Current File : //lib/python3.9/site-packages/cockpit/channels/metrics.py
# This file is part of Cockpit.
#
# Copyright (C) 2022 Red Hat, Inc.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
import asyncio
import json
import logging
import sys
import time
from collections import defaultdict
from typing import Dict, List, NamedTuple, Optional, Set, Tuple, Type, Union
from ..channel import AsyncChannel, ChannelError
from ..jsonutil import JsonList, JsonObject, get_int
from ..samples import SAMPLERS, SampleDescription, Sampler, Samples
logger = logging.getLogger(__name__)
class MetricInfo(NamedTuple):
derive: Optional[str]
desc: SampleDescription
class InternalMetricsChannel(AsyncChannel):
payload = 'metrics1'
restrictions = [('source', 'internal')]
metrics: List[MetricInfo]
samplers: Set
samplers_cache: Optional[Dict[str, Tuple[Type[Sampler], SampleDescription]]] = None
interval: int = 1000
need_meta: bool = True
last_timestamp: float = 0
next_timestamp: float = 0
@classmethod
def ensure_samplers(cls):
if cls.samplers_cache is None:
cls.samplers_cache = {desc.name: (sampler, desc) for sampler in SAMPLERS for desc in sampler.descriptions}
def parse_options(self, options: JsonObject) -> None:
logger.debug('metrics internal open: %s, channel: %s', options, self.channel)
interval = get_int(options, 'interval', self.interval)
if interval <= 0 or interval > sys.maxsize:
raise ChannelError('protocol-error', message=f'invalid "interval" value: {interval}')
self.interval = interval
metrics = options.get('metrics')
if not isinstance(metrics, list) or len(metrics) == 0:
logger.error('invalid "metrics" value: %s', metrics)
raise ChannelError('protocol-error', message='invalid "metrics" option was specified (not an array)')
assert self.samplers_cache, "ensure_samples not called"
sampler_classes = set()
for metric in metrics:
# validate it's an object
name = metric.get('name')
units = metric.get('units')
derive = metric.get('derive')
try:
sampler, desc = self.samplers_cache[name]
except KeyError as exc:
logger.error('unsupported metric: %s', name)
raise ChannelError('not-supported', message=f'unsupported metric: {name}') from exc
if units and units != desc.units:
raise ChannelError('not-supported', message=f'{name} has units {desc.units}, not {units}')
sampler_classes.add(sampler)
self.metrics.append(MetricInfo(derive=derive, desc=desc))
self.samplers = {cls() for cls in sampler_classes}
def send_meta(self, samples: Samples, timestamp: float):
metrics: JsonList = []
for metricinfo in self.metrics:
if metricinfo.desc.instanced:
metrics.append({
'name': metricinfo.desc.name,
'units': metricinfo.desc.units,
'instances': list(samples[metricinfo.desc.name].keys()),
'semantics': metricinfo.desc.semantics
})
else:
metrics.append({
'name': metricinfo.desc.name,
'derive': metricinfo.derive, # type: ignore[dict-item]
'units': metricinfo.desc.units,
'semantics': metricinfo.desc.semantics
})
now = int(time.time()) * 1000
self.send_json(source='internal', interval=self.interval, timestamp=timestamp * 1000,
now=now, metrics=metrics)
self.need_meta = False
def sample(self) -> Samples:
samples: Samples = defaultdict(dict)
for sampler in self.samplers:
sampler.sample(samples)
return samples
def calculate_sample_rate(self, value: float, old_value: Optional[float]) -> Union[float, bool]:
if old_value is not None:
return (value - old_value) / (self.next_timestamp - self.last_timestamp)
else:
return False
def send_updates(self, samples: Samples, last_samples: Samples):
data: List[Union[float, List[Optional[Union[float, bool]]]]] = []
timestamp = time.time()
self.next_timestamp = timestamp
for metricinfo in self.metrics:
value = samples[metricinfo.desc.name]
if metricinfo.desc.instanced:
old_value = last_samples[metricinfo.desc.name]
assert isinstance(value, dict)
assert isinstance(old_value, dict)
# If we have less or more keys the data changed, send a meta message.
if value.keys() != old_value.keys():
self.need_meta = True
if metricinfo.derive == 'rate':
instances: List[Optional[Union[float, bool]]] = []
for key, val in value.items():
instances.append(self.calculate_sample_rate(val, old_value.get(key)))
data.append(instances)
else:
data.append(list(value.values()))
else:
old_value = last_samples.get(metricinfo.desc.name)
assert not isinstance(value, dict)
assert not isinstance(old_value, dict)
if metricinfo.derive == 'rate':
data.append(self.calculate_sample_rate(value, old_value))
else:
data.append(value)
if self.need_meta:
self.send_meta(samples, timestamp)
self.last_timestamp = self.next_timestamp
self.send_text(json.dumps([data]))
async def run(self, options: JsonObject) -> None:
self.metrics = []
self.samplers = set()
InternalMetricsChannel.ensure_samplers()
self.parse_options(options)
self.ready()
last_samples: Samples = defaultdict(dict)
while True:
samples = self.sample()
self.send_updates(samples, last_samples)
last_samples = samples
await asyncio.sleep(self.interval / 1000)
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