def postToDataDog(self, numOfSitesWithStaleHistory):
api.api_key = 'fe1cd13de75c73f4f4de29acd85c4b36'
api.application_key = 'd0a1be7f8d3d141c8adda765ceb41f90422cbcda'
metricName = 'foobar.staleHistory.numSites'
self.logMsg("posting to DataDog: " + metricName + " = " +
str(numOfSitesWithStaleHistory))
api.metric(metricName, numOfSitesWithStaleHistory)
def sendDataToDatadog(datadogApiKey, grokServer, grokApiKey, numRecords,
metricId):
"""Get data from Grok and send to Datadog.
This gets metric data for the metric matching metricId and converts it into
two datasets in the Datadog format: one for the values and one for the
anomaly scores.
"""
# Configure the Datadog library
dog_http_api.api_key = datadogApiKey
grok = GrokSession(server=grokServer, apikey=grokApiKey)
server, metricName = _getMetricServerAndName(grok, metricId)
valuesData, anomaliesData = _getMetricData(grok, metricId, numRecords)
# Hack to limit number of records for Grok instances prior to version 1.3
# that don't respect the limit parameter when getting metric data.
valuesData = valuesData[-numRecords:]
anomaliesData = anomaliesData[-numRecords:]
print "Sending %i records for metric %s on server %s" % (
len(valuesData), metricName, server)
response = dog_http_api.metric(metricName + ".value",
valuesData,
host=server)
if response["status"] != "ok":
print "Datadog upload failed with response:\n\n%r" % response
response = dog_http_api.metric(metricName + ".anomalyScore",
anomaliesData,
host=server)
if response["status"] != "ok":
print "Datadog upload failed with response:\n\n%r" % response
def mailgun_event():
ts = request.form['timestamp']
event_tag = "event_name:" + request.form['event']
api.metric('mailgun.event', (ts, 1),
tags=[event_tag],
metric_type='counter')
return "200"
def sendDataToDatadog(datadogApiKey, YOMPServer, YOMPApiKey, numRecords,
metricId):
"""Get data from YOMP and send to Datadog.
This gets metric data for the metric matching metricId and converts it into
two datasets in the Datadog format: one for the values and one for the
anomaly scores.
"""
# Configure the Datadog library
dog_http_api.api_key = datadogApiKey
YOMP = YOMPSession(server=YOMPServer, apikey=YOMPApiKey)
server, metricName = _getMetricServerAndName(YOMP, metricId)
valuesData, anomaliesData = _getMetricData(YOMP, metricId, numRecords)
# Hack to limit number of records for YOMP instances prior to version 1.3
# that don't respect the limit parameter when getting metric data.
valuesData = valuesData[-numRecords:]
anomaliesData = anomaliesData[-numRecords:]
print "Sending %i records for metric %s on server %s" % (
len(valuesData), metricName, server)
response = dog_http_api.metric(metricName + ".value", valuesData,
host=server)
if response["status"] != "ok":
print "Datadog upload failed with response:\n\n%r" % response
response = dog_http_api.metric(metricName + ".anomalyScore", anomaliesData,
host=server)
if response["status"] != "ok":
print "Datadog upload failed with response:\n\n%r" % response
def postToDataDog(self, num):
api.api_key = 'fe1cd13de75c73f4f4de29acd85c4b36'
api.application_key = 'd0a1be7f8d3d141c8adda765ceb41f90422cbcda'
metricName = 'foobar.liveServiceDown.numStations'
self.logMessage("posting to DataDog: " + metricName + " = " + str(num))
api.metric(metricName, num)
def send_to_datadog(host, success):
ts = int(time.time())
if success:
result = "success"
else:
result = "failure"
metric_name = "example.integration.{}".format(result)
api.metric(metric_name, (ts, 1), tags=["host:{}".format(host)])
print ("POSTED to DataDog")
def report_metrics(metrics):
"""
Send metrics to DataDog.
Arguments:
metrics (dict): data to publish
"""
for key, value in metrics.iteritems():
print u"Sending {} ==> {}%".format(key, value)
dog_http_api.metric(key, value)
def report_metrics(metrics):
"""
Send metrics to DataDog.
Arguments:
metrics (dict): data to publish
"""
for key, value in metrics.iteritems():
print u"Sending {} ==> {}%".format(key, value)
dog_http_api.metric(key, value)
def report_metrics(data, groups):
"""
Given a `CoverageData` object, send coverage percentages
for each group to DataDog.
`groups` is a dict mapping aggregate group names to source file patterns.
Group names are used in the name of the metric sent to DataDog.
