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Sep 3, 2026 31 min

How to find failures without drowning in tracing data

from The New Stack Podcast Hosted by Chronosphere, Sarah Hudspeth, Alex Wilhelm, The New Stack

Traces provide a detailed view of a request’s journey through data, microservices and applications, helping SREs pinpoint where failures occur and resolve issues faster. But while tracing can reduce downtime and developer burnout, collecting every trace creates its own problems. Storing massive volumes of data is expensive, can burden the systems being monitored and makes it harder to find the information that actually matters. The solution isn’t abandoning tracing, but being smarter about what gets retained. Head sampling captures only a portion of traces upfront, while tail sampling evaluates completed traces and keeps those most valuable for troubleshooting. Dynamic sampling goes further by filtering repetitive or nearly identical traces before they overwhelm storage. On The New Stack podcast, Sarah Hudspeth of Chronosphere, a Palo Alto Networks company, explains how teams can build a more effective tracing strategy. She breaks down how thoughtful sampling and observability design can turn tracing from a data-hoarding problem into a practical tool for production troubleshooting. Learn more from The New Stack around the latest in tracing: Sampling: the philosopher’s stone of distributed tracing How OpenTelemetry Works: Tracing, Metrics and Logs on Kubernetes Why Synthetic Tracing Delivers Better Data, Not Just More Data Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

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Traces provide a detailed view of a request’s journey through data, microservices and applications, helping SREs pinpoint where failures occur and resolve issues faster. But while tracing can reduce downtime and developer burnout, collecting every trace creates its own problems. Storing massive volumes of data is expensive, can burden the systems being monitored and makes it harder to find the information that actually matters.

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How to find failures without drowning in tracing data

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This episode was published on September 3, 2026.

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