AWS Lambda Interview Questions and Answers

AWS Lambda Interview Questions have become a key focus for developers preparing for roles in serverless application development. AWS Lambda has revolutionized how developers build and deploy applications by eliminating the need for server management. As serverless computing becomes increasingly mainstream, AWS Lambda stands out for its scalability, cost-efficiency, and seamless integration with other AWS services.

In this blog, we’ve structured a list of AWS Lambda interview questions ranging from basic to advanced that are designed to help both aspiring and experienced professionals prepare effectively for job interviews.

So, first, let’s start with the Basic AWS Lambda Interview Questions. These will help you get comfortable with the core concepts and set the stage for deeper technical discussions later on.

Basic AWS Lambda Interview Questions

1. What is AWS Lambda and how does it work?

AWS Lambda is a serverless computing service that automatically manages infrastructure, allowing you to run code in response to triggers like HTTP requests, database updates, or file uploads. You simply upload your code, and AWS Lambda executes it when an event occurs, scaling resources as needed without manual provisioning.

2. Which programming languages are supported by AWS Lambda?

AWS Lambda supports several mainstream programming languages, including Python, Java, Node.js, C#, Ruby, Go, and PowerShell. You can also use custom runtimes if your preferred language isn’t natively supported, offering flexibility for different application requirements.

3. Can you explain what automated deployment means in the context of AWS Lambda?

Automated deployment refers to the process of pushing code updates and configurations to Lambda functions without manual intervention. This approach minimizes human error, accelerates release cycles, and ensures consistent environments using tools like AWS CodePipeline, AWS CodeDeploy, or third-party CI/CD tools.

4. What is auto-scaling in AWS Lambda, and how does it benefit applications?

Auto-scaling in AWS Lambda means that the service automatically adjusts the number of function instances in response to incoming requests. It can handle thousands of concurrent executions without user intervention. This elasticity ensures efficient use of resources and maintains performance under variable loads.

5. What storage options are available for use with AWS Lambda functions?

AWS Lambda primarily uses /tmp storage for temporary files (up to 512 MB). For persistent or large-scale storage, Lambda integrates with services like:

• Amazon S3 for object storage
• Amazon EBS (Elastic Block Store) for block-level storage (indirectly via other services)
• Amazon DynamoDB for key-value and document storage
• Amazon EFS (Elastic File System), which provides scalable, shared access across multiple Lambda functions

6. What is the execution timeout limit for AWS Lambda during a DDoS mitigation use case?

In most use cases, including when used during Distributed Denial of Service (DDoS) mitigation, the maximum execution timeout for a Lambda function is 15 minutes (900 seconds). However, if Lambda is indirectly used (e.g., behind API Gateway), timeouts may be influenced by the upstream service’s limits.

7. Why is AWS Lambda considered a time-saving solution for developers?

Lambda streamlines deployment and scaling, eliminating the need to manage servers. Additionally, it stores code efficiently, can interact directly with databases, and supports rapid testing. These factors reduce operational overhead and development time, allowing developers to focus on building features rather than managing infrastructure.

8. What is an AMI, and how is it relevant to Lambda or AWS in general?

An Amazon Machine Image (AMI) is a template used to launch EC2 instances. While not directly used in Lambda, AMIs are foundational to AWS infrastructure. Understanding AMIs helps when building hybrid applications where EC2 instances might interact with serverless functions via APIs or events.

9. How are Amazon EC2 instances related to AMIs?

EC2 instances are virtual servers launched using AMIs. An AMI contains the OS, application server, and application data required to launch an instance. When scaling infrastructure manually or managing workloads outside of Lambda, understanding this relationship is key to AWS architecture design.

10. What are some best practices for securing AWS Lambda functions?

Security in Lambda starts with AWS IAM (Identity and Access Management). You should follow the principle of least privilege when assigning roles and permissions. Additional best practices include:

• Encrypting environment variables
• Restricting VPC access where necessary
• Using secure API gateways
• Regularly rotating credentials
• Monitoring access with AWS CloudTrail

Staying updated with the latest AWS security patches and guidelines is also critical for minimizing risks.

Now that we’ve covered the basics, let’s move on to some intermediate-level AWS Lambda interview questions to deepen your understanding.

Intermediate AWS Lambda Interview Questions

1. What is Amazon Elastic Block Store (EBS), and how does it relate to Lambda?

Amazon EBS provides block-level storage volumes for use with EC2 instances, not directly with Lambda. However, Lambda can interact with EBS indirectly, for example, through APIs or other AWS services. For Lambda-specific persistent storage, Amazon EFS is more suitable, as it integrates natively with Lambda for shared file access.