"""
for group_name, pattern in groups.iteritems():
metric = 'test_eng.coverage.{group}'.format(group=group_name.replace(' ', '_'))
percent = data.coverage(pattern)
if percent is not None:
print u"Sending {} ==> {}%".format(metric, percent)
dog_http_api.metric(metric, percent)
def push_to_datadog(qresults, team):
ddog_url = "https://app.datadoghq.com/api/"
api.api_key = "bc7d8263101c9dce7651f783a829f403"
api.application_key = "7d37c0dfe91e953500c1dd5c8d24ae1ab9244a80"
# Note timestamp must be ~current per datadog API, so not useful for back porting
# or for really even sending ever, therefore we're just going to take the first item in the array
# Datadog api requires a float to be passed in for single values and tuple for multi values
# FIXME don't just send team-budget and team-actual make it dynamic
budget_value = float(qresults[0]['budget'])
budget_name = "'team.members.budget." + team.replace(" ", "_") + "." + qresults[0]['team'].replace(" ", "_") + "'"
actual_value = float(qresults[0]['actual'])
actual_name = "'team.members.actual." + team.replace(" ", "_") + "." + qresults[0]['team'].replace(" ", "_") + "'"
ddtags = '"team:%s, subteam:%s' % (team.replace(" ", "_"), qresults[0]['team'].replace(" ", "_")) + '"'
response = api.metric(budget_name, budget_value, tags=[ddtags])
#print("api.metric(%s, %s, tags=[%s])" % (budget_name, budget_value, ddtags))
print("Datadog - response - %s" % (response))
response = api.metric(actual_name, actual_value, tags=[ddtags])
#print("api.metric(%s, %s, tags=[%s])" % (actual_name, actual_value, ddtags))
print("Datadog - response - %s" % (response))
def push_to_datadog(json_data):
ddog_url = "https://app.datadoghq.com/api/"
api.api_key = "bc7d8263101c9dce7651f783a829f403"
api.application_key = "7d37c0dfe91e953500c1dd5c8d24ae1ab9244a80"
for metric in json_data:
# Note timestamp must be ~current per datadog API, so not useful for back porting
# or for really even sending ever
# Datadog api requires a float/int to be passed in for single values and tuple for multi values
metric_name = "'jenkins.custom.stats." + metric + "'"
metric_value = json_data[metric][0]['value']
response = api.metric(metric_name, metric_value)
#print("api.metric(%s, %s)" % (metric_name, metric_value))
print("DataDog response - %s" % (response))
def push_to_datadog(qresults, proj, team):
ddog_url = "https://app.datadoghq.com/api/"
api.api_key = "bc7d8263101c9dce7651f783a829f403"
api.application_key = "7d37c0dfe91e953500c1dd5c8d24ae1ab9244a80"
for metric in qresults:
# Note timestamp must be ~current per datadog API, so not useful for back porting
# or for really even sending ever
# Datadog api requires a float to be passed in for single values and tuple for multi values
metric_value = float(qresults[metric]['value'])
metric_name = "'mingle." + metric.replace(" ", "_") + '.' + proj.replace(" ", "_") + '.' + team.replace(" ", "_") + "'"
ddtags = '"project:%s, team:%s, minglemetric:%s' % (proj.replace(" ", "_"), team.replace(" ", "_"), metric.replace(" ", "_")) + '"'
response = api.metric(metric_name, metric_value, tags=[ddtags])
#print("api.metric(%s, %s, tags=[%s])" % (metric_name, metric_value, ddtags))
print("response - %s" % (response))
def recordKeys(keys, keyType='inbox'):
details = {}
keyTypeLabel = "%sKeys" % keyType
details["timestamp"] = str(datetime.datetime.now())
details[keyTypeLabel] = len(keys)
keyNames = []
if len(keys) > 0:
for key in keys:
keyNames.append(key.name)
details[keyTypeLabel] = keyNames
lastRuns.append(details)
if len(lastRuns) > 60:
lastRuns.popleft()
if options.datadogApiKey != None:
api.api_key = options.datadogApiKey
api.application_key = options.datadogAppKey
api.timeout = 15
api.swallow = False
metricName = "cloudops.yumrepomanager.%s.%s" % (
options.yumRepoBucketName.replace('-', '_'), keyTypeLabel)
log("Publishing metric to datadog: %s..." % metricName)
log(" --> %s" % json.dumps(api.metric(metricName, len(keys))))
from dogapi import dog_http_api as api
api.api_key = 'apikey_3'
api.application_key = '9d945c35fd7cc7abb1088fd0632ef8e25516af74'
# Submit a single point with a timestamp of `now`
api.metric('page.views', 1000)
# Submit a point with a timestamp (must be ~current)
api.metric('my.pair', (1317652676, 15))
# Submit multiple points.
api.metric('my.series', [(1317652676, 15), (1317652800, 16)])
# Submit a point with a host and tags.
api.metric('my.series', 100, host="myhost.example.com", tags=["version:1"])
import os
import time
from datetime import datetime as dt
from datetime import timedelta as delta
import math
# import the simple dog client
from dogapi import dog_http_api as dog
# give dog your credentials (we're using os.environ to let you experiment via environment variables)
# in this example we're only reporting data, so we only need an API key
# see: https://github.com/DataDog/dogapi/wiki/Authentication for more on API authentication
dog.api_key = os.environ.get("DATADOG_API_KEY")
# emit points one by one. timestamp is determined at call time.
dog.metric('test.api.test_metric', 4.0, host="some_host")
time.sleep(1)
dog.metric('test.api.test_metric', 5.0, host="another_host")
# emit a list of points in one go as a list of (timestamp, value)
# here we pretend to send a point a minute for the past hour
now = dt.now()
points = []
# create the list here (a list comprehension would do too)
for i in range(60, 1, -1):
t = time.mktime((now - delta(minutes=i)).timetuple())
points.append((t, math.cos(i) + 1.0))
