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Learn how Jaeger adaptive sampling dynamically adjusts trace collection to cut storage usage while preserving visibility into latency‑critical and bursty traffic.
Choose between Elasticsearch, Cassandra, and in-memory storage for Jaeger based on span volume, retention, and operational capacity.
Missing trace links across microservices frustrate observability. This post shows how to enable OpenTelemetry’s built‑in W3C TraceContext propagator in Java, Go, and Python, walk through a minimal request chain, evaluate overhead, and give a migration checklist.
Attach the OpenTelemetry Java agent at JVM startup to get traces with zero code changes — here's the exact configuration, how to verify spans arrive, and the silent-failure mistakes to avoid.
Decide between the OpenTelemetry Java agent and SDK, set correct context propagation, and avoid API pitfalls. Follow this guide to configure, verify, and recover from common issues in JVM tracing.
Learn how to configure Jaeger’s sampling policies—Probabilistic, Rate‑Limiting, and more—to keep trace volume under control while still capturing critical performance data in a production microservices environment.
Learn how to move Jaeger trace storage from in‑memory to Cassandra or Elasticsearch by updating only the collector configuration, keeping your instrumented services unchanged.
Configure Jaeger’s adaptive sampling to keep trace ingestion near a target rate. Step‑by‑step instructions, verification, and rollback options.
Learn how the OpenTelemetry Java agent adds automatic tracing to Java apps without code changes, covering setup, a Spring Boot example, and practical limits.
jaegertracing
opentelemetry
java
cassandra