AWS Lambda in Python with Datadog Integration

Introduction AWS Lambda is a serverless compute service that allows running code without provisioning or managing servers. It automatically scales applications by running code in response to events. Monitoring and observability are crucial for maintaining performance and reliability, and Datadog provides powerful tools to monitor Lambda functions, collect metrics, and visualize logs. This guide explains how to integrate AWS Lambda written in Python with Datadog, including setup steps and sample Python code. Prerequisites AWS account with permissions to create and manage Lambda functions Datadog account with API key AWS CLI and Datadog CLI installed Python 3.8 or later Step 1: Create a Python AWS Lambda Function Open the AWS Management Console. Navigate to Lambda > Create function. Choose Author from scratch. Enter a function name (e.g., lambda-datadog-demo). Select Python 3.9 as the runtime. Choose or create an execution role with permissions for CloudWatch Logs. Click Create function.