feat: Report histogram metrics to Triton metrics server

README.md

@@ -203,7 +203,7 @@ you need to specify a different `shm-region-prefix-name` for each server. See
 for more information.
 
 ## Triton Metrics
-Starting with the 24.08 release of Triton, users can now obtain partial
+Starting with the 24.08 release of Triton, users can now obtain specific
 vLLM metrics by querying the Triton metrics endpoint (see complete vLLM metrics
 [here](https://docs.vllm.ai/en/latest/serving/metrics.html)). This can be
 accomplished by launching a Triton server in any of the ways described above
@@ -213,16 +213,42 @@ the following:
 ```bash
 curl localhost:8002/metrics
 ```
-VLLM stats are reported by the metrics endpoint in fields that
-are prefixed with `vllm:`. Your output for these fields should look
-similar to the following:
+VLLM stats are reported by the metrics endpoint in fields that are prefixed with
+`vllm:`. Triton currently supports reporting of the following metrics from vLLM.
+```bash
+# Number of prefill tokens processed.
+counter_prompt_tokens
+# Number of generation tokens processed.
+counter_generation_tokens
+# Histogram of time to first token in seconds.
+histogram_time_to_first_token
+# Histogram of time per output token in seconds.
+histogram_time_per_output_token
+```
+Your output for these fields should look similar to the following:
 ```bash
 # HELP vllm:prompt_tokens_total Number of prefill tokens processed.
 # TYPE vllm:prompt_tokens_total counter
 vllm:prompt_tokens_total{model="vllm_model",version="1"} 10
 # HELP vllm:generation_tokens_total Number of generation tokens processed.
 # TYPE vllm:generation_tokens_total counter
 vllm:generation_tokens_total{model="vllm_model",version="1"} 16
+# HELP vllm:time_to_first_token_seconds Histogram of time to first token in seconds.
+# TYPE vllm:time_to_first_token_seconds histogram
+vllm:time_to_first_token_seconds_count{model="vllm_model",version="1"} 1
+vllm:time_to_first_token_seconds_sum{model="vllm_model",version="1"} 0.03233122825622559
+vllm:time_to_first_token_seconds_bucket{model="vllm_model",version="1",le="0.001"} 0
+vllm:time_to_first_token_seconds_bucket{model="vllm_model",version="1",le="0.005"} 0
+...
+vllm:time_to_first_token_seconds_bucket{model="vllm_model",version="1",le="+Inf"} 1
+# HELP vllm:time_per_output_token_seconds Histogram of time per output token in seconds.
+# TYPE vllm:time_per_output_token_seconds histogram
+vllm:time_per_output_token_seconds_count{model="vllm_model",version="1"} 15
+vllm:time_per_output_token_seconds_sum{model="vllm_model",version="1"} 0.04501533508300781
+vllm:time_per_output_token_seconds_bucket{model="vllm_model",version="1",le="0.01"} 14
+vllm:time_per_output_token_seconds_bucket{model="vllm_model",version="1",le="0.025"} 15
+...
+vllm:time_per_output_token_seconds_bucket{model="vllm_model",version="1",le="+Inf"} 15
 ```
 To enable vLLM engine colleting metrics, "disable_log_stats" option need to be either false
 or left empty (false by default) in [model.json](https://github.com/triton-inference-server/vllm_backend/blob/main/samples/model_repository/vllm_model/1/model.json).

ci/L0_backend_vllm/metrics_test/vllm_metrics_test.py

@@ -125,6 +125,15 @@
         # vllm:generation_tokens_total
         self.assertEqual(metrics_dict["vllm:generation_tokens_total"], 48)
 
