AWS Lambda Interview Questions and Answers

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Q: What is AWS Lambda?
AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS). It allows you to run code without provisioning or managing servers. You simply upload your code to Lambda, and AWS handles automatic scaling and managing the underlying infrastructure required to execute your code in response to events.

Q: How does AWS Lambda work?
AWS Lambda executes code in response to events triggered by AWS services or custom events. After uploading your code to Lambda, you define event sources (e.g., Amazon S3, DynamoDB, or Kinesis) that will trigger the execution. When an event occurs, Lambda automatically provisions compute resources, runs the code, and scales down once execution is complete.

Q: What are the benefits of using AWS Lambda?

• No server management: AWS manages the infrastructure, scaling, and patching for you.
• Cost-effective: You pay only for the compute time used.
• Scalable: Automatically handles high volumes of requests by scaling horizontally.
• Fully managed: AWS takes care of infrastructure maintenance and monitoring.
• Integration with AWS services: Seamlessly integrates with other AWS services for easy serverless architectures.

Q: What programming languages are supported by AWS Lambda?
AWS Lambda supports several programming languages, including:

• Node.js
• Python
• Java
• Go
• .NET Core (C#)
• Ruby

Q: What is a Lambda function?
A Lambda function is the code you upload to AWS Lambda to be executed in response to events. It contains the logic that defines what happens when the function is triggered.

Q: How do you trigger a Lambda function?
Lambda functions can be triggered by various event sources, such as:

• Changes in Amazon S3 buckets (e.g., file uploads)
• Updates to records in DynamoDB
• Messages published to Amazon SNS topics
• Events generated by AWS CloudWatch or IoT services

Q: What are cold starts in AWS Lambda?
Cold starts refer to the latency that occurs when a Lambda function is invoked for the first time or after a period of inactivity. During a cold start, AWS provisions the required resources, leading to increased latency. Subsequent invocations reuse these resources, resulting in faster execution times (known as warm starts).

Q: How can you optimize AWS Lambda performance?
To optimize Lambda performance:

• Reduce the size of your deployment package.
• Minimize initialization code and external dependencies.
• Use provisioned concurrency to keep functions warm.
• Implement efficient error handling and retries.
• Tune memory allocation and timeout settings.

Q: What are the limitations of AWS Lambda?

• Execution duration: Maximum of 15 minutes per function.
• Memory allocation: Up to 10 GB per function.
• Deployment package size: Maximum 250 MB (including layers).
• Concurrency limits: Default limit is 1,000 concurrent executions per region.
• Stateless nature: Functions are stateless and lack persistent storage.

Q: How do you monitor and debug AWS Lambda functions?
You can monitor and debug Lambda functions using:

• AWS CloudWatch Logs: Captures log output from Lambda functions.
• AWS CloudWatch Metrics: Tracks function performance, invocation counts, errors, and duration metrics.
• AWS X-Ray: Provides distributed tracing to identify bottlenecks and troubleshoot issues.

Q: What are the key components of AWS Lambda?

• Function Code: The logic you write and upload to Lambda.
• Event Source: The AWS service or custom application that triggers the function.
• Execution Role: IAM role that grants the function permission to access AWS resources.
• Function Configuration: Settings like memory, timeout, environment variables, and runtime.

Q: What is the maximum timeout for an AWS Lambda function?
The maximum timeout for an AWS Lambda function is 15 minutes. This is configurable in the function settings.

Q: How is AWS Lambda priced?
AWS Lambda pricing is based on two factors:

1. Number of Requests: First 1 million requests are free; after that, you are charged per million requests.
2. Duration: Measured in milliseconds from the time the function starts executing until it returns or terminates.

Additional charges apply for data transfer and provisioned concurrency.

Q: Can AWS Lambda call another Lambda function?
Yes, AWS Lambda can invoke other Lambda functions synchronously or asynchronously. This is often done to create workflows or pipelines using services like AWS Step Functions.

Q: What are Lambda Layers, and why are they used?
Lambda Layers are a distribution mechanism for code and libraries that can be shared across multiple Lambda functions. They are used to:

• Reduce duplication by sharing common dependencies (e.g., libraries, SDKs).
• Keep deployment packages small.
• Separate business logic from shared code.

Q: What are the types of triggers for AWS Lambda?
AWS Lambda can be triggered by:

AWS Services:

• S3 (e.g., file uploads).
• DynamoDB (e.g., table updates).
• Kinesis (e.g., data stream events).
• SNS (e.g., topic messages).
• API Gateway (e.g., RESTful API calls).

Custom Events: Application or service-generated events.

Scheduled Events: Using CloudWatch Events to schedule invocations.

Q: What are the steps to deploy a Lambda function?

1. Write the code and package it (e.g., as a .zip file).
2. Log in to the AWS Management Console or use the AWS CLI.
3. Create a Lambda function and upload the code package.
4. Configure the function’s runtime, memory, timeout, and environment variables.
5. Define the execution role and event source triggers.
6. Test and deploy the function.

