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Post latency metrics whether or not tracker is configured #774

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Merged
merged 4 commits into from
Jan 21, 2020
Merged

Post latency metrics whether or not tracker is configured #774

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09ec668
Post latency metrics whether or not tracker is configured
deliahu Jan 21, 2020
a9ac8f0
Fix syntax error
deliahu Jan 21, 2020
3ae184a
Rename metrics_list
deliahu Jan 21, 2020
66ca6b9
Merge branch 'master' into metrics-fix
vishalbollu Jan 21, 2020
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15 changes: 8 additions & 7 deletions pkg/workloads/cortex/lib/type/api.py
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Original file line number Diff line number Diff line change
Expand Up @@ -64,20 +64,21 @@ def upload_class(self, class_name):
def metric_dimensions(self):
return [{"Name": "APIName", "Value": self.name}, {"Name": "APIID", "Value": self.id}]

def post_request_metrics(self, status_code, start_time, prediction_value=None):
metrics_list = []
metrics_list.append(self.status_code_metric(status_code))
def post_latency_metrics(self, status_code, start_time):
metrics = [self.status_code_metric(status_code), self.latency_metric(start_time)]
self.post_metrics(metrics)

def post_tracker_metrics(self, prediction_value=None):
if prediction_value is not None:
metrics_list.append(self.prediction_metrics(prediction_value))

metrics_list.append(self.latency_metric(start_time))
metrics = [self.prediction_metrics(prediction_value)]
self.post_metrics(metrics)

def post_metrics(self, metrics):
try:
if self.statsd is None:
raise CortexException("statsd client not initialized") # unexpected

for metric in metrics_list:
for metric in metrics:
tags = ["{}:{}".format(dim["Name"], dim["Value"]) for dim in metric["Dimensions"]]
if metric.get("Unit") == "Count":
self.statsd.increment(metric["MetricName"], value=metric["Value"], tags=tags)
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4 changes: 3 additions & 1 deletion pkg/workloads/cortex/serve/serve.py
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Original file line number Diff line number Diff line change
Expand Up @@ -120,9 +120,11 @@ def after_request(response):
prediction = g.prediction

try:
api.post_latency_metrics(response.status_code, g.start_time)

if api.tracker is not None:
predicted_value = api.tracker.extract_predicted_value(prediction)
api.post_request_metrics(response.status_code, g.start_time, predicted_value)
api.post_tracker_metrics(predicted_value)
if predicted_value is not None and predicted_value not in local_cache["class_set"]:
api.upload_class(predicted_value)
local_cache["class_set"].add(predicted_value)
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