AWS Lambda is a popular serverless compute service that lets you run event-driven functions without managing servers. Here are 50 common AWS Lambda interview questions for beginners to help assess Lambda knowledge and experience.
We’ll cover Lambda architecture, functions, triggers, monitoring, security, pricing, integrations, use cases and more through detailed explanations and examples. Let’s get started understanding the Lambda platform!
AWS Lambda Interview Questions
Q1: What is AWS Lambda?
AWS Lambda is a serverless compute service that runs functions in response to events like HTTP requests, database changes, queue messages etc. Lambda handles provisioning servers, scaling capacity, monitoring, and logging automatically. This allows developers to focus just on application code.
Q2: What are the key benefits of AWS Lambda?
Key benefits include:
- No server management – Fully managed service
- Event-driven – Execute functions in response to events
- Scales automatically – Handles traffic spikes seamlessly
- Pay per use – Pay only for compute used per request
- Integrates with many AWS services – Triggers from S3, DynamoDB etc
- Microservices and ETL workflows – Decoupled functions
Q3: What programming languages does Lambda support?
AWS Lambda supports code written in Node.js, Python, Ruby, Java, C#, Go, and PowerShell. The code can leverage any packages or dependencies.
Q4: What are AWS Lambda functions?
Lambda functions are the core units of code executed. A Lambda function consists of application code written in a supported language like Node.js. Functions have associated compute resources and configurations settings like memory allocated.
Q5: How are Lambda functions executed and scaled?
When a Lambda function is triggered, AWS handles running the function on capacity provisioned automatically. Additional instances are spun up seamlessly to handle increased load. Lambda autoscaling removes capacity when no longer needed.
Q6: How are Lambda functions billed?
Lambda bills based on total compute time consumed. When a function runs, you’re billed for the number of milliseconds it executes and the allocated memory. Billing is rounded up to the nearest 100ms. Unused functions incur no charge.
Q7: What are common Lambda trigger types?
Common triggers include HTTP requests, new objects uploaded to S3, DynamoDB updates, CloudWatch events, SQS queue messages, and API Gateway requests. Lambda functions can be triggered synchronously or asynchronously.
Q8: What are key components of a Lambda function?
Key components include:
- Handler – Code invoked when function is triggered
- Runtime – Programming language used
- Resources – Configured memory and maximum execution duration
- Triggers – Events that invoke function
- Environment variables – Passed in key-value pairs
- IAM role – Permissions for AWS access
Q9: What are AWS Lambda layers?
Lambda layers allow packaging libraries and other dependencies to be shared and imported by Lambda functions. Layers separate shared dependencies from function code for improved reuse. Layers are locked to specific versions for immutability.
Q10: How do you monitor Lambda functions?
CloudWatch provides metrics for Lambda functions including invocations, errors, duration, and throttled requests. X-Ray enables tracing requests through functions. Logs can integrate with CloudWatch Logs Insights. Dashboards give overview visibility into metrics.
Q11: What are best practices for writing Lambda functions?
Best practices include:
- Keep functions stateless if possible
- Follow single responsibility principle – modular functions
- Optimize performance – reuse objects, keep functions lean
- Set functions to use maximum memory they need
- Handle errors and exceptions properly
- Add logging and instrumentation
- Follow security best practices
Q12: What are some key Lambda security considerations?
- IAM roles should follow principle of least privilege
- Encrypt environment variables
- Validate inputs and sanitize outputs
- Enable VPC for isolation
- Rotate secrets using Secrets Manager
- Monitor CloudTrail logs
- Run security checks with tools like cfn_nag
Q13: What are use cases suited for AWS Lambda?
Lambda excels for event-driven applications like:
- Processing uploads to S3
- Running ETL pipelines and workflows
- Integration and microservices glue code
- Serving web APIs
- React to DynamoDB data changes
- Serverless CRON jobs replacing scheduled instances
Lambda suits event-driven and intermittent workloads.
Q14: When is AWS Lambda NOT the best choice?
Lambda may not be ideal for:
- Long running or continuous processes – limited to 15 minutes
- Workloads requiring heavy compute or GPUs
- Steady state applications with sustained traffic
- Very cost sensitive workloads – can be expensive at high scale
- Low latency apps – additional start up latency
Q15: What are AWS Lambda limits to be aware of?
Key limits include:
- Execution: 15 mins max, 10GB disk capacity
- Deployment package: 50MB zipped, 250MB unzipped
- Concurrency: 1000 concurrent executions default
- Environment variables: 4KB max
- /tmp storage: 512MB max
- Invoke payload async: 256KB, sync 6MB
- Role limits – policies, AWS API rate limiting
Q16: How does AWS Lambda pricing work?
Lambda bills per number of requests and compute time consumed. Duration is calculated from execution start to return or termination. Memory allocated per function affects pricing.
1 million free requests provided monthly. Beyond that costs $0.20 per 1 million requests.
Q17: What are the components of the AWS Lambda architecture?
