◉ DISTRIBUTED TRACING

LLM API Gateway Tracing

Implement comprehensive distributed tracing for LLM API Gateways. Visualize request flows, analyze latency, and optimize performance across your entire API infrastructure.

Why Tracing Matters

Distributed tracing provides end-to-end visibility into requests flowing through your LLM API Gateway. Unlike traditional logging, tracing captures the causal relationship between services.

Sample Trace Timeline

Authentication
45ms
Routing
30ms
Transform
60ms
LLM Processing
1350ms
Response
30ms

Implementation

tracing_setup.py
# OpenTelemetry Tracing Setup from opentelemetry import trace from opentelemetry.sdk.trace import TracerProvider from opentelemetry.sdk.trace.export import BatchSpanProcessor from opentelemetry.exporter.jaeger import JaegerExporter # Initialize tracer provider = TracerProvider() processor = BatchSpanProcessor(JaegerExporter()) provider.add_span_processor(processor) trace.set_tracer_provider(provider) tracer = trace.get_tracer("llm-gateway") @tracer.start_as_current_span("process_request") def process_request(request): # Your request processing logic pass
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Request Flow

Track every request from client to LLM provider and back.

Latency Analysis

Identify bottlenecks in your request pipeline.

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Performance

Monitor and optimize gateway performance metrics.

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Correlation

Correlate traces with logs and metrics.

◈ Related Topics