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Comment by niftaystory | Hacker News Reader

Code traces are metrics. Run times per function calls metrics, count of specific function call metrics.

Otel is an attempt to package such arithmetic.

Web apps have added so many layers of syntax sugar and semantic wank, we’ve lost sight its all just the same old math operations relative to different math objects. Sets are not triangles but both are tested, quantified, and compared with the same old mathematical ops we learn by middle school.

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No, code traces are not just metrics; and while you can knit together something approximating traces from metrics, you'll quickly run into the reason why traces are a distinct thing. First, in a distributed system, you'll discover that you can't rely on clocks to get the timing of subsecond events correct. Second, you'll be contextless about code paths. So, you might independantly reinvent the idea of passing along a context - and now you're just making your own tracing system but without any of the benefit of building on years of existing discoveries in this field.

OTel does feel a little bit heavy, unless you're already used to e.g. New Relic, Dynatrace, etc. where you have to run an agent process and instrumentize your code to some extent; it's never going to be free to audit every function call! This is why (a) you sample down and don't keep every trace, and (b) unless your company is extremely flush with cash you probably don't run tracing in every environment. If you can get away with it just in a staging or perf test env you can reap most of the benefit without the production impact and cost.

All those things you describe are computable metrics. They have to be or Otel itself would not be able to compute them for consumption. All you described are cherry picked semantic indirections to obfuscate it’s all just a computer computing metrics of its own memory states.

Sorry for knowing how computers actually work (EE grad not a CS grad). I know that can frustrate CS grads who think their preferred OS and favorite programming language is how a computer works. You’re describing how contemporary SWEs view their day job.

Edit: teleMETRY …what’s in a name? Oh right …meaning.

As a no grad to EE grad: traces mean a bundle of metrics that varies in structure hence you can't store and process them as effective as a list of counters unless you have a distinct bin for each possible trace, combinatorial explosion y'know.

You know the conversation is going well for you when you resort to citing the "meaning" of a name instead of, you know, base reality. Who needs the territory, I've got my map right here.

Speaking of meaning, the best I can make of your point is that you're using a much broader definition of "metrics" than the rest of this conversation, and in particular broader than Prometheus (remember context? very important for "meaning"!) supports. That or you really just don't know what a "trace" is (in this context).

To be a smart-ass, one has to be smart first. Quit this.

OpenTelemetry's traces are trees of spans. You cannot represent this efficiently without a combinatorial explosion of labels.

You may be thinking of metrics in the sense of counters and gauges, but that's not the data model that OpenTelemetry (and before they, Zipkin, Jaeger, and OpenCensus) uses for traces.

The data model for tracing is to emit events that provide a span ID and an optional parent span ID. The event collector can piece these together into a tree after the fact, which will work as long as the parent structure is maintained.

Prometheus is absolutely not suitable for this.

Quibbling about the word "telemetry" doesn't really help here. OpenTelemetry supports three different, completely different subsets of functionality: Metrics (counters, gauges, histograms), traces (span events in a tree structure), and logging (structured log events). They each have completely different client interfaces.

huh? I've always heard and read and experienced that "logs, traces, metrics" are the 3 legs of the observability stool.

Open teleMETRY

Any guesses as to etymology?

By this logic, you can say that logging, metrics and tracing are all fundamentally just different kinds of data and we should be calling it just plain databases and CRUD.

They're related, but people have a very specific idea and concept of what each is, you haven't actually provided a good argument why we should throw out these distinctions just because they somewhat resemble each other if you ignore a few details

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