- AWS Management Console – Create, monitor, configure functions
- SDKs – Build and deploy Lambda functions programmatically
- CLI – Manage Lambda via AWS CLI
- Lambda Services – Self-healing and autoscaling infrastructure
- VPC – Optional network connectivity and isolation
- AWS X-Ray – Distributed tracing
- CloudWatch – Monitoring, logging and alerts
Q18: How do you deploy Lambda functions?
Functions can be deployed via:
- AWS Management Console
- AWS SAM templates – Infrastructure-as-code for Lambda and other resources
- AWS CloudFormation – IaC for broader AWS environment
- AWS SDK – Programatically deploy Lambda functions
- CI/CD pipelines – Automated testing and deployment to Lambda
Q19: What are the most common triggers for Lambda functions?
The most popular Lambda function triggers are:
- API Gateway – Execute function on HTTP requests
- S3 – Respond to S3 object uploads or changes
- CloudWatch Events – Execute on scheduled CRON jobs
- CloudWatch Logs – Process streaming log data
- SQS – Run on queue message delivery
- DynamoDB – Respond to data changes and events
Q20: How does calling AWS Lambda functions from your application code work?
The AWS SDK provides a Lambda client for calling functions from application code. The Lambda API exposes operations like Invoke to synchronously run a function while providing error handling and response metadata.
Q21: What is serverless computing?
Serverless computing refers to executing code without handling infrastructure provisioning or management. AWS Lambda is a serverless service since it transparently handles capacity, scaling, patching and more. Serverless allows focusing just on the application code.
Q22: How are Lambda functions isolated from other functions and tenants?
Lambda runs each function execution in its own isolated container including any declared external libraries or dependencies. Different users’ Lambda functions and data remain fully isolated.
Q23: What are AWS Lambda aliases?
Lambda aliases point to function versions and provide versioning capabilities like canary deployments. Aliases are mutable labels while versions are immutable. Aliases enable functions like staging, prod, canary, or per environment.
Q24: What is AWS Lambda@Edge?
Lambda@Edge allows deploying Lambda functions that execute right at AWS edge locations for use cases like modifying CloudFront CDN requests and responses. This allows lower latency running closer to users.
Q25: What are potential downsides of AWS Lambda to consider?
Potential downsides of Lambda include:
- Additional latency from cold starts
- Vendor lock-in – difficulty moving serverless code elsewhere
- Debugging and monitoring distributed functions can be hard
- Unpredictable or confusing pricing at high scale
Q26: What are common causes of errors in Lambda functions?
Common error causes include:
- Timeout from function executing too long
- Out of memory when memory allocated is insufficient
- Exceptions thrown within function logic
- Dependency failures from external calls
- Permission errors from improperly scoped IAM roles
- Software bugs failing under load
Monitoring helps identify and troubleshoot these issues.
Q27: How does AWS Lambda integrate with other services?
Lambda integrates natively with many AWS services for triggers like S3, SQS, and CloudWatch. It can also invoke other AWS APIs and resources like DynamoDB tables, SNS topics, Step Functions workflows and more to build serverless apps.
Q28: What are benefits of the AWS Serverless Application Model (SAM)?
SAM allows defining Lambdas, APIs, databases and other resources as code for consistent deployment and management. SAM provides shorthand YAML-based syntax to simplify configuring Lambda functions compared to standard CloudFormation.
Q29: What is the serverless trifecta?
The serverless trifecta refers to using Lambda, DynamoDB and API Gateway together as a fully managed cloud stack. This combination facilitates building a category of applications without managing servers.
Q30: What are best practices for writing and optimizing Lambda functions?
Best practices include:
- Streamline functions to critical logic
- Minimize external calls to avoid latency
- Initialize SDKs and database connections outside handler
- Leverage layers for common dependencies
- Use environment variables for configuration
- Enable provisioned concurrency for consistent performance
Q31: How does provisioned concurrency improve Lambda performance?
Provisioned concurrency initialize lambda instances in advance before they are invoked resulting in faster invocations. This avoids cold start latency since instances are immediately ready to serve requests without container initialization delay.
Q32: What tools can be used to optimize Lambda cost?
Tools to reduce Lambda cost include:
- AWS Lambda Power Tuning for optimizing settings
- Dashboards to monitor usage and spending
- Enable auto-scaling to shut down idle functions
- Prefer functions with smaller memory footprints
- Set restrictive permissions to prevent misuse
- Use Duration billing mode to cut idle time costs
Q33: How do you monitor Lambda functions?
Monitoring approaches include:
- CloudWatch metrics for invocation and performance data
- X-Ray tracing for granular timings and call graphs
- Logging to CloudWatch Logs
- Health checks and alarms based on metrics
- Dashboards correlating business KPIs to Lambda
- Tracking overall monthly Lambda costs
Robust monitoring ensures reliability.
Q34: How can you do load testing for Lambda functions?
