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The latest News and Information on Distributed Tracing and related technologies.

sumologic

Configuring the OpenTelemetry Collector

Sep 10, 2020 By Dave Sudia In Sumo Logic
The OpenTelemetry Collector is a new, vendor-agnostic agent that can receive and send metrics and traces of many formats. It is a powerful tool in a cloud-native observability stack, especially when you have apps using multiple distributed tracing formats, like Zipkin and Jaeger; or, you want to send data to multiple backends like an in-house solution and a vendor. This article will walk you through configuring and deploying the OpenTelemetry Collector for such scenarios.
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splunk

Splunk Now Top Contributor to OpenTelemetry

Sep 8, 2020 By Tim Tully In Splunk

Editor’s note: This post is a collaboration between Tim Tully, Splunk CTO, and Spiros Xanthos, Splunk’s vice president of product management for observability and IT Ops and previously the founder and CEO of Omnition. My love for the open-source software movement began with Linux in the ’90s and grew during my time at Yahoo! in the early days of Hadoop.

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honeycomb

Interview with Honeycomb Engineer Chris Toshok: Dogfooding OpenTelemetry

Sep 3, 2020 By Shelby Spees In Honeycomb

At Honeycomb, we talk a lot about eating our own dogfood. Since we use Honeycomb to observe Honeycomb, we have many opportunities to try out UX changes ourselves before rolling them out to all of our users. UX doesn’t stop at the UI though! Developer experience matters too, especially when getting started with observability. We often get questions about the difference between using our Beeline SDKs compared with other integrations, especially OpenTelemetry (abbreviated “OTel”).

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Debugging, distributed tracing, and profiling for web applications

Aug 21, 2020 By Google Operations In Google Operations
Google Cloud offers many tools that can help you manage your application services. In this video, we teach you how to set up and utilize Cloud Trace, Cloud Profiler, and Cloud Debugger to collect latency data across different services, memory-allocation information, and inspect application code locations without compromising the performance of your web application.
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NodeJS Instrumentation - Adding Custom Tags to Spans | Datadog Tips & Tricks

Aug 21, 2020 By Datadog In Datadog
In part 1 of this 4 part series, you’ll learn how to use manual instrumentation to add additional detail to traces. We’ll add new tags, or attributes, to the spans generated by our NodeJS application, allowing for more insightful data visualizations in App Analytics.
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NodeJS Instrumentation - Creating Custom Spans for Method-Level Visibility | Datadog Tips & Tricks

Aug 21, 2020 By Datadog In Datadog
In part 2 of this 4 part series, you’ll learn how to instrument your NodeJS application to capture custom method-level spans, allowing visibility into how specific methods behave in your application. Flame graphs allow for deep insight into the performance of your code. During instrumentation, we can capture custom spans for deeper layers of visibility in the resulting flame graphs. In this video, we use instrumentation to capture a method-level span, allowing us to see the performance of that specific method in our flame graphs in the Datadog UI.
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NodeJS Instrumentation - Adding Analyzed Spans for Improved Data Analytics | Datadog Tips & Tricks

Aug 21, 2020 By Datadog In Datadog
In part 4 of this 4 part series, you’ll learn how to add Analyzed Spans to your traces to open up even more data search and aggregation capabilities via App Analytics. In this video, we will walk you through how you can turn any span into an Analyzed Span. Analyzed Spans function like the root spans of a trace, allowing us to turn the tags embedded in them into facets for advanced data aggregation and searching in App Analytics. You can check out how to add tags to spans—and how to utilize them in App Analytics—in our first video of the series here.
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jaegertracing

Jaeger Turns Five: A Tribute to Project Contributors

Aug 18, 2020 By Yuri Shkuro In JaegerTracing

August 3rd, 2015 was the date of the first commit in the internal Jaeger repository at Uber. Technically, the true birthday of the project was probably a week or so earlier, because while I was prototyping the collector service we went through a number of project names, some of them rather embarrassing to name here, and the real first commits happened in a differently named repository.

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