You have been tasked with creating a dashboard in your organization’s Observability platform.

Within the Designing and Implementing Enterprise Network Assurance (300-445 ENNA) framework, the transition from " polling " to " streaming " is a major architectural shift. To populate real-time dashboards in external observability platforms like Grafana , Splunk , or AppDynamics , the architect should utilize the OpenTelemetry (OTel) integration (Option B).

ThousandEyes for OpenTelemetry is a push-based API built on the standardized OpenTelemetry Protocol (OTLP) . Unlike traditional REST API polling (Option A), which retrieves data at fixed intervals and can be subject to rate limiting and latency, the OTel integration allows ThousandEyes to stream granular network metrics as they are collected. These metrics—including latency, loss, jitter, and HTTP response times—are exported in a standardized format that is natively understood by modern observability backends. This allows the platform to populate complex visualizations such as time-series graphs, heatmaps, and multi-metric tables in near real-time, providing a " single pane of glass " view that correlates network performance with application and infrastructure telemetry.

A key advantage of the OTel approach is data portability and correlation . By applying metadata tags to ThousandEyes tests, the data can be filtered and categorized within the external dashboard to match the organization ' s business logic (e.g., grouping by region or application tier). This enables SREs and NetOps teams to quickly identify if a performance dip in an application dashboard correlates with a spike in internet latency measured by ThousandEyes. Options C and D do not provide the streaming data pipeline required for real-time external dashboard population. Thus, OpenTelemetry is the definitive choice for high-fidelity, real-time observability integration.