Trace sampling can help you manage data volume, optimize performance, and maintain actionable observability without collecting every piece of telemetry data.
Observability in modern software systems is essential for maintaining system health and troubleshooting effectively, but collecting all telemetry data is rarely practical. That’s where sampling techniques in OpenTelemetry come into play.
This video explains trace sampling and explores how software engineers and developers can leverage head and tail sampling to balance system performance with insightful observability.
Discover why sampling is crucial in managing data volume, focusing on actionable insights, and optimizing performance. Learn the best practices for trace sampling and get a comprehensive breakdown of OpenTelemetry's supported techniques. Last, but not least, dive into observability best practices to keep track of sampling decisions.
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📖 Chapters 📖
00:00 Intro
00:14 Welcome
02:16 Introduction
07:42 Head Sampling
16:47 Collector Sampling
25:13 Best Practices
27:44 Observability
30:20 Conclusion
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🔗 Additional Links
GitHub tutorial
Is it observable blog
Dynatrace Trial
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