2. How does AWS Lambda handle failures during event processing?

Lambda processes events in either synchronous or asynchronous modes. In synchronous execution, failures return errors to the invoking service. In asynchronous mode, Lambda retries the event automatically up to two additional times, spaced out with exponential backoff. For advanced error handling, you can configure DLQs (Dead Letter Queues) or destination settings for failed events.

3. Is vertical scaling supported in AWS Lambda?

Unlike EC2, Lambda does not support traditional vertical scaling. Instead, it allows you to allocate memory between 128 MB and 10,240 MB, which indirectly affects the CPU and network throughput. Increasing memory improves performance, making it a form of vertical scaling within Lambda’s serverless model.

4. What are some limitations of AWS Lambda that developers should be aware of?

Key limitations include:

• Execution timeout: Max 15 minutes per invocation
• Deployment package size: 50 MB (zipped), or 250 MB when using layers
• Ephemeral disk storage (/tmp): 512 MB (expandable to 10 GB via EFS)
• No persistent state: Functions are stateless by default
• Concurrent executions: Limited by AWS account concurrency limits, though this can be increased

Understanding these helps in designing scalable, efficient serverless apps.

5. How can a Lambda function be triggered or executed?

Lambda functions can be executed via:

• AWS Console (manual testing)
• AWS CLI and SDKs
• Amazon API Gateway
• Event sources like S3 (file uploads), DynamoDB (data changes), or CloudWatch (scheduling)
• AWS Step Functions for orchestration

These varied options make Lambda highly flexible in different architectures.

6. What’s a simple technique to boost performance in AWS Lambda?

One effective way is to increase the memory allocation, which also enhances CPU power. Additionally, keeping functions warm using scheduled invocations (like a CloudWatch cron job) reduces cold start latency. You can also use provisioned concurrency to keep functions pre-initialized.

7. How can AWS Lambda be used in different application scenarios?

Lambda can serve multiple roles:

• Backend APIs (via API Gateway)
• Data processing (S3 uploads, DynamoDB streams)
• Automation (triggered by CloudWatch Events)
• ETL workflows (transforming data before storing in Redshift or S3)
• Security monitoring (using AWS Config or GuardDuty)

Its event-driven nature makes it ideal for microservice and serverless patterns.

8. How does AWS Lambda ensure code security at rest and in transit?

Lambda stores your function code in Amazon S3 and encrypts it at rest using AWS Key Management Service (KMS). During execution, Lambda performs additional integrity checks and encrypts data in transit using industry-standard TLS protocols. You can also implement your encryption logic within the function for added security.

9. What does serverless computing mean in the context of AWS Lambda?

Serverless computing allows developers to run code without managing infrastructure. AWS automatically handles provisioning, scaling, patching, and resource allocation. With AWS Lambda, you’re charged only for compute time used, making it ideal for dynamic, cost-efficient workloads without the overhead of maintaining servers.

10. How does AWS Lambda integrate into a CI/CD pipeline?

Lambda functions can be deployed automatically through CI/CD pipelines using tools like AWS CodePipeline, AWS CodeBuild, or third-party platforms such as Jenkins and GitHub Actions. You can automate the entire lifecycle from writing and testing code to packaging and deploying it with defined approvals and rollback policies.

Ready to level up? Let’s dive into the advanced AWS Lambda interview questions that test real-world expertise and architecture knowledge.

Advanced AWS Lambda Interview Questions

1. How do you create a custom Amazon Machine Image (AMI) for deployment purposes?

Creating a custom AMI starts by launching an EC2 instance using an existing trusted AMI. After that, install necessary packages, update configurations, and remove sensitive data if applicable. Once the setup is ready, you can create an AMI from this instance, which captures the full state of the server for consistent deployment in future use cases, like building Lambda layers or test environments.

2. Does updating a Lambda function cause downtime or affect availability?

No, updating a Lambda function doesn’t cause downtime. When you update a function, Lambda briefly manages multiple versions during the transition; existing executions may continue using the previous version, while new requests are gradually routed to the updated one. This process, called eventual consistency, ensures high availability during version changes.

3. What operational restrictions exist for AWS Lambda functions?

Lambda imposes restrictions on operations that could compromise its managed environment. These include:

• Disabling instance-level operations
• Blocking system tracing or debugging tools
• No inbound network connections
• Limited outbound network access (TCP only; IP sockets supported)
• No root-level access

These guardrails ensure security and isolation but require alternate architectural choices for advanced debugging or real-time networking.

4. How can developers get started with building a serverless application using Lambda?

To start a serverless project with Lambda:

• Choose a blueprint from the AWS Lambda console or initialize a project using AWS SAM (Serverless Application Model).
• Define resources in a template.yaml file.
• Package your app using the sam package.
• Deploy using sam deploy or CloudFormation.

This creates a reproducible, infrastructure-as-code setup ideal for version control and CI/CD.

