[Feature] Tracing: Fine-Grained Tracing for Request Latency Part1 #5255
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Motivation
FastDeploy currently lacks request-level observability mechanisms. Although performance analysis can be performed using profiling tools, they are not suitable for long-term, stable monitoring and introduce significant performance overhead. To help developers diagnose performance bottlenecks and troubleshoot issues more effectively, we have introduced a new request-level end-to-end tracing capability.
Modifications
This update introduces a new Trace utility class and provides a Docker Compose setup for launching Jaeger to visualize tracing data. To reduce the review burden, the feature will be delivered and refined across multiple incremental PRs.
Usage or Command
Accuracy Tests
Checklist
[FDConfig],[APIServer],[Engine],[Scheduler],[PD Disaggregation],[Executor],[Graph Optimization],[Speculative Decoding],[RL],[Models],[Quantization],[Loader],[OP],[KVCache],[DataProcessor],[BugFix],[Docs],[CI],[Optimization],[Feature],[Benchmark],[Others],[XPU],[HPU],[GCU],[DCU],[Iluvatar],[Metax]]pre-commitbefore commit.releasebranch, make sure the PR has been submitted to thedevelopbranch, then cherry-pick it to thereleasebranch with the[Cherry-Pick]PR tag.