AWS Lambda Python functions with a database (DynamoDB)

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: https://github.com/pixegami/python-la... 📚 Resources 🔗 AWS: https://aws.amazon.com 🔗 AWS CLI: https://aws.amazon.com/cli 🔗 Boto3 (Python AWS SDK): https://boto3.amazonaws.com/v1/docume... 💡 Learn More! (Related tutorials) 🔗 FastAPI on AWS Lambda:    • Deploy FastAPI on AWS Lambda ⚡ Serverless ...   🔗 AWS Infrastructure with CDK:    • AWS CDK Tutorial: Deploy a Python Lambda F...   📽 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