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remove expensive debug logs from controller #57813

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Merged
abrarsheikh merged 3 commits into from
Oct 17, 2025
Merged

remove expensive debug logs from controller #57813

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aed89b5
remove expensive debug logs from controller
abrarsheikh Oct 16, 2025
256edd5
Merge branch 'master' of github.com:ray-project/ray into SERVE-1244-a…
abrarsheikh Oct 17, 2025
aa770c2
remove spammy warning
abrarsheikh Oct 17, 2025
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28 changes: 0 additions & 28 deletions python/ray/serve/_private/autoscaling_state.py
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Original file line number Diff line number Diff line change
Expand Up @@ -932,21 +932,11 @@ def update_running_replica_ids(
app_state = self._app_autoscaling_states.get(deployment_id.app_name)
if app_state:
app_state.update_running_replica_ids(deployment_id, running_replicas)
else:
logger.warning(
f"Cannot update running replica ids for deployment "
f"{deployment_id} because the application {deployment_id.app_name} is not registered"
)

def on_replica_stopped(self, replica_id: ReplicaID):
app_state = self._app_autoscaling_states.get(replica_id.deployment_id.app_name)
if app_state:
app_state.on_replica_stopped(replica_id)
else:
logger.warning(
f"Cannot invoke callback on replica stopped for replica "
f"{replica_id} because the application {replica_id.deployment_id.app_name} is not registered"
)

def get_metrics_for_deployment(
self, deployment_id: DeploymentID
Expand All @@ -956,10 +946,6 @@ def get_metrics_for_deployment(
deployment_id.app_name
].get_replica_metrics_by_deployment_id(deployment_id)
else:
logger.warning(
f"Cannot get metrics for deployment "
f"{deployment_id} because the application {deployment_id.app_name} is not registered"
)
return {}

def get_total_num_requests_for_deployment(
Expand All @@ -970,10 +956,6 @@ def get_total_num_requests_for_deployment(
deployment_id.app_name
].get_total_num_requests_for_deployment(deployment_id)
else:
logger.warning(
f"Cannot get total number of requests for deployment "
f"{deployment_id} because the application {deployment_id.app_name} is not registered"
)
return 0

def is_within_bounds(
Expand All @@ -992,11 +974,6 @@ def record_request_metrics_for_replica(
)
if app_state:
app_state.record_request_metrics_for_replica(replica_metric_report)
else:
logger.warning(
f"Cannot record request metrics for replica "
f"{replica_metric_report.replica_id} because the application {replica_metric_report.replica_id.deployment_id.app_name} is not registered"
)

def record_request_metrics_for_handle(
self,
Expand All @@ -1008,11 +985,6 @@ def record_request_metrics_for_handle(
)
if app_state:
app_state.record_request_metrics_for_handle(handle_metric_report)
else:
logger.warning(
f"Cannot record request metrics for handle "
f"{handle_metric_report.handle_id} because the application {handle_metric_report.deployment_id.app_name} is not registered"
)

def drop_stale_handle_metrics(self, alive_serve_actor_ids: Set[str]) -> None:
for app_state in self._app_autoscaling_states.values():
Expand Down
8 changes: 0 additions & 8 deletions python/ray/serve/_private/controller.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,6 @@
from ray.serve._private.application_state import ApplicationStateManager, StatusOverview
from ray.serve._private.autoscaling_state import AutoscalingStateManager
from ray.serve._private.common import (
RUNNING_REQUESTS_KEY,
DeploymentID,
HandleMetricReport,
NodeId,
Expand Down Expand Up @@ -275,9 +274,6 @@ def get_pid(self) -> int:
def record_autoscaling_metrics_from_replica(
self, replica_metric_report: ReplicaMetricReport
):
logger.debug(
f"Received metrics from replica {replica_metric_report.replica_id}: {replica_metric_report.aggregated_metrics.get(RUNNING_REQUESTS_KEY)} running requests"
)
latency = time.time() - replica_metric_report.timestamp
latency_ms = latency * 1000
if latency_ms > RAY_SERVE_RPC_LATENCY_WARNING_THRESHOLD_MS:
Expand All @@ -294,10 +290,6 @@ def record_autoscaling_metrics_from_replica(
def record_autoscaling_metrics_from_handle(
self, handle_metric_report: HandleMetricReport
):
logger.debug(
f"Received metrics from handle {handle_metric_report.handle_id} for deployment {handle_metric_report.deployment_id}: "
f"{handle_metric_report.queued_requests} queued requests and {handle_metric_report.aggregated_metrics[RUNNING_REQUESTS_KEY]} running requests"
)
latency = time.time() - handle_metric_report.timestamp
latency_ms = latency * 1000
if latency_ms > RAY_SERVE_RPC_LATENCY_WARNING_THRESHOLD_MS:
Expand Down