Q: How do you manage versions in AWS Lambda?
Lambda supports function versioning, allowing you to publish a new version of your function. Each version is immutable and identified by a version number. You can:

• Use aliases to point to specific versions (e.g., development, production).
• Roll back to previous versions if needed.

Q: What is Provisioned Concurrency in AWS Lambda?
Provisioned Concurrency keeps a specified number of function instances initialized and ready to handle requests. It minimizes cold starts, ensuring consistent performance for latency-sensitive applications.

Q: How does AWS Lambda integrate with Amazon API Gateway?
Lambda can serve as the backend for RESTful APIs through Amazon API Gateway. The integration allows:

• API Gateway to invoke Lambda functions when API endpoints are called.
• The ability to transform request and response payloads.
• Built-in support for throttling, caching, and authorization.

Q: What is the difference between synchronous and asynchronous invocation in AWS Lambda?

• Synchronous Invocation: The caller waits for the function to complete and receives the response (e.g., invoked by API Gateway).
• Asynchronous Invocation: The function is invoked, and the caller does not wait for a response (e.g., invoked by S3 or SNS). The function’s output can be stored in services like SQS or CloudWatch.

Q: Can AWS Lambda access resources in a VPC?
Yes, Lambda can access resources in a VPC by configuring it with VPC-specific settings. You must:

• Specify the subnets and security groups to allow access.
• Ensure that the required network configuration is in place (e.g., NAT gateway for internet access).

Q: What is the purpose of environment variables in AWS Lambda?
Environment variables are key-value pairs that store configuration settings for Lambda functions. They allow you to:

• Modify function behavior without changing code.
• Store sensitive data securely using AWS Secrets Manager or KMS for encryption.

Q: What are common use cases for AWS Lambda?

• File Processing: Automatically process files uploaded to S3 (e.g., image resizing, data transformation).
• Data Stream Processing: Analyze real-time data from Kinesis or DynamoDB Streams.
• Web APIs: Backend logic for APIs through API Gateway.
• Automated Tasks: Perform scheduled tasks with CloudWatch Events.
• Chatbots: Power conversational interfaces integrated with Amazon Lex.
• Event-Driven Workflows: Orchestrate workflows using Step Functions.

Q: How can you handle errors in AWS Lambda?

• Use try-catch blocks within your code to catch exceptions.
• Configure dead-letter queues (DLQs) for unprocessed events.
• Monitor errors using CloudWatch metrics and logs.
• Implement retries using the Retry Policy for asynchronous invocations.

Q: What is the difference between Lambda@Edge and AWS Lambda?

• AWS Lambda: Runs functions in the AWS region where they are deployed.
• Lambda@Edge: Runs functions at AWS edge locations to improve performance for global users. Lambda@Edge is commonly used for content delivery with Amazon CloudFront.

Q: Can AWS Lambda be used for long-running tasks?
Lambda is designed for short-lived tasks with a maximum execution time of 15 minutes. For longer-running processes, consider using Amazon ECS, AWS Batch, or other compute services.

Q: How do you secure AWS Lambda functions?

• Use IAM roles with the least privilege to limit access.
• Encrypt sensitive environment variables using AWS KMS.
• Use VPC configurations for secure network access.
• Apply AWS WAF with API Gateway to protect from malicious traffic.
• Enable X-Ray tracing for monitoring and debugging security issues.

Q: What are the differences between AWS Lambda and traditional servers?

• Server Management: Lambda is serverless, meaning AWS manages servers for you, while traditional servers require provisioning and management.
• Billing: Lambda charges only for the compute time used, while traditional servers often incur costs even when idle.
• Scalability: Lambda scales automatically in response to events, while traditional servers may require manual scaling or load balancers.
• Statelessness: Lambda functions are stateless and ephemeral, while traditional servers can maintain state.
• Execution Duration: Lambda functions have a maximum execution time of 15 minutes, whereas traditional servers can run indefinitely.

Q: What is the Execution Context in AWS Lambda?
The Execution Context is a temporary environment created by AWS Lambda to run your function. It includes:

• Temporary Disk Space: Up to 512 MB in /tmp for local storage during execution.
• Environment Variables: Key-value pairs for configuration.
• Initialization State: Objects initialized outside the handler method persist between invocations (warm starts).

Q: How does AWS Lambda handle retries for asynchronous invocations?
Lambda automatically retries asynchronous invocations twice in case of failure. If the retries fail, you can configure a Dead Letter Queue (DLQ) using Amazon SQS or SNS to store the failed events for further processing.

Q: Can AWS Lambda work with container images?
Yes, AWS Lambda supports container images. You can:

• Build container images with custom runtimes or dependencies.
• Push the images to Amazon Elastic Container Registry (ECR).
• Deploy these images to Lambda functions with a maximum size of 10 GB.

Q: What is the relationship between AWS Lambda and Step Functions?
Step Functions orchestrate multiple Lambda functions into workflows. You can use Step Functions to:

• Manage dependencies between functions.
• Handle retries and error handling.
• Pass data between function invocations.
• Create state machines to model business workflows.

