def getModelUrl(url, datasource='prometheus', isUpper=None):
# None to make sure drop anomaly is tured on
#if modeDropAnomaly is None:
# return None
origMetricName = None
if datasource == 'prometheus':
origMetricName = retrieveMetricName(url)
elif datasource == 'wavefront':
origMetricName, others = parseQueryData(url)
newMetricName = getModelMetricName(origMetricName, datasource, isUpper)
return url.replace(origMetricName, newMetricName)
def test_wavefront_2(self):
nn, kv = parseQueryData(self.str3)
expected_nn = 'appdynamics_apm_transactions_errors_per_min'
self.assertEqual(nn, expected_nn)
def test_wavefront_0(self):
nn, kv = parseQueryData(self.str1)
expected_nn = 'ad_apm_errors_errors_per_min'
self.assertEqual(nn, expected_nn)
def test_wavefront_1(self):
nn, kv = parseQueryData(self.str2)
expected_nn = 'tf_http_server_requests_count'
self.assertEqual(nn, expected_nn)
#import sys
#sys.path.append('../')
from wavefront.metric import parseQueryData
str1 = 'sum(ts(tf.http.server.requests.count, env="prd" and app="abc" and status="5*"))'
nn, kv = parseQueryData(str1)
print(nn)
print(kv)
str1 = 'avg(align(60s, mean, ts("ad.apm.errors.errors_per_min", env="prd" and app="efg")), app)'
nn, kv = parseQueryData(str1)
print(nn)
print(kv)