Options for load testing Lambda include:
- Automated REST API testing tools like Artillery, Locust
- AWS SDK integration tests driving high traffic
- CloudWatch autoscaling rules to trigger spikes
- CI/CD pipeline load tests before deployment
- Chaos testing by randomly terminating instances
Load tests validate Lambda scalability.
Q35: How does AWS X-Ray help debug issues with Lambda?
X-Ray tracks function invocations end-to-end from trigger through downstream calls. X-Ray traces pinpoint failures and performance issues across distributed functions. Annotations add context.
Q36: What is a service role for Lambda?
The service role provides an IAM role granting Lambda permissions to integrate with and access other AWS resources at runtime like writing to S3 buckets or DynamoDB tables.
Q37: What are considerations around Lambda costs?
- Pay per request and compute time consumed
- Choose memory settings wisely – higher memory = higher cost
- Leverage reserved concurrency for predictable pricing
- No charge for unused functions or compute
- Evaluate tradeoffs of continuous vs triggered workloads
- Exits early on failure to reduce execution time
Carefully monitor and optimize based on usage patterns.
Q38: What are features for debugging Lambda functions?
Debugging features include:
- Logging to CloudWatch Logs
- Tracing with X-Ray
- Enabling active tracing via SDK
- Verbose CloudWatch metrics and triggers
- Configuring test events to locally invoke functions
- CloudWatch Log Insights queries
- AWS SAM local invocation
Leverage logs, metrics, traces and test invocations to squash bugs faster.
Q39: How does Lambda achieve high availability?
Lambda achieves HA by running functions across multiple Availability Zones automatically. Functions are replicated to prevent any single point of failure or one AZ outage. Lambda infrastructure is built for reliability.
Q40: What are cold starts in Lambda?
When a function is invoked after being idle, triggering its initialization introduces additional latency known as a cold start. Keeping functions busy helps amortize cold start across more executions.
Q41: How are Lambda functions scaled?
Lambda automatically scales capacity in and out in response to traffic. Additional instances are added seamlessly to handle concurrent spikes in traffic. Unused capacity is recycled after a few minutes to minimize costs.
Q42: What are execution contexts in Lambda?
Execution contexts provide functions with runtime environments including allocated CPU, memory, disk and network. Separate execution contexts isolate different functions and provide runtime dependencies.
Q43: Can Lambda functions enable inbound internet access?
Yes, functions can be configured to enable public internet access via NAT gateways. Access can be locked down to authorized sources via security groups. Private-only functions with no internet use VPC.
Q44: What are some alternatives or competitors to AWS Lambda?
Major competitors and alternatives include:
- Google Cloud Functions
- Azure Functions
- IBM Cloud Functions
- Alibaba Function Compute
- Apache OpenWhisk
- Auth0 Webtasks
But AWS Lambda remains the most mature and robust serverless offering.
Q45: What languages allow creating functions as Lambda Layer ARNs for reuse?
Python and Ruby allow deploying functions as layers. Node.js allows packaging dependencies as layers. Java archives can also be used as layers.
Q46: Can multiple functions be bundled to simplify management?
Yes, the Serverless Application Model (SAM) allows defining and deploying groups of Lambda functions together along with APIs, databases and other resources needed.
Q47: What are the most common causes of Lambda failures?
Most failures are from:
- Function code errors from bugs or issues in handling data.
- Permissions errors when incorrectly scoped roles restrict resources.
- Runtime issues from exceeding Lambda environment limits like timeouts.
- Dependency failures when functions rely on faulty external services.
- Suboptimal memory configuration causing OOM failures under load.
Monitoring helps quickly identify and troubleshoot these failure points.
Q48: What are considerations for migrating legacy apps to Lambda?
- Decomposing monoliths into microservices functions
- Assessing triggers versus continuous executions
- Optimizing around stateless functions where possible
- Rethinking data storage and access patterns
- Comparing cost of refactoring vs operating at scale
- Validating performance under load – avoid large dependencies
It requires breaking apart and optimizing workloads for Lambda’s execution model.
Q49: Where are some real-world examples of large scale Lambda deployments?
Major examples include:
- Netflix – Transcoding media files
- ATP Tour – Serverless event architecture
- Target – Web services and data processing
- Nike – Order and supply chain management
- Expedia – Personalizing search experiences
- New York Times – Optimizing media encoding
Q50: How can you migrate a REST API to API Gateway and Lambda?
- Wrap existing endpoints in Lambda functions
- Migrate request processing into Lambda functions
- Configure API Gateway methods to map to Lambda functions
- Migrate existing endpoints incrementally
- Mock dependencies or convert to services
This allows scaling endpoints serverlessly while reusing business logic.
These AWS Lambda interview questions test the reader’s knowledge across key aspects like Lambda functions, triggers, monitoring, pricing, architecture, integration, security, debugging and more. Mastering Lambda fundamentals is essential for leveraging serverless.
The questions range from basic concepts around functions and serverless to more advanced performance tuning, scaling, and reliability considerations. Studying these questions and answers will provide a solid grounding in applying Lambda across use cases.