In IBM Cloud Pak for Integration (CP4I), the Operations Dashboard provides visibility into API and application performance by collecting and analyzing tracing data. The Sampling Policy is a configurable setting that determines the percentage of traces that are sampled, collected, and stored for analysis.
Tracing all requests can be resource-intensive, so a sampling policy allows administrators to control how much trace data is captured, balancing observability with system performance.
Sampling can be random (e.g., capture 10% of requests) or rule-based (e.g., capture only slow or error-prone transactions).
Administrators can configure trace sampling rates based on workload needs.
A higher sampling rate captures more traces, useful for debugging but may increase storage and processing overhead.
A lower sampling rate reduces storage but might miss some performance insights.
How the Sampling Policy Works:
A. Sampling policy (Correct) ✅
The sampling policy is the correct setting that defines how traces are collected and stored in the Operations Dashboard.
B. Sampling context (Incorrect) ❌
No such configuration exists in CP4I. The term "context" is generally used for metadata about a trace, not for controlling sampling rates.
C. Tracing policy (Incorrect) ❌
While tracing policies define whether tracing is enabled, they do not directly configure trace sampling rates.
D. Trace context (Incorrect) ❌
Trace context refers to the metadata attached to traces (such as trace IDs), but it does not determine the percentage of traces sampled.
Analysis of the Options:
IBM API Connect and Operations Dashboard - Tracing Configuration
IBM Cloud Pak for Integration - Distributed Tracing Guide
OpenTelemetry and Sampling Policy for IBM Cloud Pak
IBM Cloud Pak for Integration (CP4I) v2021.2 Administration References:
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