Q: How can you reduce cold start latency in AWS Lambda?

• Provisioned Concurrency: Keeps a pool of pre-initialized function instances ready.
• Reduce Deployment Package Size: Smaller packages load faster.
• Use Lighter Runtimes: Runtimes like Node.js and Python have shorter initialization times.
• Optimize Code Initialization: Minimize code executed during initialization.

Q: What are the use cases for Lambda@Edge?
Lambda@Edge runs functions at AWS edge locations and is commonly used for:

• Content Customization: Tailor content delivery for users based on location or device.
• Request/Response Manipulation: Modify HTTP headers or request paths.
• Access Control: Implement user authentication and authorization.
• Real-time A/B Testing: Route traffic to different backend resources dynamically.

Q: What are AWS Lambda Extensions?
Lambda Extensions allow you to integrate additional tools and services with Lambda, such as:

• Monitoring (e.g., Datadog, New Relic).
• Security (e.g., AWS Secrets Manager, Snyk).
• Logging (e.g., AWS CloudWatch, Splunk).
  Extensions run alongside your function code and can be used for tasks like telemetry collection and initialization.

Q: What is the role of IAM in AWS Lambda?
IAM (Identity and Access Management) is critical for Lambda security:

• Execution Role: Defines permissions for the Lambda function to access other AWS resources.
• Resource Policies: Grant permissions for event sources to invoke the function.
• Least Privilege: Ensures that the function has only the permissions required to perform its tasks.

Q: How does AWS Lambda handle scaling?
Lambda scales horizontally by creating new instances of your function in response to increased requests. Each function instance handles one request at a time.

• Concurrency Limits: Default is 1,000 concurrent executions per region, but it can be increased upon request.
• Burst Scaling: Lambda supports burst scaling for up to 500–3,000 instances, depending on the region.

Q: What are Event Source Mappings in AWS Lambda?
Event Source Mappings are configurations that connect a Lambda function to an event source (e.g., SQS, DynamoDB Streams). They automatically poll or read events from the source and invoke the function with the event data.

Q: How do you manage dependencies in AWS Lambda?

• Deployment Packages: Include dependencies in a .zip file along with your code.
• Lambda Layers: Store shared libraries and dependencies that can be reused across multiple functions.
• Container Images: Package dependencies in Docker images for Lambda functions.

Q: Can AWS Lambda access relational databases?
Yes, Lambda can access relational databases like Amazon RDS or Aurora.

• Use VPC Configuration: To connect securely to RDS in a private subnet.
• Optimize connection management using connection pooling libraries (e.g., RDS Proxy) to handle concurrent requests efficiently.

Q: What is AWS Lambda’s pricing model?
AWS Lambda charges are based on:

Request Count:

• 1 million free requests per month.
• After that, $0.20 per 1 million requests.

Compute Time:

• Charged in 1 ms increments based on memory and execution time.

Provisioned Concurrency: Additional charges apply for keeping functions warm.

Q: What is RDS Proxy, and how does it benefit AWS Lambda?
RDS Proxy is a fully managed database proxy that improves Lambda’s connection management with relational databases. Benefits include:

• Efficiently handles a large number of connections.
• Reduces database overhead.
• Improves application performance and scalability.

Q: What are some challenges of AWS Lambda?

• Cold Start Latency: Affects response times for infrequent requests.
• Execution Limits: 15-minute maximum execution time.
• Stateless Nature: Requires external storage for persistent data.
• Resource Limits: Memory (up to 10 GB) and ephemeral disk (512 MB) constraints.

Q: How do you handle secrets securely in AWS Lambda?

• Use AWS Secrets Manager or AWS Systems Manager Parameter Store to store sensitive data.
• Encrypt environment variables using AWS KMS.
• Grant least-privilege permissions to the IAM role for accessing secrets.

Q: How can you debug Lambda functions locally?

• Use the AWS SAM CLI (Serverless Application Model) to simulate Lambda functions locally.
• Use IDE extensions like AWS Toolkit for VS Code or IntelliJ.
• Leverage unit testing frameworks and mock event sources for testing.

Q: What is the difference between Event-Driven Architecture and Polling in AWS Lambda?

• Event-Driven: Lambda is triggered directly by events from services like S3 or SNS.
• Polling: Lambda polls event sources like DynamoDB Streams or SQS to fetch and process messages.

Q: Can AWS Lambda be used for machine learning?
Yes, AWS Lambda can be used for lightweight machine learning tasks, such as:

• Hosting pre-trained models for inference.
• Real-time data preprocessing for ML pipelines.
  For heavy ML tasks, services like SageMaker or EC2 are recommended.

Q: How does Lambda handle large payloads?

• Payload Limits: The request and response payload for synchronous invocations is 6 MB, while for asynchronous invocations, it is 256 KB.
• Large Data Handling: For larger payloads, store data in S3 and pass the S3 location as an input to Lambda.