5. What are some drawbacks or limitations of serverless architecture in Lambda?

While Lambda offers great scalability and simplicity, its limitations include:

• Vendor lock-in: Deep integration with AWS services limits portability.
• Cold start latency: For infrequent invocations, initialization delays can occur.
• Limited runtime duration: Max execution time of 15 minutes.
• Limited observability: Traditional debugging tools are restricted.
• Concurrency limits: Burst scaling is controlled by AWS account limits.

Mitigating these often requires architectural workarounds and monitoring tools.

6. How is a Lambda function different from an anonymous class in Java?

Lambda functions in Java are stateless expressions used for functional interfaces, enhancing code brevity and readability. Anonymous classes, on the other hand, are object-oriented constructs that allow method overrides with their instance. While both enable inline behavior, Lambda functions are more lightweight and optimized for functional programming.

7. Are Lambda expressions considered nameless code blocks, and how do they work internally?

Yes, Lambda expressions are anonymous, inline code blocks that implement a single abstract method from a functional interface. They don’t require a name, class, or method signature. Internally, they compile into a method reference or invokedynamic instruction, making them memory-efficient and fast at runtime.

8. What types of workloads or applications are best suited for AWS Lambda?

Lambda is ideal for event-driven, stateless workloads like:

• Real-time file processing (e.g., image resizing after S3 upload)
• Stream processing (e.g., Kinesis or DynamoDB streams)
• Data validation and filtering
• Backend services for APIs
• Scheduled tasks (e.g., cron jobs using CloudWatch)
• IoT event handling

Lambda excels when services need instant execution with a minimal resource footprint.

9. What is the difference between final and effectively final variables in Lambda expressions?

In Java, a final variable is explicitly marked and cannot be reassigned after initialization. An effectively final variable isn’t declared final but never reassigned after its initial value, making it functionally equivalent. Lambda expressions can reference both, but only final or effectively final variables can be used inside a Lambda to ensure thread safety and immutability.

10. Can you explain how AWS Lambda actually works under the hood?

AWS Lambda abstracts away the infrastructure and uses a containerized model under the hood:

• Your code is uploaded and stored in an S3-based blob store.
• When invoked, Lambda checks for a warm container.
• If none exist, it spins up a new container with your runtime and code (cold start).
• The function runs and responds.
• The container is kept warm for a short period to handle subsequent requests.

This model allows high efficiency, fast scaling, and cost-effective execution.

Conclusion

AWS Lambda has revolutionized the way we build and deploy applications in the cloud, thanks to its serverless and event-driven nature. Whether you’re a beginner or an experienced professional, understanding Lambda deeply is crucial for cloud-based roles. Mastering these interview questions will give you a strong edge in your next AWS-focused interview.

If you want to dive deeper into AWS and build your expertise, you can explore AWS Solution Architect Certification Training to gain a comprehensive understanding of AWS services, infrastructure, and deployment strategies. For more detailed insights, check out our What is AWS and AWS Tutorial. If you are preparing for an interview, explore our AWS Interview Questions.

FAQs

1. Where can I practice the AWS Lambda interview questions?

You can practice AWS Lambda interview questions using:

• AWS Free Tier: Set up real Lambda functions and triggers.
• AWS Skill Builder: Offers hands-on labs and courses.
• GitHub Repositories: Many open-source Lambda examples are available.
• Cloud Academy & ACloudGuru: Provide scenario-based exercises.
• Online Coding Platforms: LeetCode and HackerRank for logic building.

2. What is AWS Lambda used for?

AWS Lambda is used to run backend services without provisioning or managing servers. It is ideal for:

• Processing real-time data streams
• Responding to HTTP requests
• Automating tasks on AWS
• Running scheduled jobs
• Building APIs and microservices

It operates on a pay-as-you-go model and automatically scales with demand.

3. What is Lambda API in AWS?

The Lambda API is a RESTful interface provided by AWS that allows you to manage Lambda functions programmatically. You can use it to:

• Create, update, or delete functions
• Invoke functions directly
• Configure environment variables
• Manage permissions

It supports access via AWS SDKs, AWS CLI, or HTTPS endpoints.

4. What are the 3 components of AWS Lambda?

The three key components of AWS Lambda are:

• Function: The actual code logic is written in supported languages.
• Event Source: The AWS service or trigger that invokes the function (e.g., S3, API Gateway).
• Execution Role (IAM): Grants permissions for Lambda to access other AWS resources securely.

5. What is Lambda in EC2?

While Lambda and EC2 both run code in the AWS ecosystem, Lambda is a serverless compute service, whereas EC2 requires you to manage servers. Lambda abstracts the infrastructure and lets you run code in response to events without provisioning, patching, or scaling servers, unlike EC2, where you handle all server-level operations.