Uploaded August 2022 | Updated September 2026, 8 minutes ago

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AWS Lambda functions are a great way to deploy your Python code or API (e.g. Flask, FastAPI) - at a cheap cost and not having to worry about servers.

But since Lambda functions are ephemeral (they disappear after they finish running), how do we persist data? In this tutorial, we'll use AWS DynamoDB as a database for us to store information used by our Lambda functions.

🛠 Essential Links
🔗 Code: github.com/pixegami/python-lambda-with-database

📚 Resources
🔗 AWS: aws.amazon.com
🔗 AWS CLI: aws.amazon.com/cli
🔗 Boto3 (Python AWS SDK): boto3.amazonaws.com/v1/documentation/api/latest/index.html

💡 Learn More! (Related tutorials)
🔗 FastAPI on AWS Lambda: youtu.be/RGIM4JfsSk0
🔗 AWS Infrastructure with CDK: youtu.be/o3s4VqlMsT8

📽 Chapters

00:00 Introduction
01:04 Create an AWS Lambda function
04:00 Implement Lambda handler in VS Code
07:20 Create a DynamoDB table on AWS
10:36 Configure AWS CLI
12:00 Access DynamoDB from Python (using boto3)
17:30 Deploy to Lambda
20:30 Granting your Lambda function access to DynamoDB
22:37 The function can now save data!
23:40 Wrapping up

#aws #pixegami