b3-propagation VS signoz

I've been playing with OTEL for a while, with a few backends like Jaeger and Zipkin, and am trying to figure out a way to perform end to end timing measurements across a graph of services triggered by any of several events.

Consider this scenario: There is a collection of services that talk to one another, and not all use HTTP. Say agent A0 makes a connection to agent A1, this is observed by service S0 which triggers service S1 to make calls to S2 and S3, which propagate elsewhere and return answers.

If we limit the scope of this problem to services explicitly making HTTP calls to other services, we can easily use the Propagators API [1] and use X-B3 headers [2] to propagate the trace context (trace ID, span ID, parent span ID) across this graph, from the origin through to the destination and back. This allows me to query the metrics collector (Jaeger or Zipkin) using this trace ID, look at the timestamps originating at the various services and do a T_end - T_start to determine the overall time taken by one call for a round trip across all the related services.

However, this breaks when a subset of these functions cannot propagate the B3 trace IDs for various reasons (e.g., a service is watching a specific state and acts when the state changes). I've been looking into OTEL and other related non-OTEL ways to capture metrics, but it appears there's not much research into this area though it does not seem like a unique or new problem.

Has anyone here looked at this scenario, and have you had any luck with OTEL or other mechanisms to get results?

[1] https://opentelemetry.io/docs/specs/otel/context/api-propaga...

[2] https://github.com/openzipkin/b3-propagation

[3] https://www.w3.org/TR/trace-context/

(Note that OpenTelemetry uses, by default, the W3C context propagation specification, while Istio uses the B3 context propagation specification – this can be modified).

The default format for context propagation is B3 so we use headers X-B3-TraceId and X-B3-SpanId

You should also check out SigNoz [1], we are an open-core alternative to DataDog - based natively on OpenTelemetry. We also have a cloud product if you don't want to host yourself

[1] https://signoz.io

You might want to have a look at SigNoz [1] as well. We have also published some perf benchmark wrt Elastic & Loki [2] and have some cool features like logs pipeline for manipulating logs before ingestion

[1] https://github.com/signoz/signoz

Check Signoz's repo on GitHub

SigNoz maintainer here.

We also have traces, metrics and logs in a single application which makes correlation across them much easier. From what I can understand from Quickwit website, they use Grafana and Jaeger for UI.

Here'e our github repo if you want to check it out. https://github.com/signoz/signoz

Using user's private with no opt-out option is unethical.

If anyone is looking self-hosted for alternatives then they should try SigNoz: https://github.com/SigNoz/signoz

SigNoz is a great New Relic alternative that is open-source and provides three signals in a single pane of glass. You can monitor logs, metrics, and traces and correlate signals for better insights into application performance.

If anyone wants to check the project, here's our github repo - https://github.com/signoz/signoz

You need a backend to which you can send the collected data for monitoring and visualization. SigNoz is an OpenTelemetry-native APM that is well-suited for visualizing OpenTelemetry data.

Once the data is collected, it needs to be sent to a backend. That’s where SigNoz comes into the picture. SigNoz is an open-source OpenTelemetry-native APM that provides logs, metrics and traces under a single pane of glass.