monitoring-observability

Observability across distributed systems requires integrating metrics, logs, and traces via standard OpenTelemetry instrumentation. You collect data from microservices and cloud-native architectures to enable real-time dashboards, alerting, and rapid root-cause analysis across services.

Correlating traces with logs and metrics requires proven instrumentation patterns that link telemetry data across services. By applying OpenTelemetry standards, you can trace requests through microservices and match them with corresponding log entries and metric anomalies for rapid root-cause analysis.

Setting up Prometheus metrics and Grafana dashboards involves configuring Prometheus-compatible metrics collection and building real-time visualizations. You instrument your cloud-native applications to expose metrics, then query and display them in Grafana to monitor system health and performance.

OpenTelemetry instrumentation is required to standardize tracing and structured logging across microservices. It provides the framework to collect and export telemetry data, ensuring your distributed traces and logs are correlated and compatible with tools like Jaeger and Prometheus.

This observability approach supports event-driven applications needing real-time alerting by defining clear alerting rules and runbooks. It applies to modern cloud-native architectures, enabling dashboards and incident response workflows for event-driven microservices.

Using Prometheus and Grafana without distributed tracing limits your ability to perform rapid root-cause analysis across services. While metrics and dashboards show system anomalies, traces are required to follow requests through microservices and pinpoint the exact failure point.