opentelemetry-specificatio VS opentelemetry-proto

Sure, happy to provide more specifics!

Our main issue was the lack of a synchronous gauge. The officially supported asynchronous API of registering a callback function to report a gauge metric is very different from how we were doing things before, and would have required lots of refactoring of our code. Instead, we wrote a wrapper that exposes a synchronous-like API: https://gist.github.com/yolken-airplane/027867b753840f7d15d6....

It seems like this is a common feature request across many of the SDKs, and it's in the process of being fixed in some of them (https://github.com/open-telemetry/opentelemetry-specificatio...)? I'm not sure what the plans are for the golang SDK specifically.

Another, more minor issue, is the lack of support for "constant" attributes that are applied to all metrics. We use these to identify the app, among other use cases, so we added wrappers around the various "Add", "Record", "Observe", etc. calls that automatically add these. (It's totally possible that this is supported and I missed it, in which case please let me know!).

Overall, the SDK was generally well-written and well-documented, we just needed some extra work to make the interfaces more similar to the ones were were using before.

Two problems with OpenTelemetry:

1. It doesn't know what the hell it is. Is it a semantic standard? Is a protocol? It is a facade? What layer of abstraction does it provide? Answer: All of the above! All the things! All the layers!

2. No one from OpenTelemetry has actually tried instrumenting a library. And if they have, they haven't the first suggestion on how instrumenters should actually use metrics, traces, and logs. Do you write to all three? To one? I asked this question two years ago, not a single response. [1]

[1] https://github.com/open-telemetry/opentelemetry-specificatio...

That's why you have otel logging: https://github.com/open-telemetry/opentelemetry-specificatio...

There are a large amount of subtle tradeoffs around the bucketing scheme (log, vs. log-linear, base) and memory layout (sparse, dense, chunked) the amount of configurability in the histogram space (circllhist, DDSketch, HDRHistogram, ...). A good overview is this discussion here:

https://github.com/open-telemetry/opentelemetry-specificatio...

As for the circllhist: There are no knobs to turn. It uses base 10 and two decimal digits of precision. In the last 8 years I have not seen a single use-case in the operational domain where this was not appropriate.

A good place to look at is the milestones on GitHub: https://github.com/open-telemetry/opentelemetry-specificatio...

Logging is still experimental in the spec. Metrics API is feature freeze and the protocol is stable, so it's more on language SDKs to stabilize their implementations. This is a focus for several of them right now.

Maybe, you are asking yourself: "But I already had instrumented my applications with vendor-specific libraries and I'm using their agents and monitoring tools, why should I change to OpenTelemetry?". The answer is: maybe you're right and I don't want to encourage you to update the way how you are doing observability in your applications, that's a hard and complex task. But, if you are starting from scratch or you are not happy with your current observability infrastructure, OpenTelemetry is the best choice, independently of the backend telemetry tool that you are using. I would like to invite you to take a look at the number of exporters available in the collector contrib section, if your backend tracing tool is not there, probably it's already using the Open Telemetry Protocol (OTLP) and you will be able to use the core collector. Otherwise, you should consider changing your backend telemetry tool or contributing to the project creating a new exporter.

Here's the example payloads for OTLP over JSON and example of how to ingest them: https://github.com/open-telemetry/opentelemetry-proto/tree/m...

An OTLP receiver can receive data via gRPC or HTTP using the OTLP format. There are advanced configurations that you can enable via the YAML file.

Cerbos fully transitioned from OpenCensus to OpenTelemetry, a move that significantly boosts our metrics and tracing capabilities. This shift allows for more efficient integration with a variety of observability products supporting the OpenTelemetry protocol (OTLP) but also offers the flexibility to use push metrics and fine-tune trace sampling. With this update, configuration through the tracing block in Cerbos files is deprecated in favor of using OpenTelemetry environment variables.

Networking is Easy (Really!) Since you install the agent directly into the environment where you are running your application, there is no complex networking. When developing in localMode, the agent listens on the common OpenTelemetry Line Protocol (OTLP) on ports 4317 & 4318 automatically.

Oh nice, thank you (and also solumos) for the links! It looks like oteps/pull/171 (merged June 2023) expanded and superseded the opentelemetry-proto/pull/346 PR (closed Jul 2022) [0]. The former resulted in merging OpenTelemetry Enhancement Proposal 156 [1], with some interesting results especially for 'Phase 2' where they implemented columnar storage end-to-end (see the Validation section [2]):

* For univariate time series, OTel Arrow is 2 to 2.5 better in terms of bandwidth reduction ... and the end-to-end speed is 3.1 to 11.2 times faster

* For multivariate time series, OTel Arrow is 3 to 7 times better in terms of bandwidth reduction ... Phase 2 has [not yet] been .. estimated but similar results are expected.

* For logs, OTel Arrow is 1.6 to 2 times better in terms of bandwidth reduction ... and the end-to-end speed is 2.3 to 4.86 times faster

* For traces, OTel Arrow is 1.7 to 2.8 times better in terms of bandwidth reduction ... and the end-to-end speed is 3.37 to 6.16 times faster

[0]: https://github.com/open-telemetry/opentelemetry-proto/pull/3...

[1]: https://github.com/open-telemetry/oteps/blob/main/text/0156-...

[2]: https://github.com/open-telemetry/oteps/blob/main/text/0156-...

We then modified the benchmark to encode our example data which is an opentelemetry trace data.