Tracing asynchronous Python code with Datadog APM

Datadog APM's Python tracing client now supports integration with several asynchronous libraries such as asyncio, aiohttp, gevent, and Tornado. This enables developers to gain visibility into their distributed applications using end-to-end flame graphs with minimal configuration. Asynchronous programming optimizes I/O-bound Python applications by implementing cooperative multitasking instead of multithreading. Datadog's Python APM client has been designed specifically for async support, allowing users to trace and debug asynchronous code more effectively. The end-to-end flame graphs provide insights into how tasks are executed concurrently across the environment, helping developers identify errors or latency issues in their applications. To start tracing asynchronous Python applications, users need to configure the tracer with the correct context provider based on the async framework or library they're using.