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ray-project--ray/python/ray/dashboard/modules/usage_stats/usage_stats_head.py
T
2026-07-13 13:17:40 +08:00

218 lines
7.8 KiB
Python

import asyncio
import logging
import os
import random
from concurrent.futures import ThreadPoolExecutor
import requests
import ray
import ray._common.usage.usage_lib as ray_usage_lib
import ray.dashboard.utils as dashboard_utils
from ray._common.network_utils import build_address
from ray._common.utils import get_or_create_event_loop
from ray.dashboard.utils import async_loop_forever
logger = logging.getLogger(__name__)
class UsageStatsHead(dashboard_utils.DashboardHeadModule):
def __init__(self, config: dashboard_utils.DashboardHeadModuleConfig):
super().__init__(config)
self.usage_stats_enabled = ray_usage_lib.usage_stats_enabled()
self.usage_stats_prompt_enabled = ray_usage_lib.usage_stats_prompt_enabled()
self.cluster_config_to_report = None
self.client = ray_usage_lib.UsageReportClient()
# The total number of report succeeded.
self.total_success = 0
# The total number of report failed.
self.total_failed = 0
# The seq number of report. It increments whenever a new report is sent.
self.seq_no = 0
self._dashboard_url_base = (
f"http://{build_address(self.http_host, self.http_port)}"
)
# We want to record stats for anyone who has run ray with grafana or
# prometheus at any point in time during a ray session.
self._grafana_ran_before = False
self._prometheus_ran_before = False
if ray._private.utils.get_dashboard_dependency_error() is None:
import aiohttp
import ray.dashboard.optional_utils
routes = ray.dashboard.optional_utils.DashboardHeadRouteTable
@routes.get("/usage_stats_enabled")
async def get_usage_stats_enabled(self, req) -> aiohttp.web.Response:
return ray.dashboard.optional_utils.rest_response(
status_code=dashboard_utils.HTTPStatusCode.OK,
message="Fetched usage stats enabled",
usage_stats_enabled=self.usage_stats_enabled,
usage_stats_prompt_enabled=self.usage_stats_prompt_enabled,
)
@routes.get("/cluster_id")
async def get_cluster_id(self, req) -> aiohttp.web.Response:
return ray.dashboard.optional_utils.rest_response(
status_code=dashboard_utils.HTTPStatusCode.OK,
message="Fetched cluster id",
cluster_id=self.gcs_client.cluster_id.hex(),
)
def _check_grafana_running(self):
from ray._common.usage.usage_lib import TagKey, record_extra_usage_tag
if self._grafana_ran_before:
return
grafana_running = False
try:
resp = requests.get(f"{self._dashboard_url_base}/api/grafana_health")
if resp.status_code == 200:
json = resp.json()
grafana_running = (
json["result"] is True and json["data"]["grafanaHost"] != "DISABLED"
)
except Exception:
pass
record_extra_usage_tag(
TagKey.DASHBOARD_METRICS_GRAFANA_ENABLED,
str(grafana_running),
)
if grafana_running:
# Don't need to update the tag ever again
self._grafana_ran_before = True
def _check_prometheus_running(self):
from ray._common.usage.usage_lib import TagKey, record_extra_usage_tag
if self._prometheus_ran_before:
return
prometheus_running = False
try:
resp = requests.get(f"{self._dashboard_url_base}/api/prometheus_health")
if resp.status_code == 200:
json = resp.json()
prometheus_running = json["result"] is True
except Exception:
pass
record_extra_usage_tag(
TagKey.DASHBOARD_METRICS_PROMETHEUS_ENABLED,
str(prometheus_running),
)
if prometheus_running:
# Don't need to update the tag ever again
self._prometheus_ran_before = True
def _fetch_and_record_extra_usage_stats_data(self):
logger.debug("Recording dashboard metrics extra telemetry data...")
self._check_grafana_running()
self._check_prometheus_running()
def _report_usage_sync(self):
"""
- Always write usage_stats.json regardless of report success/failure.
- If report fails, the error message should be written to usage_stats.json
- If file write fails, the error will just stay at dashboard.log.
usage_stats.json won't be written.
"""
if not self.usage_stats_enabled:
return
try:
self._fetch_and_record_extra_usage_stats_data()
data = ray_usage_lib.generate_report_data(
self.cluster_config_to_report,
self.total_success,
self.total_failed,
self.seq_no,
self.gcs_address,
self.gcs_client.cluster_id.hex(),
)
error = None
try:
self.client.report_usage_data(
ray_usage_lib._usage_stats_report_url(), data
)
except Exception as e:
logger.info(f"Usage report request failed. {e}")
error = str(e)
self.total_failed += 1
else:
self.total_success += 1
finally:
self.seq_no += 1
data = ray_usage_lib.generate_write_data(data, error)
self.client.write_usage_data(data, self.session_dir)
except Exception as e:
logger.exception(e)
logger.info(f"Usage report failed: {e}")
async def _report_usage_async(self):
if not self.usage_stats_enabled:
return
loop = get_or_create_event_loop()
with ThreadPoolExecutor(max_workers=1) as executor:
await loop.run_in_executor(executor, lambda: self._report_usage_sync())
def _report_disabled_usage_sync(self):
assert not self.usage_stats_enabled
try:
if ray_usage_lib.is_ray_init_cluster(self.gcs_client):
return
data = ray_usage_lib.generate_disabled_report_data()
self.client.report_usage_data(ray_usage_lib._usage_stats_report_url(), data)
except Exception as e:
logger.debug(f"Disabled usage report failed: {e}")
async def _report_disabled_usage_async(self):
assert not self.usage_stats_enabled
loop = get_or_create_event_loop()
with ThreadPoolExecutor(max_workers=1) as executor:
await loop.run_in_executor(
executor, lambda: self._report_disabled_usage_sync()
)
@async_loop_forever(ray_usage_lib._usage_stats_report_interval_s())
async def periodically_report_usage(self):
await self._report_usage_async()
async def run(self):
self.cluster_config_to_report = ray_usage_lib.get_cluster_config_to_report(
os.path.expanduser("~/ray_bootstrap_config.yaml")
)
if not self.usage_stats_enabled:
logger.info("Usage reporting is disabled.")
await self._report_disabled_usage_async()
return
else:
logger.info("Usage reporting is enabled.")
# Wait for 1 minutes to send the first report
# so autoscaler has the chance to set DEBUG_AUTOSCALING_STATUS.
await asyncio.sleep(min(60, ray_usage_lib._usage_stats_report_interval_s()))
await self._report_usage_async()
# Add a random offset before the second report to remove sample bias.
await asyncio.sleep(
random.randint(0, ray_usage_lib._usage_stats_report_interval_s())
)
await asyncio.gather(self.periodically_report_usage())
@staticmethod
def is_minimal_module():
return True