Used For

• +**Your photo uploads take 2-4 hours to process in batches** → Each image resizes automatically in under 1 second as soon as it's uploaded
• +**Your ETL scripts fail overnight and you find out the next morning** → Data moves instantly when changes happen, with automatic retries and alerts
• +**You're running a $500/month server that's only busy 10% of the time** → Pay only when code actually runs, typically dropping costs 50-80%
• +Handles 1,000 simultaneous requests per function automatically - no load balancer configuration or capacity planning
• +Connects to 220+ AWS services without writing integration code - just pick your trigger and go

Best For

• >Your image processing keeps crashing your $200/month server that sits idle 90% of the time
• >Building APIs without wanting to babysit servers at 3am when traffic spikes
• >You're already deep in AWS and need something to glue all your services together

Not For

• -Teams without developers — this requires actual coding, not drag-and-drop automation
• -Apps that need to run longer than 15 minutes — Lambda kills your function dead at the time limit
• -Anyone sensitive to 1-10 second delays — cold starts will frustrate users expecting instant responses

Pairs With

• *S3 (where files land that trigger Lambda to process them automatically)
• *API Gateway (to turn Lambda functions into proper REST APIs that frontend apps can call)
• *DynamoDB (for storing data since Lambda functions can't remember anything between runs)
• *CloudWatch (where you'll spend way too much time debugging why your function failed at 2am)
• *Step Functions (to chain multiple Lambda functions together when one isn't enough)
• *EventBridge (to schedule Lambda functions or trigger them from external apps)
• *RDS or Redshift (where Lambda dumps the processed data for your actual applications to use)

The Catch

• !Memory allocation mistakes will triple your bill - set it to 1GB when you need 128MB and watch costs explode
• !That 1,000 concurrent execution limit hits faster than expected during traffic spikes, causing throttling
• !Cold starts are worse for complex functions - importing big libraries like pandas adds 3-5 seconds to startup time

Bottom Line

Pay-per-millisecond code execution that's either genius or a money pit depending on whether you optimize it.