Episode

How SRE Teams Use Observability Pipelines to Reduce Data Costs

Podcast
The Site Reliability Podcast with Fexingo: SRE, Uptime, and Production Engineering
Published
Jul 8, 2026
Duration seconds
668
Processing state
not_requested
Canonical source
https://audio.fexingo.com/business/the-site-reliability-podcast/episode-0098.mp3
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https://audio.fexingo.com/business/the-site-reliability-podcast/episode-0098.mp3
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Markdown
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Summary

Episode 98 of The Site Reliability Podcast with Fexingo dives into observability pipelines — the middleware that sits between your systems and your monitoring tools. Lucas and Luna explore how teams at companies like DoorDash and Slack have used pipelines to filter, sample, and shape telemetry data before it reaches their observability backends, slashing costs by up to 70 percent without losing signal. They break down the concept of 'intelligent sampling' versus naive tail-based sampling, discuss the trade-offs of using open-source tools like OpenTelemetry Collector versus managed services like Cribl or Vector, and walk through a concrete example: how a mid-stage SaaS company reduced its Datadog bill from $240,000 to $72,000 per year. The episode also covers the pitfalls — like accidentally dropping critical traces during partial outages — and how to design pipeline rules that preserve high-cardinality dimensions for debugging. If you're an SRE or platform engineer feeling the sting of observability vendor pricing, this one's for you. #ObservabilityPipelines #SRE #SiteReliabilityEngineering #DataCostOptimization #OpenTelemetry #Cribl #Vector #Datadog #DoorDash #Slack #TelemetrySampling #IntelligentSampling #ObservabilityCosts #Monitoring #Technology #FexingoBusiness #BusinessPodcast #ProdEng Keep every episode free: buymeacoffee.com/fexingo