Source code for ironic_lib.metrics

# Copyright 2016 Rackspace Hosting
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#    Licensed under the Apache License, Version 2.0 (the "License"); you may
#    not use this file except in compliance with the License. You may obtain
#    a copy of the License at
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#         http://www.apache.org/licenses/LICENSE-2.0
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#    Unless required by applicable law or agreed to in writing, software
#    distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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import abc
import functools
import random
import time

import six

from ironic_lib.common.i18n import _


[docs]class Timer(object): """A timer decorator and context manager. This metric type times the decorated method or code running inside the context manager, and emits the time as the metric value. It is bound to this MetricLogger. For example:: from ironic_lib import metrics_utils METRICS = metrics_utils.get_metrics_logger() @METRICS.timer('foo') def foo(bar, baz): print bar, baz with METRICS.timer('foo'): do_something() """ def __init__(self, metrics, name): """Init the decorator / context manager. :param metrics: The metric logger :param name: The metric name """ if not isinstance(name, six.string_types): raise TypeError(_("The metric name is expected to be a string. " "Value is %s") % name) self.metrics = metrics self.name = name self._start = None def __call__(self, f): @functools.wraps(f) def wrapped(*args, **kwargs): start = _time() result = f(*args, **kwargs) duration = _time() - start # Log the timing data (in ms) self.metrics.send_timer(self.metrics.get_metric_name(self.name), duration * 1000) return result return wrapped def __enter__(self): self._start = _time() def __exit__(self, exc_type, exc_val, exc_tb): duration = _time() - self._start # Log the timing data (in ms) self.metrics.send_timer(self.metrics.get_metric_name(self.name), duration * 1000)
[docs]class Counter(object): """A counter decorator and context manager. This metric type increments a counter every time the decorated method or context manager is executed. It is bound to this MetricLogger. For example:: from ironic_lib import metrics_utils METRICS = metrics_utils.get_metrics_logger() @METRICS.counter('foo') def foo(bar, baz): print bar, baz with METRICS.counter('foo'): do_something() """ def __init__(self, metrics, name, sample_rate): """Init the decorator / context manager. :param metrics: The metric logger :param name: The metric name :param sample_rate: Probabilistic rate at which the values will be sent """ if not isinstance(name, six.string_types): raise TypeError(_("The metric name is expected to be a string. " "Value is %s") % name) if (sample_rate is not None and (sample_rate < 0.0 or sample_rate > 1.0)): msg = _("sample_rate is set to %s. Value must be None " "or in the interval [0.0, 1.0]") % sample_rate raise ValueError(msg) self.metrics = metrics self.name = name self.sample_rate = sample_rate def __call__(self, f): @functools.wraps(f) def wrapped(*args, **kwargs): self.metrics.send_counter( self.metrics.get_metric_name(self.name), 1, sample_rate=self.sample_rate) result = f(*args, **kwargs) return result return wrapped def __enter__(self): self.metrics.send_counter(self.metrics.get_metric_name(self.name), 1, sample_rate=self.sample_rate) def __exit__(self, exc_type, exc_val, exc_tb): pass
[docs]class Gauge(object): """A gauge decorator. This metric type returns the value of the decorated method as a metric every time the method is executed. It is bound to this MetricLogger. For example:: from ironic_lib import metrics_utils METRICS = metrics_utils.get_metrics_logger() @METRICS.gauge('foo') def add_foo(bar, baz): return (bar + baz) """ def __init__(self, metrics, name): """Init the decorator / context manager. :param metrics: The metric logger :param name: The metric name """ if not isinstance(name, six.string_types): raise TypeError(_("The metric name is expected to be a string. " "Value is %s") % name) self.metrics = metrics self.name = name def __call__(self, f): @functools.wraps(f) def wrapped(*args, **kwargs): result = f(*args, **kwargs) self.metrics.send_gauge(self.metrics.get_metric_name(self.name), result) return result return wrapped
def _time(): """Wraps time.time() for simpler testing.""" return time.time() @six.add_metaclass(abc.ABCMeta)
[docs]class MetricLogger(object): """Abstract class representing a metrics logger. A MetricLogger sends data to a backend (noop or statsd). The data can be a gauge, a counter, or a timer. The data sent to the backend is composed of: - a full metric name - a numeric value The format of the full metric name is: _prefix<delim>name where: - _prefix: [global_prefix<delim>][uuid<delim>][host_name<delim>]prefix - name: the name of this metric - <delim>: the delimiter. Default is '.' """ def __init__(self, prefix='', delimiter='.'): """Init a MetricLogger. :param prefix: Prefix for this metric logger. This string will prefix all metric names. :param delimiter: Delimiter used to generate the full metric name. """ self._prefix = prefix self._delimiter = delimiter
[docs] def get_metric_name(self, name): """Get the full metric name. The format of the full metric name is: _prefix<delim>name where: - _prefix: [global_prefix<delim>][uuid<delim>][host_name<delim>] prefix - name: the name of this metric - <delim>: the delimiter. Default is '.' :param name: The metric name. :return: The full metric name, with logger prefix, as a string. """ if not self._prefix: return name return self._delimiter.join([self._prefix, name])
[docs] def send_gauge(self, name, value): """Send gauge metric data. Gauges are simple values. The backend will set the value of gauge 'name' to 'value'. :param name: Metric name :param value: Metric numeric value that will be sent to the backend """ self._gauge(name, value)
[docs] def send_counter(self, name, value, sample_rate=None): """Send counter metric data. Counters are used to count how many times an event occurred. The backend will increment the counter 'name' by the value 'value'. Optionally, specify sample_rate in the interval [0.0, 1.0] to sample data probabilistically where:: P(send metric data) = sample_rate If sample_rate is None, then always send metric data, but do not have the backend send sample rate information (if supported). :param name: Metric name :param value: Metric numeric value that will be sent to the backend :param sample_rate: Probabilistic rate at which the values will be sent. Value must be None or in the interval [0.0, 1.0]. """ if (sample_rate is None or random.random() < sample_rate): return self._counter(name, value, sample_rate=sample_rate)
[docs] def send_timer(self, name, value): """Send timer data. Timers are used to measure how long it took to do something. :param m_name: Metric name :param m_value: Metric numeric value that will be sent to the backend """ self._timer(name, value)
[docs] def timer(self, name): return Timer(self, name)
[docs] def counter(self, name, sample_rate=None): return Counter(self, name, sample_rate)
[docs] def gauge(self, name): return Gauge(self, name)
@abc.abstractmethod def _gauge(self, name, value): """Abstract method for backends to implement gauge behavior.""" @abc.abstractmethod def _counter(self, name, value, sample_rate=None): """Abstract method for backends to implement counter behavior.""" @abc.abstractmethod def _timer(self, name, value): """Abstract method for backends to implement timer behavior."""
[docs]class NoopMetricLogger(MetricLogger): """Noop metric logger that throws away all metric data.""" def _gauge(self, name, value): pass def _counter(self, name, value, sample_rate=None): pass def _timer(self, m_name, value): pass

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