Inference Observability
High-resolution, inference-native profiling, tracing, and metrics across models, engines, and GPUs.
NVIDIA
PyTorch
Hugging Face
vLLM
SGLang
PyTorch Hugging Face vLLM SGLang Inference profiling
Continuous, high-resolution profiling timelines exposing operation durations and resource utilization across inference workloads.
LLM tracing
LLM generation tracing with per-step timing, token throughput, and latency breakdowns for major inference frameworks.
System metrics
System-level metrics for inference engines and hardware (CPU, GPU, accelerators).
Error monitoring
Error monitoring for device-level failures, runtime exceptions, and inference errors.
AI optimization
Inference telemetry for AI agents to identify bottlenecks and drive targeted improvements across the inference stack.