125 lines
3.5 KiB
Python
Executable File
125 lines
3.5 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright 2017 The Kubernetes Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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'''
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This script parses metrics from Cluster Autoscaler e2e tests.
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'''
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from __future__ import division
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from __future__ import print_function
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import argparse
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import json
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class CAMetric(object):
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def __init__(self, function_name):
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self.function_name = function_name
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self.sum = 0.0
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self.average = 0.0
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self.buckets = []
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self.count = 0
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self.upper_bound = 0.0
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def print(self):
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print(self.function_name, '\t', self.sum, '\t', self.count,'\t', self.avg,
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'\t', self.upper_bound)
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print(self.buckets)
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def print_summary(summary):
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print('function_name\t sum\t count\t avg\t upper_bound')
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print('buckets')
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for metric in summary.values():
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metric.print()
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def function_name(sample):
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return sample['metric']['function']
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def metric_value(sample):
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return sample['value'][1]
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def upper_bound(buckets):
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'''
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Going from the rightmost bucket, find the first one that has some samples
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and return its upper bound.
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'''
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for i in range(len(buckets) - 1, -1, -1):
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le, count = buckets[i]
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if i == 0:
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return le
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else:
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le_prev, count_prev = buckets[i-1]
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if count_prev < count:
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return le
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def parse_metrics_file(metrics_file):
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'''
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Return interesting metrics for all Cluster Autoscaler functions.
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Metrics are stored in a map keyed by function name and are expressed in
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seconds. They include
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* sum of all samples
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* count of sumples
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* average value of samples
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* upper bound - all collected samples were smaller than this value
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* buckets - list of tuples (# of samples, bucket upper bound)
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'''
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summary = {}
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with open(metrics_file) as metrics_file:
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summary = {}
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metrics = json.load(metrics_file)
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ca_metrics = metrics['ClusterAutoscalerMetrics']
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total_sum = ca_metrics['cluster_autoscaler_function_duration_seconds_sum']
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for sample in total_sum:
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function = function_name(sample)
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summary[function] = CAMetric(function)
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summary[function].sum = float(metric_value(sample))
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count = ca_metrics['cluster_autoscaler_function_duration_seconds_count']
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for sample in count:
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function = function_name(sample)
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summary[function].count = int(metric_value(sample))
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summary[function].avg = summary[function].sum / summary[function].count
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buckets = ca_metrics['cluster_autoscaler_function_duration_seconds_bucket']
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for sample in buckets:
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function = function_name(sample)
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summary[function].buckets.append(
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(float(sample['metric']['le']), int(metric_value(sample))))
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for value in summary.values():
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value.upper_bound = upper_bound(value.buckets)
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return summary
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def main():
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parser = argparse.ArgumentParser(description='Parse metrics from Cluster Autoscaler e2e test')
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parser.add_argument('metrics_file', help='File to read metrics from')
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args = parser.parse_args()
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summary = parse_metrics_file(args.metrics_file)
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print_summary(summary)
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if __name__ == '__main__':
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main()
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