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How To Troubleshoot and Monitor Production Applications using OpenTelemetry

Description

OpenTelemetry is a free, open-source Observability Protocol. OpenTelemetry sits at the application layer, and exports Traces, Metrics, and Logs to a backend for observing. It is extremely helpful and beneficial to developers in mean "time-to-detection" and "time-to-resolution" of bugs and issues that occur at the application layer; this ranges from detecting and alerting for errors raised (such as TypeError), to finding that a specific microservice (such as AWS Lambda) ran for twice as long as usual, all the way to seeing the output of a service and comparing it to the expected output to find a bug in the logic of the service.
This tutorial is geared towards beginner/intermediate Python developers, who have some experience in Python, its syntax, and very minimal experience in Requests and Flask is needed (extremely popular libraries, with 50k and 60k stars on GitHub, respectively). No OpenTelemetry experience is needed at all. This is a total and complete introduction into OpenTelemetry, consisting instrumenting your first application, viewing your first traces and metrics, and if time-allows then deploying your first Jaeger instance locally (no experience is needed, only Docker desktop), to allow students of this workshop tutorial to build their own in-house observability platform, be-it for their selves or employers.
It is important that every developer have at least a solid understanding of Traces, Metrics, and Logs, which we know today as the three pillars of observability. These are the foundational building blocks for monitoring Production environments at the application layer. The extended base workshop is available here and the base slides are available here. Thank you.

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