Moves and rename common/djangoapps/newrelic_custom_metrics.
This commit is contained in:
Robert Raposa
@@ -1,52 +0,0 @@
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"""
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This is an interface to the newrelic_custom_metrics middleware. Functions
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defined in this module can be used to report custom metrics to New Relic. For
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example:
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import newrelic_custom_metrics
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...
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newrelic_custom_metrics.accumulate('xb_user_state.get_many.num_items', 4)
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There is no need to do anything else. The metrics are automatically cleared
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before the next request.
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We try to keep track of our custom metrics at:
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https://openedx.atlassian.net/wiki/display/PERF/Custom+Metrics+in+New+Relic
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TODO: supply additional public functions for storing strings and booleans.
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"""
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from newrelic_custom_metrics import middleware
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def accumulate(name, value):
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"""
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Accumulate custom New Relic metric for the current request.
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The named metric is accumulated by a numerical amount using the sum. All
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metrics are queued up in the request_cache for this request. At the end of
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the request, the newrelic_custom_metrics middleware will batch report all
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queued accumulated metrics to NR.
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Arguments:
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name (str): The metric name. It should be period-delimited, and
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increase in specificty from left to right. For example:
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'xb_user_state.get_many.num_items'.
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value (number): The amount to accumulate into the named metric. When
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accumulate() is called multiple times for a given metric name
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during a request, the sum of the values for each call is reported
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for that metric. For metrics which don't make sense to accumulate,
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make sure to only call this function once during a request.
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"""
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middleware.NewRelicCustomMetrics.accumulate_metric(name, value)
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def increment(name):
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"""
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Increment a custom New Relic metric representing a counter.
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Here we simply accumulate a new custom metric with a value of 1, and the
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middleware should automatically aggregate this metric.
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"""
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accumulate(name, 1)
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@@ -1,71 +0,0 @@
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"""
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Middleware for handling the storage, aggregation, and reporing of custom New
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Relic metrics.
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This middleware will only call on the newrelic agent if there are any metrics
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to report for this request, so it will not incur any processing overhead for
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request handlers which do not record custom metrics.
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"""
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import logging
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log = logging.getLogger(__name__)
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try:
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import newrelic.agent
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except ImportError:
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log.warning("Unable to load NewRelic agent module")
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newrelic = None # pylint: disable=invalid-name
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import request_cache
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REQUEST_CACHE_KEY = 'newrelic_custom_metrics'
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class NewRelicCustomMetrics(object):
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"""
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The middleware class. Make sure to add below the request cache in
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MIDDLEWARE_CLASSES.
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"""
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@classmethod
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def _get_metrics_cache(cls):
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"""
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Get a reference to the part of the request cache wherein we store New
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Relic custom metrics related to the current request.
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"""
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return request_cache.get_cache(name=REQUEST_CACHE_KEY)
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@classmethod
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def accumulate_metric(cls, name, value):
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"""
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Accumulate a custom metric (name and value) in the metrics cache.
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"""
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metrics_cache = cls._get_metrics_cache()
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metrics_cache.setdefault(name, 0)
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metrics_cache[name] += value
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@classmethod
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def _batch_report(cls):
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"""
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Report the collected custom metrics to New Relic.
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"""
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if not newrelic:
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return
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metrics_cache = cls._get_metrics_cache()
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for metric_name, metric_value in metrics_cache.iteritems():
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newrelic.agent.add_custom_parameter(metric_name, metric_value)
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# Whether or not there was an exception, report any custom NR metrics that
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# may have been collected.
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def process_response(self, request, response): # pylint: disable=unused-argument
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"""
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Django middleware handler to process a response
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"""
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self._batch_report()
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return response
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def process_exception(self, request, exception): # pylint: disable=unused-argument
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"""
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Django middleware handler to process an exception
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"""
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self._batch_report()
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return None
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@@ -1,46 +0,0 @@
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"""
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Tests for newrelic custom metrics.
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"""
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from django.test import TestCase
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from mock import patch, call
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import newrelic_custom_metrics
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class TestNewRelicCustomMetrics(TestCase):
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"""
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Test the newrelic_custom_metrics middleware and helpers
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"""
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@patch('newrelic.agent')
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def test_cache_normal_contents(self, mock_newrelic_agent):
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"""
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Test normal usage of collecting and reporting custom New Relic metrics
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"""
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newrelic_custom_metrics.accumulate('hello', 10)
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newrelic_custom_metrics.accumulate('world', 10)
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newrelic_custom_metrics.accumulate('world', 10)
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newrelic_custom_metrics.increment('foo')
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newrelic_custom_metrics.increment('foo')
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# based on the metric data above, we expect the following calls to newrelic:
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nr_agent_calls_expected = [
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call('hello', 10),
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call('world', 20),
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call('foo', 2),
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]
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# fake a response to trigger metrics reporting
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newrelic_custom_metrics.middleware.NewRelicCustomMetrics().process_response(
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'fake request',
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'fake response',
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)
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# Assert call counts to newrelic.agent.add_custom_parameter()
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expected_call_count = len(nr_agent_calls_expected)
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measured_call_count = mock_newrelic_agent.add_custom_parameter.call_count
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self.assertEqual(expected_call_count, measured_call_count)
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# Assert call args to newrelic.agent.add_custom_parameter(). Due to
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# the nature of python dicts, call order is undefined.
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mock_newrelic_agent.add_custom_parameter.has_calls(nr_agent_calls_expected, any_order=True)
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@@ -89,6 +89,7 @@ from openedx.core.djangoapps.external_auth.login_and_register import (
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login as external_auth_login,
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register as external_auth_register
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)
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from openedx.core.djangoapps import monitoring_utils
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import track.views
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@@ -120,8 +121,6 @@ from openedx.core.djangoapps.embargo import api as embargo_api
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import analytics
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from eventtracking import tracker
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import newrelic_custom_metrics
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# Note that this lives in LMS, so this dependency should be refactored.
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from notification_prefs.views import enable_notifications
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@@ -654,7 +653,7 @@ def dashboard(request):
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# Record how many courses there are so that we can get a better
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# understanding of usage patterns on prod.
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newrelic_custom_metrics.accumulate('num_courses', len(course_enrollments))
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monitoring_utils.accumulate('num_courses', len(course_enrollments))
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# sort the enrollment pairs by the enrollment date
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course_enrollments.sort(key=lambda x: x.created, reverse=True)
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