Distributed Tracing: Distributed Tracing | AI Knowledge Hub

Distributed tracing is a technique used to monitor and troubleshoot the performance of applications that span multiple services or systems. It involves tracking requests as they flow through these interconnected components, providing insights into potential bottlenecks and issues.

Distributed tracing leverages AI and tracing systems to track requests across distributed systems by collecting and correlating traces from various services. This provides a complete view of request execution, aiding in identifying performance problems.

The core components of distributed tracing include traces (representing the journey of a request), spans (representing individual operations within a trace, including timing data), and context propagation (the mechanism for passing trace IDs and span IDs between services).

The key components include traces – which represent the entire journey of a request, spans – which capture individual operations within that trace along with their timing data, and context propagation – which is how trace IDs and span IDs are passed between different services to ensure they can be correlated.