class ReportHead(dashboard_utils.DashboardHeadModule):
def __init__(self, dashboard_head):
super().__init__(dashboard_head)
self._stubs = {}
self._ray_config = None
DataSource.agents.signal.append(self._update_stubs)
# TODO(fyrestone): Avoid using ray.state in dashboard, it's not
# asynchronous and will lead to low performance. ray disconnect()
# will be hang when the ray.state is connected and the GCS is exit.
# Please refer to: https://github.com/ray-project/ray/issues/16328
assert dashboard_head.gcs_address or dashboard_head.redis_address
gcs_address = dashboard_head.gcs_address
temp_dir = dashboard_head.temp_dir
self.service_discovery = PrometheusServiceDiscoveryWriter(
gcs_address, temp_dir)
async def _update_stubs(self, change):
if change.old:
node_id, port = change.old
ip = DataSource.node_id_to_ip[node_id]
self._stubs.pop(ip)
if change.new:
node_id, ports = change.new
ip = DataSource.node_id_to_ip[node_id]
options = GLOBAL_GRPC_OPTIONS
channel = ray._private.utils.init_grpc_channel(f"{ip}:{ports[1]}",
options=options,
asynchronous=True)
stub = reporter_pb2_grpc.ReporterServiceStub(channel)
self._stubs[ip] = stub
@routes.get("/api/launch_profiling")
async def launch_profiling(self, req) -> aiohttp.web.Response:
ip = req.query["ip"]
pid = int(req.query["pid"])
duration = int(req.query["duration"])
reporter_stub = self._stubs[ip]
reply = await reporter_stub.GetProfilingStats(
reporter_pb2.GetProfilingStatsRequest(pid=pid, duration=duration))
profiling_info = (json.loads(reply.profiling_stats)
if reply.profiling_stats else reply.std_out)
return dashboard_optional_utils.rest_response(
success=True,
message="Profiling success.",
profiling_info=profiling_info)
@routes.get("/api/ray_config")
async def get_ray_config(self, req) -> aiohttp.web.Response:
if self._ray_config is None:
try:
config_path = os.path.expanduser("~/ray_bootstrap_config.yaml")
with open(config_path) as f:
cfg = yaml.safe_load(f)
except yaml.YAMLError:
return dashboard_optional_utils.rest_response(
success=False,
message=f"No config found at {config_path}.",
)
except FileNotFoundError:
return dashboard_optional_utils.rest_response(
success=False,
message="Invalid config, could not load YAML.")
payload = {
"min_workers": cfg.get("min_workers", "unspecified"),
"max_workers": cfg.get("max_workers", "unspecified"),
}
try:
payload["head_type"] = cfg["head_node"]["InstanceType"]
except KeyError:
payload["head_type"] = "unknown"
try:
payload["worker_type"] = cfg["worker_nodes"]["InstanceType"]
except KeyError:
payload["worker_type"] = "unknown"
self._ray_config = payload
return dashboard_optional_utils.rest_response(
success=True,
message="Fetched ray config.",
**self._ray_config,
)
@routes.get("/api/cluster_status")
async def get_cluster_status(self, req):
"""Returns status information about the cluster.
Currently contains two fields:
autoscaling_status (str)-- a status message from the autoscaler.
autoscaling_error (str)-- an error message from the autoscaler if
anything has gone wrong during autoscaling.
These fields are both read from the GCS, it's expected that the
autoscaler writes them there.
"""
assert ray.experimental.internal_kv._internal_kv_initialized()
legacy_status = internal_kv._internal_kv_get(
DEBUG_AUTOSCALING_STATUS_LEGACY)
formatted_status_string = internal_kv._internal_kv_get(
DEBUG_AUTOSCALING_STATUS)
formatted_status = (json.loads(formatted_status_string.decode())
if formatted_status_string else {})
error = internal_kv._internal_kv_get(DEBUG_AUTOSCALING_ERROR)
return dashboard_optional_utils.rest_response(
success=True,
message="Got cluster status.",
autoscaling_status=legacy_status.decode()
if legacy_status else None,
autoscaling_error=error.decode() if error else None,
cluster_status=formatted_status if formatted_status else None,
)
async def run(self, server):
# Need daemon True to avoid dashboard hangs at exit.
self.service_discovery.daemon = True
self.service_discovery.start()
gcs_addr = self._dashboard_head.gcs_address
subscriber = GcsAioResourceUsageSubscriber(gcs_addr)
await subscriber.subscribe()
while True:
try:
# The key is b'RAY_REPORTER:{node id hex}',
# e.g. b'RAY_REPORTER:2b4fbd...'
key, data = await subscriber.poll()
if key is None:
continue
data = json.loads(data)
node_id = key.split(":")[-1]
DataSource.node_physical_stats[node_id] = data
except Exception:
logger.exception(
"Error receiving node physical stats from reporter agent.")
@staticmethod
def is_minimal_module():
return False
dashboard = Dashboard(
args.host,
args.port,
args.port_retries,
args.redis_address,
redis_password=args.redis_password,
log_dir=args.log_dir)
# TODO(fyrestone): Avoid using ray.state in dashboard, it's not
# asynchronous and will lead to low performance. ray disconnect()
# will be hang when the ray.state is connected and the GCS is exit.
# Please refer to: https://github.com/ray-project/ray/issues/16328
service_discovery = PrometheusServiceDiscoveryWriter(
args.redis_address, args.redis_password, args.temp_dir)
# Need daemon True to avoid dashboard hangs at exit.
service_discovery.daemon = True
service_discovery.start()
loop = asyncio.get_event_loop()
loop.run_until_complete(dashboard.run())
except Exception as e:
traceback_str = ray._private.utils.format_error_message(
traceback.format_exc())
message = f"The dashboard on node {platform.uname()[1]} " \
f"failed with the following " \
f"error:\n{traceback_str}"
if isinstance(e, FrontendNotFoundError):
logger.warning(message)
else:
logger.error(message)
raise e
# Something went wrong, so push an error to all drivers.