Why Tracing in OpsRamp

OpsRamp tracing turns request-level telemetry into workflows for investigation, service analysis, topology, and governance. It brings trace data into the same operational context as services, infrastructure, logs, metrics, and alerts.

Operational value

• Follow a request end to end: Inspect the services and operations involved in a transaction and identify the span where latency or failure began.
• Analyze service performance: Compare request rate, latency, error rate, and Apdex-style performance indicators by service or operation.
• Understand dependencies: Build service maps and trace topology from observed parent-child calls instead of relying only on manually maintained diagrams.
• Correlate application and infrastructure context: Use resource attributes such as Kubernetes cluster, namespace, workload, and deployment to connect application behavior with its runtime environment.
• Investigate exceptions and events: Inspect span status, attributes, and timestamped events in the context of the complete request.
• Control data volume: Apply trace-aware sampling before forwarding, monitor tenant ingestion usage, and manage retention periods.

OpsRamp trace ingestion requires the OpsRamp trace proxy. Manually instrumented applications send OTLP spans to the proxy, optionally through an OpenTelemetry Collector. The Collector can provide centralized processing and egress but does not replace the trace proxy.
The result is a shared view for developers, SREs, and operations teams: developers can inspect code-path behavior, SREs can identify dependency and latency patterns, and administrators can govern access, ingestion limits, and retention.