KCNA Cloud Native Observability Practice Question
Which TWO of the following tools are commonly used for distributed tracing in cloud-native environments? (Select two.)
⚠ Common exam trap
The trap is selecting Grafana or Prometheus because they appear in observability stacks — but tracing requires a dedicated tracing backend, and Grafana is only a frontend that can query one.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Zipkin
Zipkin (A) is correct because it is a dedicated distributed tracing system that collects and visualizes latency data across microservice call chains using trace and span IDs propagated via headers such as B3. Jaeger (C) is also correct because it is a CNCF-graduated distributed tracing platform that instruments requests across services, supports OpenTracing/OpenTelemetry, and provides trace storage and a UI for span analysis. Grafana (B) is primarily a visualization and dashboarding layer that can query tracing backends but is not itself a tracing system. Fluentd (D) is a log collection and forwarding agent, and Prometheus (E) is a metrics monitoring and time-series database, neither of which performs distributed request tracing.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Zipkin
Why this is correct
Zipkin satisfies the distributed tracing requirement by collecting and correlating span data across microservices, using trace and span IDs propagated through request headers to reconstruct end-to-end request flows. Its lightweight, vendor-neutral design suits cloud-native architectures, where it commonly pairs with instrumentation libraries to visualise latency across service boundaries.
- ✗
Grafana
Why it's wrong here
Grafana visualises metrics and logs from sources such as Prometheus and Loki; it does not instrument or propagate trace context across services. It is tempting because Grafana Tempo provides tracing, but the base Grafana product is a dashboarding layer, correct when the requirement is visualisation rather than distributed tracing.
- ✓
Jaeger
Why this is correct
Jaeger provides distributed tracing by propagating trace context across microservice boundaries, letting you visualise request flows and pinpoint latency in cloud-native systems. It satisfies the stem's requirement for a tracing tool, instrumenting services via OpenTelemetry to capture spans and dependencies across distributed components.
- ✗
Fluentd
Why it's wrong here
Fluentd is a log collection and forwarding agent; it ships and aggregates log events but does not generate or propagate trace spans. It is tempting because it is a standard cloud-native observability component, and it is correct when the requirement is centralised log aggregation rather than distributed tracing.
- ✗
Prometheus
Why it's wrong here
Prometheus is a metrics collection and time-series database; it scrapes counters and gauges but does not propagate trace or span context between services. It is tempting because it is ubiquitous in cloud-native observability, and it is the right choice when the requirement is metrics monitoring and alerting rather than distributed tracing.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CNCF exam blueprint
This KCNA practice question is part of Courseiva's free CNCF certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the KCNA exam.