Tracing sampling is a crucial technique for managing the volume of trace data in production environments.
By default, Traceloop traces every request, which works well for debugging or development but can become expensive and noisy in high-traffic production systems.Sampling helps in several ways: it reduces noise in traces, helping you focus on important traces while maintaining visibility into your system.
It also helps with cost management in terms of storage, processing, and network bandwidth, making it essential for production deployments.
Pros: Simple to configure, predictable sampling rate, deterministic behaviorCons: May create partial traces if child spans are sampled differently, especially when spans are spread across multiple microservices or services with different sampling configurations.
Pros: Maintains trace integrity, prevents partial traces, ensures complete trace visibility when sampledCons: Slightly more complex configuration, but worth the additional setup for production environments
If you see partial traces (missing spans in the middle of a trace), ensure you’re using ParentBased sampler:
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# ❌ May create partial traces across servicessampler = TraceIdRatioBased(0.1)# ✅ Maintains trace integrity across all servicessampler = ParentBased(TraceIdRatioBased(0.1))
If you’re still collecting too much data or experiencing high costs, reduce the sampling rate:
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# Reduce from 10% to 5% for high-traffic environmentssampler = ParentBased(TraceIdRatioBased(0.05))# For very high traffic, consider 1% samplingsampler = ParentBased(TraceIdRatioBased(0.01))
If you need more visibility for debugging or monitoring, increase the sampling rate:
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# Increase from 10% to 25% for better visibilitysampler = ParentBased(TraceIdRatioBased(0.25))# For critical debugging, consider 50% or highersampler = ParentBased(TraceIdRatioBased(0.5))