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Configure Jaeger 1.x adaptive sampling to hold a steady traces-per-second target across hot and cold services, with verification steps, fallback behavior, and rollback.
Learn how to use Jaeger Remote Sampling to dynamically adjust trace rates across services without redeploying code, including configuration examples and verification steps.
When some requests produce traces and others don’t, or downstream spans disappear, follow these ordered checks to pinpoint tracer‑Agent connectivity, sampling, retention filters, or propagation issues.
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.
Sentry traces only help if the header chain survives every hop. A two-service walkthrough, the sampling trade-off, and how to verify propagation.
A step‑by‑step guide to add Datadog APM tracing to a Java microservice: install the Agent, drop the dd‑java‑agent jar, set environment variables, verify logs, and confirm traces in the UI.
High‑traffic services can flood Jaeger with spans. Remote sampling lets you set global, per‑service, and per‑operation rates centrally—without redeploying. Learn how to configure, verify, and trade‑off head‑based sampling versus tail‑based guarantees.
jaegertracing
datadog
dynatrace
java
opentelemetry