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How to Responsibly and Effectively Contribute to Open Source Using AI
With the influx of AI tooling, it’s never been easier to contribute to open source communities. These tools are capable of gathering context quickly, “understanding” repositories faster than ever before. They provide instant summaries about repositories that, previously, would have meant reading lines and lines of code.
Tracing Refinery
We recently released Refinery 2.9, which came with great performance improvements. Reading through the release notes, I felt the need to write a piece on this improvement, as it’s quite important but easy to overlook: collect loop taking too long. This is the story of how we used distributed tracing to find the slowdown in this loop.
The OTTL Cookbook: Common Solutions to Data Transformation Problems
As our software complexity increases, so does our telemetry—and as our telemetry increases, it needs more and more tweaking en route to its final destination. You’ve likely needed to change an attribute, parse a log body, or touch up a metric before it landed in your backend of choice.
Collecting Kubernetes Data Using OpenTelemetry
Running a Kubernetes cluster isn’t easy. With all the benefits come complexities and unknowns. In order to truly understand your Kubernetes cluster and all the resources running inside, you need access to the treasure trove of telemetry that Kubernetes provides. With the right tools, you can get access to all the events, logs, and metrics of all the nodes, pods, containers, etc. running in your cluster. So which tool should you choose? Since we are all in on OpenTelemetry, we think the best solution is the OpenTelemetry Collector.