OpenTelemetry Python guide – Walkthrough, hacks and Examples
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OpenTelemetry in a Nutshell
OpenTelemetry (OTel) is an open-source observability framework that allows developers to capture telemetry data from distributed cloud-native applications. It provides APIs, tools, and SDKs to collect and generate traces, metrics, and logs. OpenTelemetry can be used with multiple programming languages.
One of its key features is related to capturing and propagating distributed traces and spans across different services and components. It also supports capturing and exporting metrics like request latency, error rates, and resource usage that can be used to monitor and generate alerts on various aspects of the system.
Some of its advantages:
A unified and standardized method for collecting telemetry data.
Support for multiple export formats, including popular observability platforms like Prometheus, Jaeger, and Zipkin.
It’s a vendor-agnostic.
This article demonstrates the process of OTel-based python observability and tracing so you can capture and export traces and metrics from your apps. It will show how to integrate it with popular observability tools, and also how to enrich it with unique visibility and error data
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