def reset_prometheus(getpid=os.getpid):
"""Reset prometheus file cache.
MultiProcessValue keeps a files cache which is only accessible via
a closure. So the only way to clear the cache is to recreate the closure,
which is what we do here.
"""
try:
from prometheus_client import values
values.ValueClass = values.MultiProcessValue(getpid)
except ImportError:
pass # prometheus is optional
class MultiprocessMutexValue(values.MultiProcessValue()):
"""
MultiprocessValue protected by mutex
Rucio usually is deployed using the apache MPM module, which means that it both uses multiple
subprocesses, and multiple threads per subprocess.
"""
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self._lock = Lock()
def inc(self, amount):
with self._lock:
return super().inc(amount)
def set(self, value):
with self._lock:
return super().set(value)
def get(self):
with self._lock:
return super().get()
import os
from prometheus_client import values
# Override pid function if we have a reusable gunicorn worker ID
if os.environ.get('prometheus_multiproc_dir', None): # noqa
try:
values.ValueClass = values.MultiProcessValue(
process_identifier=lambda: os.environ.get('APP_WORKER_ID', 1000), )
except TypeError:
values.ValueClass = values.MultiProcessValue(
_pidFunc=lambda: os.environ.get('APP_WORKER_ID', 1000), )
# Import all files that define metrics. This has the effect that
# `import django_prometheus` will always instanciate all metric
# objects right away.
import django_prometheus.middleware
import django_prometheus.models
# Import pip_prometheus to export the pip metrics automatically.
try:
import pip_prometheus
except ImportError:
# If people don't have pip, don't export anything.
pass
try: # Load celery exporter if possible
import django_prometheus.celery
except ImportError:
pass
default_app_config = 'django_prometheus.apps.DjangoPrometheusConfig'
def get_label_value(self):
"""
:return: the label value
:rtype: str
"""
return self.name.lower()
REGISTRY = prometheus_client.CollectorRegistry()
if "prometheus_multiproc_dir" in os.environ:
# For why this is needed see:
# https://github.com/prometheus/client_python/issues/275#issuecomment-504755024
import uwsgi
prometheus_client.values.ValueClass = values.MultiProcessValue(
uwsgi.worker_id)
multiprocess.MultiProcessCollector(REGISTRY)
APPLY = ActionMetrics('apply', 'apply a manifest', ['manifest'])
# TODO: Ideally include an action (ChartDeployAction) label, but that's not
# determined until after chart handling starts.
CHART_HANDLE = ChartHandleMetrics(
'chart_handle',
'handle a chart (including delete, deploy, test (all as necessary) but '
'not download)', ['manifest', 'chart'])
CHART_DOWNLOAD = ActionMetrics(
'chart_download', 'download a chart (will be noop if previously cached)',
['manifest', 'chart'])
CHART_DELETE = ActionMetrics('chart_delete', 'delete a chart',
['manifest', 'chart'])
def setUpClass(cls):
cls.temp_dir = TemporaryDirectory()
os.environ["prometheus_multiproc_dir"] = cls.temp_dir.name
cls.patch_value_class = unittest.mock.patch.object(
values, "ValueClass", values.MultiProcessValue(cls.current_test))
cls.patch_value_class.start()
# remove all *container*.db files since we're restarting the process
files = glob(
f"/{getenv('PROMETHEUS_MULTIPROC_DIR')}/*{audius_prometheus_container}*")
for f in files:
logger.info(f"Removing prometheus file: {f}")
remove(f)
# since the server and worker containers share ${PROMETHEUS_MULTIPROC_DIR}/,
# will ensure each container uses its own prefix to avoid pid collisions between the
# two containers when using the prometheus-client in multi-process mode
def process_identifier():
return f"{audius_prometheus_container}_{getpid()}"
values.ValueClass = values.MultiProcessValue(
process_identifier=process_identifier)
@bp.route("/prometheus_metrics", methods=["GET"])
def prometheus_metrics_exporter():
PrometheusMetric.populate_collectors()
registry = CollectorRegistry()
multiprocess.MultiProcessCollector(registry)
data = generate_latest(registry)
headers = {
"Content-type": CONTENT_TYPE_LATEST,
"Content-Length": str(len(data)),
}
return Response(data, headers=headers, mimetype=CONTENT_TYPE_LATEST)
