How Jidu Scaled Smart Car Tracing with OpenObserve

Jidu, the technology company behind Jiyue's autonomous driving systems, faced significant challenges with their Elasticsearch-based observability stack, which struggled to handle the exponential growth in telemetry data from their vehicles. The system's limitations included incomplete observability due to trace sampling, performance bottlenecks despite substantial resource allocation, and high operational costs for storing sampled data. These issues impacted the stability and reliability of their systems, prompting Jidu to transition to OpenObserve, an open-source observability platform. OpenObserve provided full-fidelity tracing, efficient resource usage, and significant cost savings through data compression, transforming Jidu's operations by addressing the previous challenges and enhancing the efficiency, reliability, and scalability of their systems. The transition enabled engineers to perform real-time analysis without timeouts, streamlined debugging workflows, and improved metric correlation, ultimately leading to improved application stability and customer satisfaction. This transformation offers valuable insights for other companies dealing with high-throughput telemetry data, demonstrating that modern platforms can offer comprehensive observability without prohibitive costs.

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