+        # vllm:time_to_first_token_seconds
+        self.assertEqual(metrics_dict["vllm:time_to_first_token_seconds_count"], 3)
+        self.assertTrue(metrics_dict["vllm:time_to_first_token_seconds_sum"] > 0)
+        self.assertEqual(metrics_dict["vllm:time_to_first_token_seconds_bucket"], 3)
+        # vllm:time_per_output_token_seconds
+        self.assertEqual(metrics_dict["vllm:time_per_output_token_seconds_count"], 45)
+        self.assertTrue(metrics_dict["vllm:time_per_output_token_seconds_sum"] > 0)
+        self.assertEqual(metrics_dict["vllm:time_per_output_token_seconds_bucket"], 45)
+
     def test_vllm_metrics_disabled(self):
         # Test vLLM metrics
         self.vllm_infer(

src/utils/metrics.py

@@ -24,7 +24,7 @@
 # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-from typing import Dict, Union
+from typing import Dict, List, Union
 
 import triton_python_backend_utils as pb_utils
 from vllm.engine.metrics import StatLoggerBase as VllmStatLoggerBase
@@ -46,6 +46,16 @@ def __init__(self, labels):
             description="Number of generation tokens processed.",
             kind=pb_utils.MetricFamily.COUNTER,
         )
+        self.histogram_time_to_first_token_family = pb_utils.MetricFamily(
+            name="vllm:time_to_first_token_seconds",
+            description="Histogram of time to first token in seconds.",
+            kind=pb_utils.MetricFamily.HISTOGRAM,
+        )
+        self.histogram_time_per_output_token_family = pb_utils.MetricFamily(
+            name="vllm:time_per_output_token_seconds",
+            description="Histogram of time per output token in seconds.",
+            kind=pb_utils.MetricFamily.HISTOGRAM,
+        )
 
         # Initialize metrics
         # Iteration stats
@@ -55,6 +65,51 @@ def __init__(self, labels):
         self.counter_generation_tokens = self.counter_generation_tokens_family.Metric(
             labels=labels
         )
+        # Use the same bucket boundaries from vLLM sample metrics.
+        # https://github.com/vllm-project/vllm/blob/21313e09e3f9448817016290da20d0db1adf3664/vllm/engine/metrics.py#L81-L96
+        self.histogram_time_to_first_token = (
+            self.histogram_time_to_first_token_family.Metric(
+                labels=labels,
+                buckets=[
+                    0.001,
+                    0.005,
+                    0.01,
+                    0.02,
+                    0.04,
+                    0.06,
+                    0.08,
+                    0.1,
+                    0.25,
+                    0.5,
+                    0.75,
+                    1.0,
+                    2.5,
+                    5.0,
+                    7.5,
+                    10.0,
+                ],
+            )
+        )
+        self.histogram_time_per_output_token = (
+            self.histogram_time_per_output_token_family.Metric(
+                labels=labels,
+                buckets=[
+                    0.01,
+                    0.025,
+                    0.05,
+                    0.075,
+                    0.1,
+                    0.15,
+                    0.2,
+                    0.3,
+                    0.4,
+                    0.5,
+                    0.75,
+                    1.0,
+                    2.5,
+                ],
+            )
+        )
 
 
 class VllmStatLogger(VllmStatLoggerBase):
@@ -82,6 +137,19 @@ def _log_counter(self, counter, data: Union[int, float]) -> None:
         if data != 0:
             counter.increment(data)
 
+    def _log_histogram(self, histogram, data: Union[List[int], List[float]]) -> None:
+        """Convenience function for logging list to histogram.
+
+        Args:
+            histogram: A histogram metric instance.
+            data: A list of int or float data to observe into the histogram metric.
+
+        Returns:
+            None
+        """
+        for datum in data:
+            histogram.observe(datum)
+
     def log(self, stats: VllmStats) -> None:
         """Report stats to Triton metrics server.
 
@@ -97,3 +165,10 @@ def log(self, stats: VllmStats) -> None:
         self._log_counter(
             self.metrics.counter_generation_tokens, stats.num_generation_tokens_iter
         )
+        self._log_histogram(
+            self.metrics.histogram_time_to_first_token, stats.time_to_first_tokens_iter
+        )
+        self._log_histogram(
+            self.metrics.histogram_time_per_output_token,
+            stats.time_per_output_tokens_iter,
+        )