vllm.config.observability ¶

@config
class ObservabilityConfig:
    """Configuration for observability - metrics and tracing."""

    show_hidden_metrics_for_version: str | None = None
    """Enable deprecated Prometheus metrics that have been hidden since the
    specified version. For example, if a previously deprecated metric has been
    hidden since the v0.7.0 release, you use
    `--show-hidden-metrics-for-version=0.7` as a temporary escape hatch while
    you migrate to new metrics. The metric is likely to be removed completely
    in an upcoming release."""

    @cached_property
    def show_hidden_metrics(self) -> bool:
        """Check if the hidden metrics should be shown."""
        if self.show_hidden_metrics_for_version is None:
            return False
        return version._prev_minor_version_was(self.show_hidden_metrics_for_version)

    otlp_traces_endpoint: str | None = None
    """Target URL to which OpenTelemetry traces will be sent."""

    collect_detailed_traces: list[DetailedTraceModules] | None = None
    """It makes sense to set this only if `--otlp-traces-endpoint` is set. If
    set, it will collect detailed traces for the specified modules. This
    involves use of possibly costly and or blocking operations and hence might
    have a performance impact.

    Note that collecting detailed timing information for each request can be
    expensive."""

    kv_cache_metrics: bool = False
    """Enable KV cache residency metrics (lifetime, idle time, reuse gaps).
    Uses sampling to minimize overhead.
    Requires log stats to be enabled (i.e., --disable-log-stats not set)."""

    kv_cache_metrics_sample: float = Field(default=0.01, gt=0, le=1)
    """Sampling rate for KV cache metrics (0.0, 1.0]. Default 0.01 = 1% of blocks."""

    cudagraph_metrics: bool = False
    """Enable CUDA graph metrics (number of padded/unpadded tokens, runtime cudagraph
    dispatch modes, and their observed frequencies at every logging interval)."""

    enable_layerwise_nvtx_tracing: bool = False
    """Enable layerwise NVTX tracing. This traces the execution of each layer or
    module in the model and attach information such as input/output shapes to
    nvtx range markers. Noted that this doesn't work with CUDA graphs enabled."""

    enable_mfu_metrics: bool = False
    """Enable Model FLOPs Utilization (MFU) metrics."""

    enable_mm_processor_stats: bool = False
    """Enable collection of timing statistics for multimodal processor operations.
    This is for internal use only (e.g., benchmarks) and is not exposed as a CLI
    argument."""

    enable_logging_iteration_details: bool = False
    """Enable detailed logging of iteration details.
    If set, vllm EngineCore will log iteration details
    This includes number of context/generation requests and tokens
    and the elapsed cpu time for the iteration."""

    @cached_property
    def collect_model_forward_time(self) -> bool:
        """Whether to collect model forward time for the request."""
        return self.collect_detailed_traces is not None and (
            "model" in self.collect_detailed_traces
            or "all" in self.collect_detailed_traces
        )

    @cached_property
    def collect_model_execute_time(self) -> bool:
        """Whether to collect model execute time for the request."""
        return self.collect_detailed_traces is not None and (
            "worker" in self.collect_detailed_traces
            or "all" in self.collect_detailed_traces
        )

    def compute_hash(self) -> str:
        """
        WARNING: Whenever a new field is added to this config,
        ensure that it is included in the factors list if
        it affects the computation graph.

        Provide a hash that uniquely identifies all the configs
        that affect the structure of the computation
        graph from input ids/embeddings to the final hidden states,
        excluding anything before input ids/embeddings and after
        the final hidden states.
        """
        # no factors to consider.
        # this config will not affect the computation graph.
        factors: list[Any] = []
        hash_str = safe_hash(str(factors).encode(), usedforsecurity=False).hexdigest()
        return hash_str

    @field_validator("show_hidden_metrics_for_version")
    @classmethod
    def _validate_show_hidden_metrics_for_version(cls, value: str | None) -> str | None:
        if value is not None:
            # Raises an exception if the string is not a valid version.
            parse(value)
        return value

    @field_validator("otlp_traces_endpoint")
    @classmethod
    def _validate_otlp_traces_endpoint(cls, value: str | None) -> str | None:
        if value is not None:
            from vllm.tracing import is_tracing_available, otel_import_error_traceback

            if not is_tracing_available():
                raise ValueError(
                    "OpenTelemetry is not available. Unable to configure "
                    "'otlp_traces_endpoint'. Ensure OpenTelemetry packages are "
                    f"installed. Original error:\n{otel_import_error_traceback}"
                )
        return value

    @field_validator("collect_detailed_traces")
    @classmethod
    def _validate_collect_detailed_traces(
        cls, value: list[DetailedTraceModules] | None
    ) -> list[DetailedTraceModules] | None:
        """Handle the legacy case where users might provide a comma-separated
        string instead of a list of strings."""
        if value is not None and len(value) == 1 and "," in value[0]:
            value = cast(list[DetailedTraceModules], value[0].split(","))
        return value

    @model_validator(mode="after")
    def _validate_tracing_config(self):
        if self.collect_detailed_traces and not self.otlp_traces_endpoint:
            raise ValueError(
                "collect_detailed_traces requires `--otlp-traces-endpoint` to be set."
            )
        return self