181 lines
8 KiB
Python
181 lines
8 KiB
Python
import datetime
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import logging
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import time
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from functools import wraps
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from Queue import Queue, Full
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from flask import g, request
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from trollius import Return
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logger = logging.getLogger(__name__)
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# Buckets for the API response times.
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API_RESPONSE_TIME_BUCKETS = [.01, .025, .05, .1, .25, .5, 1.0, 2.5, 5.0]
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# Buckets for the builder start times.
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BUILDER_START_TIME_BUCKETS = [.5, 1.0, 5.0, 10.0, 30.0, 60.0, 120.0, 180.0, 240.0, 300.0, 600.0]
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class MetricQueue(object):
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""" Object to which various metrics are written, for distribution to metrics collection
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system(s) such as Prometheus.
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"""
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def __init__(self, prom):
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# Define the various exported metrics.
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self.resp_time = prom.create_histogram('response_time', 'HTTP response time in seconds',
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labelnames=['endpoint'],
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buckets=API_RESPONSE_TIME_BUCKETS)
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self.resp_code = prom.create_counter('response_code', 'HTTP response code',
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labelnames=['endpoint', 'code'])
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self.non_200 = prom.create_counter('response_non200', 'Non-200 HTTP response codes',
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labelnames=['endpoint'])
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self.multipart_upload_start = prom.create_counter('multipart_upload_start',
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'Multipart upload started')
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self.multipart_upload_end = prom.create_counter('multipart_upload_end',
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'Multipart upload ends.', labelnames=['type'])
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self.build_capacity_shortage = prom.create_gauge('build_capacity_shortage',
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'Build capacity shortage.')
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self.builder_time_to_start = prom.create_histogram('builder_tts',
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'Time from triggering to starting a builder.',
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labelnames=['builder_type'],
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buckets=BUILDER_START_TIME_BUCKETS)
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self.builder_time_to_build = prom.create_histogram('builder_ttb',
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'Time from triggering to actually starting a build',
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labelnames=['builder_type'],
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buckets=BUILDER_START_TIME_BUCKETS)
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self.build_time = prom.create_histogram('build_time', 'Time spent buildig', labelnames=['builder_type'])
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self.builder_fallback = prom.create_counter('builder_fallback', 'Builder fell back to ec2 executor')
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self.percent_building = prom.create_gauge('build_percent_building', 'Percent building.')
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self.build_counter = prom.create_counter('builds', 'Number of builds', labelnames=['name'])
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self.ephemeral_build_workers = prom.create_counter('ephemeral_build_workers',
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'Number of started ephemeral build workers')
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self.ephemeral_build_worker_failure = prom.create_counter('ephemeral_build_worker_failure',
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'Number of failed-to-start ephemeral build workers')
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self.work_queue_running = prom.create_gauge('work_queue_running', 'Running items in a queue',
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labelnames=['queue_name'])
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self.work_queue_available = prom.create_gauge('work_queue_available',
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'Available items in a queue',
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labelnames=['queue_name'])
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self.repository_pull = prom.create_counter('repository_pull', 'Repository Pull Count',
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labelnames=['namespace', 'repo_name', 'protocol',
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'status'])
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self.repository_push = prom.create_counter('repository_push', 'Repository Push Count',
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labelnames=['namespace', 'repo_name', 'protocol',
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'status'])
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self.repository_build_completed = prom.create_counter('repository_build_completed',
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'Repository Build Complete Count',
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labelnames=['namespace', 'repo_name',
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'status', 'executor'])
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self.chunk_size = prom.create_histogram('chunk_size',
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'Registry blob chunk size',
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labelnames=['storage_region'])
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self.chunk_upload_time = prom.create_histogram('chunk_upload_time',
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'Registry blob chunk upload time',
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labelnames=['storage_region'])
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self.authentication_count = prom.create_counter('authenication_count',
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'Authentication count',
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labelnames=['kind', 'status'])
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self.repository_count = prom.create_gauge('repository_count', 'Number of repositories')
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self.user_count = prom.create_gauge('user_count', 'Number of users')
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self.org_count = prom.create_gauge('org_count', 'Number of Organizations')
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self.robot_count = prom.create_gauge('robot_count', 'Number of robot accounts')
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# Deprecated: Define an in-memory queue for reporting metrics to CloudWatch or another
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# provider.
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self._queue = None
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def enable_deprecated(self, maxsize=10000):
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self._queue = Queue(maxsize)
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def put_deprecated(self, name, value, **kwargs):
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if self._queue is None:
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logger.debug('No metric queue %s %s %s', name, value, kwargs)
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return
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try:
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kwargs.setdefault('timestamp', datetime.datetime.now())
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kwargs.setdefault('dimensions', {})
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self._queue.put_nowait((name, value, kwargs))
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except Full:
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logger.error('Metric queue full')
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def get_deprecated(self):
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return self._queue.get()
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def get_nowait_deprecated(self):
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return self._queue.get_nowait()
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def duration_collector_async(metric, labelvalues):
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""" Decorates a method to have its duration time logged to the metric. """
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def decorator(func):
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@wraps(func)
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def wrapper(*args, **kwargs):
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trigger_time = time.time()
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try:
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rv = func(*args, **kwargs)
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except Return as e:
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metric.Observe(time.time() - trigger_time, labelvalues=labelvalues)
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raise e
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return rv
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return wrapper
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return decorator
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def time_decorator(name, metric_queue):
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""" Decorates an endpoint method to have its request time logged to the metrics queue. """
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after = _time_after_request(name, metric_queue)
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def decorator(func):
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@wraps(func)
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def wrapper(*args, **kwargs):
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_time_before_request()
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rv = func(*args, **kwargs)
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after(rv)
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return rv
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return wrapper
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return decorator
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def time_blueprint(bp, metric_queue):
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""" Decorates a blueprint to have its request time logged to the metrics queue. """
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bp.before_request(_time_before_request)
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bp.after_request(_time_after_request(bp.name, metric_queue))
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def _time_before_request():
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g._request_start_time = time.time()
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def _time_after_request(name, metric_queue):
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def f(r):
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start = getattr(g, '_request_start_time', None)
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if start is None:
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return r
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dur = time.time() - start
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dims = {'endpoint': request.endpoint}
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metric_queue.put_deprecated('ResponseTime', dur, dimensions=dims, unit='Seconds')
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metric_queue.put_deprecated('ResponseCode', r.status_code, dimensions=dims)
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metric_queue.resp_time.Observe(dur, labelvalues=[request.endpoint])
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metric_queue.resp_code.Inc(labelvalues=[request.endpoint, r.status_code])
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if r.status_code >= 500:
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metric_queue.put_deprecated('5XXResponse', 1, dimensions={'name': name})
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elif r.status_code < 200 or r.status_code >= 300:
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metric_queue.put_deprecated('Non200Response', 1, dimensions={'name': name})
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metric_queue.non_200.Inc(labelvalues=[request.endpoint])
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return r
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return f
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