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Use the OpenTelemetry Collector's Tail Sampling Processor to keep errors and slow traces while probabilistically sampling the rest. This guide covers a working configuration, policy ordering, memory limits, and common placement mistakes.
Jaeger clients fetch probabilistic or rate‑limiting sampling strategies from the collector through the local agent, enabling dynamic trace‑volume control without code changes or restarts.
Learn how to use Datadog custom spans to bridge visibility gaps in asynchronous workflows and enrich your traces with business-specific metadata.
Use Dynatrace request attributes to attach tenant IDs, order values, or feature flags to PurePaths for filtering — configure via HTTP headers or method capture, avoid PII pitfalls, and verify in minutes.
Learn how to turn on OpenTelemetry tracing in Ballerina 2201+ services with the built‑in observability module, configure an OTLP exporter, and verify traces in Jaeger.
Stop dashboard timeouts caused by high-cardinality PromQL queries. Learn how to implement Prometheus recording rules to pre-compute aggregations and reduce query latency.
Sentry traces only help if the header chain survives every hop. A two-service walkthrough, the sampling trade-off, and how to verify propagation.
Stop losing critical error traces to random sampling. Learn how to implement Jaeger tail-based sampling to capture 100% of failures and latency outliers while controlling storage costs.
An architecture note on isolating policy decisions from data-plane forwarding in a network policy service, with modular components, trust boundaries, health checks, and failure-mode mitigations.
opentelemetry
jaegertracing
datadog
dynatrace
ballerina
prometheus
npss