Tracing asynchronous Python code with Datadog APM

Datadog APM's Python tracing client now integrates with several asynchronous libraries to provide end-to-end visibility into distributed applications. Asynchronous programming optimizes I/O-bound Python applications by implementing cooperative multitasking, but it can make tracing and debugging more challenging due to context switching. Datadog's Python APM client has been designed to include async support, allowing users to easily instrument synchronous or asynchronous code. The client provides end-to-end flame graphs that enable tracing of individual requests across service boundaries, helping identify errors and latency issues. By integrating with popular async libraries, the client can auto-instrument applications and provide targeted alerts for service-level indicators such as p95 latency and 5xx error rates.

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