As geospatial platforms transition toward cloud-native microservices, management complexity has surged across API data services, processing engines, and multi-format storage systems. Traditional monitoring is no longer sufficient for these distributed environments. To ensure high availability and rapid troubleshooting, a shift toward deep Observability is essential.
This presentation introduces an open-source Geospatial Observation Stack—specifically designed for cloud-native geospatial architectures using OpenTelemetry, Prometheus, Grafana, and Loki. We demonstrate how to achieve end-to-end tracing and correlation, enabling administrators and developers to pinpoint bottlenecks across the entire spatial data pipeline. By implementing Service-Level Objectives (SLOs) and proactive alerting policies, organizations can move from reactive fixes to predictive maintenance.
Our results show that this integrated observability approach significantly reduces Mean Time to Detect (MTTD) and Mean Time to Resolve (MTTR), ensuring robust, high-performance geospatial services in a cloud-native world.