[V1][Metrics] Handle preemptions

tests/entrypoints/openai/test_metrics.py

@@ -227,6 +227,7 @@ async def test_metrics_counts(server: RemoteOpenAIServer,
     "vllm:gpu_cache_usage_perc",
     "vllm:gpu_prefix_cache_queries",
     "vllm:gpu_prefix_cache_hits",
+    "vllm:num_preemptions_total",
     "vllm:prompt_tokens_total",
     "vllm:generation_tokens_total",
     "vllm:iteration_tokens_total",

vllm/v1/core/scheduler.py

@@ -164,6 +164,7 @@ def schedule(self) -> "SchedulerOutput":
                     self.kv_cache_manager.free(preempted_req)
                     preempted_req.status = RequestStatus.PREEMPTED
                     preempted_req.num_computed_tokens = 0
+                    self.request_preempted(preempted_req, scheduled_timestamp)
 
                     self.waiting.appendleft(preempted_req)
                     preempted_reqs.append(preempted_req)
@@ -281,9 +282,9 @@ def schedule(self) -> "SchedulerOutput":
                 self.waiting.popleft()
                 self.running.append(request)
                 self.scheduled_req_ids.add(request.request_id)
+                self.request_scheduled(request, scheduled_timestamp)
                 if request.status == RequestStatus.WAITING:
                     scheduled_new_reqs.append(request)
-                    self.request_scheduled(request, scheduled_timestamp)
                 elif request.status == RequestStatus.PREEMPTED:
                     scheduled_resumed_reqs.append(request)
                 else:
@@ -675,6 +676,13 @@ def request_scheduled(self, request: Request, timestamp: float):
             EngineCoreEvent.new_event(EngineCoreEventType.SCHEDULED,
                                       timestamp))
 
+    def request_preempted(self, request: Request, timestamp: float):
+        if not self.log_stats:
+            return
+        request.events.append(
+            EngineCoreEvent.new_event(EngineCoreEventType.PREEMPTED,
+                                      timestamp))
+
     def make_stats(self) -> Optional[SchedulerStats]:
         if not self.log_stats:
             return None

vllm/v1/engine/__init__.py

@@ -65,6 +65,7 @@ class EngineCoreEventType(enum.IntEnum):
     """The type of engine core request event."""
     QUEUED = 1
     SCHEDULED = 2
+    PREEMPTED = 3
 
 
 class EngineCoreEvent(msgspec.Struct):

vllm/v1/metrics/loggers.py

@@ -132,6 +132,11 @@ def __init__(self, vllm_config: VllmConfig):
             "GPU prefix cache hits, in terms of number of cached blocks.",
             labelnames=labelnames).labels(*labelvalues)
 
+        self.counter_num_preempted_reqs = prometheus_client.Counter(
+            name="vllm:num_preemptions_total",
+            documentation="Cumulative number of preemption from the engine.",
+            labelnames=labelnames).labels(*labelvalues)
+
         self.counter_prompt_tokens = prometheus_client.Counter(
             name="vllm:prompt_tokens_total",
             documentation="Number of prefill tokens processed.",
@@ -282,17 +287,27 @@ def log(self, scheduler_stats: SchedulerStats,
         self.counter_gpu_prefix_cache_hits.inc(
             scheduler_stats.prefix_cache_stats.hits)
 
+        self.counter_num_preempted_reqs.inc(iteration_stats.num_preempted_reqs)
         self.counter_prompt_tokens.inc(iteration_stats.num_prompt_tokens)
         self.counter_generation_tokens.inc(
             iteration_stats.num_generation_tokens)
         self.histogram_iteration_tokens.observe(
             iteration_stats.num_prompt_tokens + \
             iteration_stats.num_generation_tokens)
 
+        for ttft in iteration_stats.time_to_first_tokens_iter:
+            self.histogram_time_to_first_token.observe(ttft)
+        for tpot in iteration_stats.time_per_output_tokens_iter:
+            self.histogram_time_per_output_token.observe(tpot)
+
         for finished_request in iteration_stats.finished_requests:
             self.counter_request_success[finished_request.finish_reason].inc()
             self.histogram_e2e_time_request.observe(
                 finished_request.e2e_latency)
+            self.histogram_queue_time_request.observe(
+                finished_request.queued_time)
+            self.histogram_prefill_time_request.observe(
+                finished_request.prefill_time)
             self.histogram_inference_time_request.observe(
                 finished_request.inference_time)
             self.histogram_decode_time_request.observe(
@@ -302,15 +317,6 @@ def log(self, scheduler_stats: SchedulerStats,
             self.histogram_num_generation_tokens_request.observe(
                 finished_request.num_generation_tokens)
 
