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Capturing and correlating spans to follow requests across services for end-to-end diagnostics and performance analysis.
DESCRIPTION
Distributed tracing provides a timeline of a request as it propagates through microservices, queues, and databases. Each segment, or span, records timing, metadata, and causal relationships. Traces help pinpoint bottlenecks, errors, and retries, accelerating root cause analysis. Standards like W3C Trace Context and OpenTelemetry promote interoperability across libraries and vendors. Tracing complements metrics and logs for comprehensive observability.
ALTERNATIVE DEFINITIONS
Wikipedia
Distributed tracing is a method used to profile and monitor applications, especially those built using a microservices architecture.
Highlights microservices as a primary use case for tracing.
OpenTelemetry
Tracing is a way to observe requests as they propagate through distributed systems.
Concise signal-centric definition aligned with open standards and instrumentation.
RELATED TERMS
Observability Measure OpenTelemetry Trace Context Span Jaeger Zipkin Root Cause Analysis Service Mesh
COMPETING TERMS
RELATIONS
- Narrower: AWS X-Ray Distributed Tracing
KNOWLEDGE AREAS
Observability & Telemetry Software Engineering MLOps
TARGET AUDIENCE
DevOps Engineer Software Developer MLOps Engineer Cloud Architect Data Engineer
EXTERNAL SOURCES
- Wikipedia - Distributed tracing
- OpenTelemetry - Tracing concepts and data model
- Jaeger - End-to-end tracing system documentation
TOP QUESTIONS
How does Tracing work in microservices?
It propagates a trace context across services, recording spans for each operation. The collected spans reconstruct the request’s path and latency profile.
Category: Overview
What problems does Tracing solve?
It accelerates root cause analysis, identifies bottlenecks, and exposes hidden retries or timeouts in distributed systems.
Category: Relevancy
How is Tracing different from Logging?
Logs are event records; tracing links events into a causal timeline across services, revealing end-to-end latency and dependencies.
Category: Misunderstanding
What standards support Tracing?
OpenTelemetry defines spans and context propagation; W3C Trace Context standardizes headers between services.
Category: Requirements
Which tools implement Tracing?
Jaeger, Zipkin, OpenTelemetry collectors, and vendor platforms like Datadog and New Relic.
Category: Overview
What are common Tracing mistakes?
Sampling too aggressively, missing critical spans, and failing to propagate context across async boundaries.
Category: Mistakes
How to start with Tracing?
Instrument critical services with OpenTelemetry, enable W3C headers, and visualize traces in Jaeger or vendor tooling.
Category: HowTo
How does Tracing help with SLOs?
It exposes tail latency contributors, enabling targeted improvements to meet user-centric SLOs.
Category: Example
Is Tracing useful for ML inference services?
Yes, it captures model serving latency, feature store calls, and downstream dependency performance.
Category: Relevancy