ray/dashboard/dashboard.py

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import argparse
import asyncio
import logging
import logging.handlers
import platform
import traceback
import signal
import os
import sys
import ray._private.ray_constants as ray_constants
import ray._private.services
import ray._private.utils
import ray.dashboard.consts as dashboard_consts
import ray.dashboard.head as dashboard_head
import ray.dashboard.utils as dashboard_utils
from ray._private.gcs_pubsub import GcsPublisher
from ray._private.ray_logging import setup_component_logger
from typing import Optional, Set
# Logger for this module. It should be configured at the entry point
# into the program using Ray. Ray provides a default configuration at
# entry/init points.
logger = logging.getLogger(__name__)
class Dashboard:
"""A dashboard process for monitoring Ray nodes.
This dashboard is made up of a REST API which collates data published by
Reporter processes on nodes into a json structure, and a webserver
which polls said API for display purposes.
Args:
host: Host address of dashboard aiohttp server.
port: Port number of dashboard aiohttp server.
port_retries: The retry times to select a valid port.
gcs_address: GCS address of the cluster
log_dir: Log directory of dashboard.
"""
def __init__(
self,
host: str,
port: int,
port_retries: int,
gcs_address: str,
log_dir: str = None,
temp_dir: str = None,
session_dir: str = None,
minimal: bool = False,
modules_to_load: Optional[Set[str]] = None,
):
self.dashboard_head = dashboard_head.DashboardHead(
http_host=host,
http_port=port,
http_port_retries=port_retries,
gcs_address=gcs_address,
log_dir=log_dir,
temp_dir=temp_dir,
session_dir=session_dir,
minimal=minimal,
modules_to_load=modules_to_load,
)
async def run(self):
await self.dashboard_head.run()
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Ray dashboard.")
parser.add_argument(
"--host", required=True, type=str, help="The host to use for the HTTP server."
)
parser.add_argument(
"--port", required=True, type=int, help="The port to use for the HTTP server."
)
parser.add_argument(
"--port-retries",
required=False,
type=int,
default=0,
help="The retry times to select a valid port.",
)
parser.add_argument(
"--gcs-address", required=True, type=str, help="The address (ip:port) of GCS."
)
parser.add_argument(
"--logging-level",
required=False,
type=lambda s: logging.getLevelName(s.upper()),
default=ray_constants.LOGGER_LEVEL,
choices=ray_constants.LOGGER_LEVEL_CHOICES,
help=ray_constants.LOGGER_LEVEL_HELP,
)
parser.add_argument(
"--logging-format",
required=False,
type=str,
default=ray_constants.LOGGER_FORMAT,
help=ray_constants.LOGGER_FORMAT_HELP,
)
parser.add_argument(
"--logging-filename",
required=False,
type=str,
default=dashboard_consts.DASHBOARD_LOG_FILENAME,
help="Specify the name of log file, "
'log to stdout if set empty, default is "{}"'.format(
dashboard_consts.DASHBOARD_LOG_FILENAME
),
)
parser.add_argument(
"--logging-rotate-bytes",
required=False,
type=int,
default=ray_constants.LOGGING_ROTATE_BYTES,
help="Specify the max bytes for rotating "
"log file, default is {} bytes.".format(ray_constants.LOGGING_ROTATE_BYTES),
)
parser.add_argument(
"--logging-rotate-backup-count",
required=False,
type=int,
default=ray_constants.LOGGING_ROTATE_BACKUP_COUNT,
help="Specify the backup count of rotated log file, default is {}.".format(
ray_constants.LOGGING_ROTATE_BACKUP_COUNT
),
)
parser.add_argument(
"--log-dir",
required=True,
type=str,
default=None,
help="Specify the path of log directory.",
)
parser.add_argument(
"--temp-dir",
required=True,
type=str,
default=None,
help="Specify the path of the temporary directory use by Ray process.",
)
parser.add_argument(
"--session-dir",
required=True,
type=str,
default=None,
help="Specify the path of the session directory of the cluster.",
)
parser.add_argument(
"--minimal",
action="store_true",
help=(
"Minimal dashboard only contains a subset of features that don't "
"require additional dependencies installed when ray is installed "
"by `pip install ray[default]`."
),
)
parser.add_argument(
"--modules-to-load",
required=False,
default=None,
help=(
"Specify the list of module names in [module_1],[module_2] format."
"E.g., JobHead,StateHead... "
"If nothing is specified, all modules are loaded."
),
)
args = parser.parse_args()
try:
setup_component_logger(
logging_level=args.logging_level,
logging_format=args.logging_format,
log_dir=args.log_dir,
filename=args.logging_filename,
max_bytes=args.logging_rotate_bytes,
backup_count=args.logging_rotate_backup_count,
)
if args.modules_to_load:
modules_to_load = set(args.modules_to_load.strip(" ,").split(","))
else:
# None == default.
modules_to_load = None
dashboard = Dashboard(
args.host,
args.port,
args.port_retries,
args.gcs_address,
log_dir=args.log_dir,
temp_dir=args.temp_dir,
session_dir=args.session_dir,
minimal=args.minimal,
modules_to_load=modules_to_load,
)
loop = asyncio.get_event_loop()
def sigterm_handler():
logger.warn("Exiting with SIGTERM immediately...")
os._exit(signal.SIGTERM)
if sys.platform != "win32":
# TODO(rickyyx): we currently do not have any logic for actual
# graceful termination in the dashboard. Most of the underlying
# async tasks run by the dashboard head doesn't handle CancelledError.
# So a truly graceful shutdown is not trivial w/o much refactoring.
# Re-open the issue: https://github.com/ray-project/ray/issues/25518
# if a truly graceful shutdown is required.
loop.add_signal_handler(signal.SIGTERM, sigterm_handler)
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, dashboard_utils.FrontendNotFoundError):
logger.warning(message)
else:
logger.error(message)
raise e
# Something went wrong, so push an error to all drivers.
gcs_publisher = GcsPublisher(address=args.gcs_address)
ray._private.utils.publish_error_to_driver(
ray_constants.DASHBOARD_DIED_ERROR,
message,
gcs_publisher=gcs_publisher,
)