-        for ttft in iteration_stats.time_to_first_tokens_iter:
-            self.histogram_time_to_first_token.observe(ttft)
-        for tpot in iteration_stats.time_per_output_tokens_iter:
-            self.histogram_time_per_output_token.observe(tpot)
-        for queue_time in iteration_stats.queue_times_iter:
-            self.histogram_queue_time_request.observe(queue_time)
-        for prefill_time in iteration_stats.prefill_times_iter:
-            self.histogram_prefill_time_request.observe(prefill_time)
-
         if self.gauge_lora_info is not None:
             running_lora_adapters = \
                 ",".join(iteration_stats.running_lora_adapters.keys())

vllm/v1/metrics/stats.py

@@ -67,6 +67,8 @@ class FinishedRequestStats:
     e2e_latency: float = 0.0
     num_prompt_tokens: int = 0
     num_generation_tokens: int = 0
+    queued_time: float = 0.0
+    prefill_time: float = 0.0
     inference_time: float = 0.0
     decode_time: float = 0.0
 
@@ -78,11 +80,10 @@ def __init__(self):
         self.iteration_timestamp = time.time()
         self.num_generation_tokens = 0
         self.num_prompt_tokens = 0
+        self.num_preempted_reqs = 0
         self.finished_requests: List[FinishedRequestStats] = []
         self.time_to_first_tokens_iter: List[float] = []
         self.time_per_output_tokens_iter: List[float] = []
-        self.queue_times_iter: List[float] = []
-        self.prefill_times_iter: List[float] = []
         self.waiting_lora_adapters: Dict[str, int] = {}
         self.running_lora_adapters: Dict[str, int] = {}
 
@@ -122,9 +123,6 @@ def update_from_output(self, output: "EngineCoreOutput",
         if is_prefilling:
             # TODO: re-enable no-output-for-partial-prefills invariant as above
             if num_new_generation_tokens > 0:
-                prefill_interval = \
-                    engine_core_timestamp - req_stats.scheduled_ts
-                self.prefill_times_iter.append(prefill_interval)
                 req_stats.first_token_ts = engine_core_timestamp
         else:
             tpot = engine_core_timestamp - req_stats.last_token_ts
@@ -145,24 +143,39 @@ def update_from_events(self, req_id: str, events: List["EngineCoreEvent"],
                 if lora_stats is not None:
                     lora_stats.waiting_requests.add(req_id)
             elif event.type == EngineCoreEventType.SCHEDULED:
-                queued_interval = event.timestamp - req_stats.queued_ts
-                self.queue_times_iter.append(queued_interval)
-                req_stats.scheduled_ts = event.timestamp
+                if req_stats.scheduled_ts == 0.0:  # ignore preemptions
+                    req_stats.scheduled_ts = event.timestamp
                 LoRARequestStates.scheduled_request(lora_stats, req_id)
+            elif event.type == EngineCoreEventType.PREEMPTED:
+                self.num_preempted_reqs += 1
 
     def update_from_finished_request(self, finish_reason: "FinishReason",
                                      request_output: "RequestOutput",
                                      req_stats: RequestStateStats):
         e2e_latency = self._time_since(req_stats.arrival_time)
 
-        inference_time = req_stats.last_token_ts - req_stats.scheduled_ts
+        # Queued interval is from first QUEUED event to first SCHEDULED
+        queued_time = req_stats.scheduled_ts - req_stats.queued_ts
+
+        # Prefill interval is from first SCHEDULED to first NEW_TOKEN
+        # Any preemptions during prefill is included in the interval
+        prefill_time = req_stats.first_token_ts - req_stats.scheduled_ts
+
+        # Decode interval is from first NEW_TOKEN to last NEW_TOKEN
+        # Any preemptions during decode are included
         decode_time = req_stats.last_token_ts - req_stats.first_token_ts
 
+        # Inference interval is from first SCHEDULED to last NEW_TOKEN
+        # Any preemptions during prefill or decode are included
+        inference_time = req_stats.last_token_ts - req_stats.scheduled_ts
+
         finished_req = \
             FinishedRequestStats(finish_reason=finish_reason,
                                  e2e_latency=e2e_latency,
                                  num_prompt_tokens=len(request_output.prompt_token_ids),
                                  num_generation_tokens=req_stats.num_generation_tokens,
+                                 queued_time=queued_time,
+                                 prefill_time=prefill_time,
                                  inference_time=inference_time,
                                  decode_time=decode_time)
         self.finished_requests.append(finished_req)