primitives work, when to use them, and how to stitch them together to solve real-world problems. 

It’s about showing that you can reason about trade-offs, think in terms of systems, and build resilient, scalable solutions.

In this blog, we’ll cut through the noise and walk you through the AWS interview questions and AWS Web Services interview questions developers should actually focus on, organized by service type and engineering role. 

Compute services#

Let’s start with the foundation of every cloud application: compute. AWS gives you multiple ways to run code, each tailored to different levels of control and abstraction.

• EC2: Elastic Compute Cloud gives you virtual machines you can fully customize. You pick the OS, the instance type, and are responsible for patching, scaling, and managing everything.

• Lambda: Serverless compute. You just write the function and define the trigger. AWS handles the rest—scaling, provisioning, and patching the underlying infra.

• Elastic Beanstalk: Think of it as a middle ground between EC2 and AWS Lambda. You deploy code, and AWS manages the environment.

What they might ask: “When would you choose EC2 over Lambda?”

What they’re looking for: You understand when you need full control versus when you can trade it for simplicity, cost-efficiency, and automatic scaling.

Backend and DevOps engineers must be fluent in these trade-offs. Interviewers expect you to weigh cost, flexibility, and complexity on the fly.

These types of AWS interview questions are designed to assess your architectural judgment as much as your technical depth.

Storage services#

Storage in AWS isn’t just about dumping files into buckets. It’s about knowing which storage class, volume type, or access pattern makes sense for your workload.

• S3: Object storage used for everything from static site hosting to big data lakes. Understand storage classes, lifecycle rules, and versioning.

• EBS: Block storage that behaves like a hard drive. Great for databases and boot volumes.

• EFS: You can mount the network file system to multiple EC2 instances. Ideal for shared storage.

What they might ask: “EBS vs EFS: What’s the difference?”

What they’re looking for: You can explain throughput, latency, mount targets, and why shared vs dedicated access matters.

Everyone should know S3 cold. If you’re a backend engineer or data-heavy dev, EBS and EFS are table stakes.

Networking & security services#

Most production outages and vulnerabilities stem from misconfigured networks or access policies, so AWS interview questions almost always probe these areas.

• VPC: Virtual Private Cloud lets you control your own IP space, define subnets, set up NAT, and isolate environments.

• Security Groups & NACLs: Firewalls that define what traffic can flow in and out. Security Groups are stateful; NACLs are stateless.

• IAM: IAM (Identity and Access Management). Central to AWS. Know policies, trust relationships, and least privilege.

• Route 53: Managed DNS. Supports routing policies like failover, latency-based, and weighted routing.

What they might ask: “How do Security Groups and NACLs differ?”

What they’re looking for: You understand network boundaries, can debug access issues, and build secure, maintainable systems.

IAM is a must-know. Treat it like a first-class skill, not an afterthought.

Observability & logging#

Once your app is running, you need to know if it’s behaving. Observability is more than logs—it’s about visibility across services.

• CloudWatch: Collects logs and metrics. Use it to set alarms, visualize dashboards, and troubleshoot failures.

• CloudTrail: Tracks all API activity in your AWS account. Essential for auditing and forensic analysis.

What they might ask: “How would you debug a spike in latency?”

What they’re looking for: You can walk through log aggregation, trace requests, and correlate metrics with system behavior.

Senior candidates should bring up distributed tracing (like AWS X-Ray) and structured logging strategies.

Database services#

You’ll be expected to explain how and why you pick specific database solutions. The key is aligning the service with your query patterns, latency needs, and data structure.

• RDS: Managed relational databases. Great for transactional workloads that require strong consistency.

• DynamoDB: Fully serverless NoSQL. Ideal for massive scale and millisecond latency.

• Aurora: High-performance variant of MySQL/PostgreSQL with auto-scaling and high availability.

What they might ask: “When would you use DynamoDB instead of RDS?”

What they’re looking for: You know the trade-offs between relational vs NoSQL, strong vs eventual consistency, and scale vs structure.

Backend and data engineers should be ready to justify their choices using real-world scenarios.

These kinds of AWS interview questions and broader AWS Web Services interview questions often separate junior devs from more experienced engineers who can reason about design trade-offs.

Automation & DevOps#

Modern teams deploy dozens of times per day. You’re expected to automate infrastructure changes and streamline releases.

• CloudFormation: AWS-native IaC. Write JSON/YAML templates to define your infrastructure.

• Terraform: Popular third-party IaC tool. Supports multi-cloud. Great for managing complex stacks.

• CodePipeline / CodeBuild / CodeDeploy: AWS-native CI/CD services. Automate the whole lifecycle.

What they might ask: “How do you manage deployments across multiple environments?”

What they’re looking for: You understand promotion strategies (dev → staging → prod), rollback mechanisms, and DRY IaC practices.

DevOps and platform engineers should lead this section of the conversation.

Messaging & event-driven services#

Modern cloud architectures rely heavily on decoupling. Event-driven systems are everywhere, and interviewers want to see how you build for asynchronous workflows.

• SNS (Simple Notification Service): Pub/sub service to fan out messages to multiple consumers.

• SQS (Simple Queue Service): Reliable message queues to decouple components.

• EventBridge: Serverless event bus for routing events between AWS services and SaaS apps.

What they might ask: “How would you decouple microservices in AWS?”

What they’re looking for: You know how to build scalable systems that don’t rely on tight coupling.

Expect questions about retries, idempotency, dead-letter queues, and failure handling.

Analytics & query services#

AWS offers a suite of tools to derive insights from large datasets without provisioning servers manually.

• Athena: Query data stored in S3 using SQL. Great for ad hoc analysis.

• QuickSight: AWS’s BI tool for dashboards and visualizations.

• Redshift: Scalable data warehouse for complex analytics.

What they might ask: “How would you query logs stored in S3?”

What they’re looking for: You understand schema-on-read, pricing per query, and scalability.

Data engineers and backend devs should know when to use Athena vs Redshift.

Containers & orchestration#

Containers are a middle ground between VMs and serverless. Interviews often include questions about container lifecycle and orchestration.

• ECS: AWS’s native container service. Supports Fargate (serverless containers).

• EKS: Managed Kubernetes on AWS.

• Fargate: Run containers without managing servers.

What they might ask: “When would you use ECS over EKS?”

What they’re looking for: You understand trade-offs in control, complexity, and team maturity.

DevOps engineers and backend teams working in microservices need to know these cold.

Edge services & CDN#

Reducing latency is critical for real-time apps and global audiences.

• CloudFront: AWS’s CDN for content delivery.

• Global Accelerator: Optimizes routing over AWS’s global network.

• Lambda@Edge: Run functions closer to users, at the edge.

What they might ask: “How do you speed up your app for a global audience?”

What they’re looking for: You understand caching, edge compute, and latency management.

Frontend and mobile engineers should know CloudFront and Lambda@Edge.

Cost management & governance#

It’s not enough to build scalable systems—they must also be cost-effective.

• Cost Explorer: Visualize and explore your spending.

• AWS Budgets: Set usage thresholds and get alerts.

• Trusted Advisor: Recommends savings opportunities and best practices.

What they might ask: “How do you monitor and reduce cloud costs?”

What they’re looking for: You can explain reserved instances, spot pricing, and right-sizing.

Budget awareness shows maturity. Hiring teams love engineers who think about cost early.

Final thoughts#

You don’t need to learn all of AWS. You just need to learn the parts that matter for your role and your interview.

Start with compute, storage, and IAM. Expand to databases, observability, and automation once you’ve nailed the fundamentals. And when you're ready to go deeper—say, into Lambda or Step Functions—follow the service-specific guides linked throughout.