trace-context-w3c
opentelemetry-js
trace-context-w3c | opentelemetry-js | |
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11 | 16 | |
4 | 2,472 | |
- | 2.2% | |
0.0 | 9.4 | |
about 1 year ago | 4 days ago | |
C# | TypeScript | |
- | Apache License 2.0 |
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trace-context-w3c
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Implementing OTel Trace Context Propagation Through Message Brokers with Go
The answer is Context Propagation. The HTTP example is a classic and W3C even covers it. The propagation is adding the important fields from the context into the HTTP headers and having the other application extract those values and inject them into its trace context. This concept applies to any other way of communication. Here, we will focus on message brokers and how you can achieve context propagation for those.
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OpenTelemetry in 2023
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/
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End-to-end tracing with OpenTelemetry
-- https://www.w3.org/TR/trace-context/
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Event Driven Architecture — 5 Pitfalls to Avoid
For context propagation, why not just reuse the existing trace context that most frameworks and toolkits generate for http requests? I've had to apply some elbow grease to get it play nice but once it does you're able to use tools like Jeager, etc as part of your asynchronous flow as well.
- W3C Recommendation – Trace Context
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OpenTelemetry and Istio: Everything you need to know
(Note that OpenTelemetry uses, by default, the W3C context propagation specification, while Istio uses the B3 context propagation specification – this can be modified).
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What is Context Propagation in Distributed Tracing?
World Wide Web Consortium (W3C) has recommendations on the format of trace contexts. The aim is to develop a standardized format of passing trace context over standard protocols like HTTP. It saves a lot of time in distributed tracing implementation and ensures interoperability between various tracing tools.
- My Logging Best Practices
- Validação de entrada de dados e respostas de erro no ASP.NET
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[c#] Using W3C Trace Context standard in distributed tracing
The main objective is to propagate a message with traceparent id throw two APIs and one worker using W3C trace context standard. The first-api calls the second-api by a http call while the second-api has an asynchronous communication with the worker by a message broker (rabbitmq was chosen for that). Furthermore, zipkin was the trace system chosen (or vendor as the standard call it), being responsible for getting the application traces and building the distributed tracing diagram:
opentelemetry-js
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OpenTelemetry Journey #01 - Important concepts
JavaScript
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OpenTelemetry in 2023
> OpenTelemetry is a marketing-driven project, designed by committee, implemented naively and inefficiently, and guided by the primary goal of allowing Fortune X00 CTOs to tick off some boxes on their strategy roadmap documents.
I'm the founder of highlight.io. On the consumer side as a company, we've seen a lot of value of from OTEL; we've used it to build out language support for quite a few customers at this point, and the community is very receptive.
Here's an example of us putting up a change: https://github.com/open-telemetry/opentelemetry-js/pull/4049
Do you mind sharing why you think no-one should be using it? Some reasoning would be nice.
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OpenObserve: Elasticsearch/Datadog alternative in Rust.. 140x lower storage cost
That's traces? I was wondering if I could use https://github.com/open-telemetry/opentelemetry-js/tree/main...
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OpenObserve: Open source Elasticsearch/Datadog/Splunk alternative in Rust for logs. 140x lower storage cost
Nothing like Faro for now. However, https://github.com/open-telemetry/opentelemetry-js can be used to achieve the same result and OpenObserve has great support for Opentelemetry.
- Deno 1.33: Deno 2 is coming
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Observable front-end applications - an open source product experiment
Can it be integrated with Grafana Faro or OpenTelemetry?
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Logs and tracing: not just for production, local development too
4. Register automatic instrumentations. For example, you can automatically trace all XHR requests, fetch requests, page loads, and user interactions. With distributed tracing, you should always prefer automatic instrumentation whenever possible to reduce maintenance and leverage existing conventions. The document load instrumentation allows you to treat the server as the parent span to a given page load, from which the client will then be the root span to everything in the server. This is an extremely powerful concept that allows traces to viewed from the perspective of the user, encapsulating all requests and user interactions in a single trace with no manual instrumentation!
We also trialed Sentry's APM tool (also marketed as a distributed tracing tool). While it had pretty charts, dashboards, niceties like core web vitals, and integrated well with Sentry's error product, its utility as a distributed tracing tool is significantly less powerful than tools like Honeycomb. You will end up using a large amount of your user's bandwidth sending telemetry data that can't fully be leveraged in the Sentry UI. When I last used (in April 2021), the spans of a given trace could only be viewed in a specific part the UI and they couldn't be searched for in queries or used in charts. I'm unsure if this has been updated. But this is not the worse part. Because Sentry uses its own data model for traces, it is not compatible with open source standards such as OpenTelemetry or OpenTracing! The sales team will not tell you this during the trial. This means our entire backend, which was already instrumented with OpenTracing, would now also need to instrument Sentry's tracing (...if they supported the language) in order to connect frontend traces to backend traces. Each team I met with their sales team, I said the same thing: support OpenTelemetry, otherwise you are asking for us to further isolate our backend and frontend teams.
It looks like they have heard this opinion, as they have recently published a blog post about the evolution of the distributed tracing API, citing incompatibility with OpenTelemetry due to their data model. It will require a very large change for them to support this. Meanwhile, OpenTelemetry can be used with any tracing vendor, a large number of languages, the other major instrumentation standards (OpenTracing, OpenCensus), and any trace propagation format.
- [1]: https://github.com/open-telemetry/opentelemetry-js
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Monitoring consumer lag in Azure Event Hub
Consumer lag will quickly show any functional or technical issue with your event stream. By using the code examples from this blogpost, you can avoid having to dive into the SDKs yourself. Of course, you can adopt the metric collection to send the metric to the logs or to another metrics system like prometheus, datadog, or open telemetry.
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Any good tutorial showing you which library to use for dependency injection in a project?
I would work on getting Open Telemetry pointed at an “all-in-one” Jaegar instance and move on from there: https://www.jaegertracing.io/docs/1.25/getting-started/ https://github.com/open-telemetry/opentelemetry-js Various cloud providers may have a way to collect/view traces as well, but, Jaegar and the Open Telemetry Collector are the open source way to do that. The projects are in the process of converging in some ways — everything is in flux.
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Distributed Tracing 101 for Full Stack Developers
OpenTelemetry is a collection of open source tools, APIs, and SDKs for instrumenting, generating, and exporting telemetry data from running software. It provides language-specific implementations for most popular programming languages, including both browser JavaScript and Node.js.
What are some alternatives?
b3-propagation - Repository that describes and sometimes implements B3 propagation
Sentry - Developer-first error tracking and performance monitoring
opentelemetry-dotnet - The OpenTelemetry .NET Client
prom-client - Prometheus client for node.js
Serilog.Exceptions - Log exception details and custom properties that are not output in Exception.ToString().
PostHog - 🦔 PostHog provides open-source product analytics, session recording, feature flagging and A/B testing that you can self-host.
zipkin - Zipkin is a distributed tracing system
signoz - SigNoz is an open-source observability platform native to OpenTelemetry with logs, traces and metrics in a single application. An open-source alternative to DataDog, NewRelic, etc. 🔥 🖥. 👉 Open source Application Performance Monitoring (APM) & Observability tool
opentelemetry-specification - Specifications for OpenTelemetry
InversifyJS - A powerful and lightweight inversion of control container for JavaScript & Node.js apps powered by TypeScript.
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
nestjs-commander - A module for using NestJS to build up CLI applications