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This is where things get complicated. Implementing such a system is a lot of work, and you should rely on upcoming standards like the W3C recommendation on trace contexts. You should rely on a standard because they solve two major pain points with observability: (1) they have popular implementations like OpenTelemetry (OTel) – which happens to be the second most active CNCF project to this day – and (2) they are widely adopted by major observability backends (e.g., Datadog).
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Here is the detail of a trace generated for the code above, visualized using a local Jaeger instance:
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This is where things get complicated. Implementing such a system is a lot of work, and you should rely on upcoming standards like the W3C recommendation on trace contexts. You should rely on a standard because they solve two major pain points with observability: (1) they have popular implementations like OpenTelemetry (OTel) – which happens to be the second most active CNCF project to this day – and (2) they are widely adopted by major observability backends (e.g., Datadog).
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This will not scale with the volume of data, because the overhead associated with sending each piece of data is large in comparison to the volume of each individual piece. This is why most observability frameworks – including loggers like winston – buffer telemetry data before exporting it.