Integrating Lambda with AWS services
1. Integrating Lambda with AWS services
In this video, you'll learn the integration pattern: an event triggers Lambda, and your handler uses the AWS SDK to work with services like DynamoDB and S3 under least-privilege IAM.2. The integration loop
Most Lambda integrations follow the same loop: event in, handler logic, then an SDK call.3. Triggers vs SDK calls
A trigger decides when Lambda runs. SDK calls inside the handler read and write services like DynamoDB and S3.4. A concrete example
We'll keep coming back to this example: a file lands in S3, Lambda runs, and we store a small record in DynamoDB.5. Event payload: locate what you need
Start by finding the fields your handler needs. For an S3 trigger, the bucket name and object key are the essentials.6. Where the AWS SDK fits
Your handler doesn't talk to DynamoDB directly. In Python, that usually means `boto3`: your code calls the SDK, the SDK calls AWS APIs, and IAM is the gatekeeper.7. Execution role = credentials
Lambda gives your code temporary credentials from the execution role, so you do not put access keys in code. If the role cannot call an API, the SDK call fails.8. Least privilege: scope actions + resources
Least privilege reduces blast radius. Grant only the actions and resources the function needs, and avoid wildcards unless you truly need them.9. DynamoDB: choose the right operation
`PutItem` writes, `GetItem` reads by key, and `Query` finds related items. The operation you choose changes cost and latency, so prefer targeted operations over broad scans.10. S3: work with bucket + key
S3 interactions are object-focused. Once you have bucket and key, `GetObject` can fetch content and `PutObject` can write a new derived file.11. Put configuration in environment variables
Hardcoding resource names is brittle. Environment variables let you deploy the same code to dev and prod safely.12. SDK code: keep it small and testable
Keep the handler simple: validate inputs, call the SDK, and return. Then you can unit test the pure logic without needing live AWS calls.13. Handle SDK errors deliberately
Permission errors are common at first, so when an SDK call fails, make it obvious why. Good logs and clear failure behavior make debugging safer.14. When IAM is wrong, code looks fine
If a function hits `AccessDenied`, the execution role policy is missing something. Fix IAM before changing handler logic.15. Idempotency: safe retries and duplicates
If you might see the same event twice, you want safe repeats. Idempotency keys and conditional writes help you avoid double processing.16. Putting it together (end to end)
This is the core pattern: an S3 event brings in bucket and key, your handler parses them, `PutItem` writes metadata to DynamoDB, and CloudWatch Logs show what happened.17. Key takeaways
Separate triggers from SDK calls, keep permissions tight with the execution role, and make configuration portable with environment variables.18. Let's practice!
Let's put this into practice with some exercises!Create Your Free Account
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