AWS Lambda is a serverless compute service that automatically manages the compute fleet and scales based on demand. It's best used for short-lived, event-driven tasks. Below are typical use cases where Lambda excels.
Real-time file processing (e.g., image resizing or video transcoding after upload to S3)
Data transformation pipelines (e.g., ETL jobs triggered by data uploads or stream updates)
Webhooks and APIs (e.g., responding to HTTP requests via API Gateway)
Automation of cloud tasks (e.g., cleaning up unused resources, backup tasks)
Real-time stream processing (e.g., processing records from Kinesis or DynamoDB Streams)
Chatbot or voice assistant backend logic (e.g., Amazon Lex or Alexa)
Scheduled tasks and cron jobs (e.g., running a function every night)
Authentication triggers (e.g., post-login hooks in Cognito)
IoT data processing (e.g., processing sensor data from IoT Core)
How would you use Lambda to automatically resize images when they're uploaded to an S3 bucket?
What happens if your Lambda function times out while processing a large file from S3?
You need to run a database cleanup script every night at 2 AM. How would you set that up with Lambda?
You're building a Stripe webhook handler with API Gateway and Lambda. The function occasionally times out during traffic spikes. How would you debug and fix this?
Your team wants to move a nightly cron job from an EC2 instance to Lambda. What tradeoffs would you evaluate before migrating?
A Lambda function processing SQS messages starts throwing 'RequestId not found' errors. What could cause this and how would you investigate?
Design a serverless image processing pipeline using Lambda, S3, and Step Functions that handles 10,000 uploads per minute. Where are the bottlenecks?
Your Lambda functions suffer from cold starts that hurt P99 latency. What mitigation strategies would you evaluate and how would you measure their impact?
You need to incrementally migrate a monolithic Express.js application to Lambda. How would you approach the migration without a big-bang rewrite?
Your organization has 500+ Lambda functions across teams with inconsistent runtimes, logging, and deployment practices. How would you standardize governance without slowing feature delivery?
A critical legacy system runs on Lambda with Node.js 12 (end-of-life). Plan a migration strategy that minimizes risk and coordinates across five dependent teams.
You're evaluating Lambda versus ECS containers for a new high-throughput, low-latency service. What architectural criteria would drive the decision, and how would you validate them?