def print_metrics()

in benchmarks/benchmark/tools/profile-generator/container/benchmark_serving.py [0:0]

• 58 lines of code
• 7 McCabe index (conditional complexity)

def print_metrics(metrics: List[str], duration: float, backend: str):
  # Creates a credentials object from the default service account file
  # Assumes that script has appropriate default credentials set up, ref:
  # https://googleapis.dev/python/google-auth/latest/user-guide.html#application-default-credentials
  credentials, project_id = google.auth.default()
  # Prepare an authentication request - helps format the request auth token
  auth_req = google.auth.transport.requests.Request()

  server_metrics = {}

  # Request refresh tokens
  credentials.refresh(auth_req)
  url='https://monitoring.googleapis.com/v1/projects/%s/location/global/prometheus/api/v1/metadata' % (project_id)
  headers_api = {'Authorization': 'Bearer ' + credentials.token}
  request_post = requests.get(url=url, headers=headers_api)
  all_metrics_metadata = request_post.json()
  if request_post.ok is not True:
    print("HTTP Error: %s" % (all_metrics_metadata))
  if all_metrics_metadata["status"] != "success":
    print("Metadata error response: %s" % all_metrics_metadata["error"])

  for metric in metrics:
    print("Metric Name: %s" % (metric))

    # Find metric type
    metric_type = all_metrics_metadata['data'][metric]
    if all_metrics_metadata['data'][metric] is None:
      print("No metric found for: %s" % metric)
      return
    metric_type = metric_type[0]['type']

    metric_results = {}
    # Queries scrape all metrics collected from the last $DURATION seconds from the backend's related
    # podmonitoring spec assumed to be named "$BACKEND-podmonitoring"
    queries = {
      "gauge": {
        "Mean": "avg_over_time(%s{job='%s-podmonitoring'}[%.0fs])" % (metric, backend, duration),
        "Median": "quantile_over_time(0.5, %s{job='%s-podmonitoring'}[%.0fs])" % (metric, backend, duration),
        "Sd": "stddev_over_time(%s{job='%s-podmonitoring'}[%.0fs])" % (metric, backend, duration),
        "Min": "min_over_time(%s{job='%s-podmonitoring'}[%.0fs])" % (metric, backend, duration),
        "Max": "max_over_time(%s{job='%s-podmonitoring'}[%.0fs])" % (metric, backend, duration),
        "P90": "quantile_over_time(0.9, %s{job='%s-podmonitoring'}[%.0fs])" % (metric, backend, duration),
        "P99": "quantile_over_time(0.99, %s{job='%s-podmonitoring'}[%.0fs])" % (metric, backend, duration),
    },
      "histogram": {
        "Mean": "sum(rate(%s_sum{job='%s-podmonitoring'}[%.0fs])) / sum(rate(%s_count{job='%s-podmonitoring'}[%.0fs]))" % (metric, backend, duration, metric, backend, duration),
        "Median": "histogram_quantile(0.5, sum(rate(%s_bucket{job='%s-podmonitoring'}[%.0fs])) by (le))" % (metric, backend, duration),
        "Min": "histogram_quantile(0, sum(rate(%s_bucket{job='%s-podmonitoring'}[%.0fs])) by (le))" % (metric, backend, duration),
        "Max": "histogram_quantile(1, sum(rate(%s_bucket{job='%s-podmonitoring'}[%.0fs])) by (le))" % (metric, backend, duration),
        "P90": "histogram_quantile(0.9, sum(rate(%s_bucket{job='%s-podmonitoring'}[%.0fs])) by (le))" % (metric, backend, duration),
        "P99": "histogram_quantile(0.99, sum(rate(%s_bucket{job='%s-podmonitoring'}[%.0fs])) by (le))" % (metric, backend, duration),
    }
  }
    for query_name, query in queries[metric_type].items():
      # Configure respective query
      url='https://monitoring.googleapis.com/v1/projects/%s/location/global/prometheus/api/v1/query' % (project_id)
      headers_api = {'Authorization': 'Bearer ' + credentials.token}
      params = {'query': query}
      print(f"Finding {query_name} {metric} with the following query: {query}")
      request_post = requests.get(url=url, headers=headers_api, params=params)
      response = request_post.json()

      print(f"Got response from metrics server: {response}")

      # handle response
      if request_post.ok:
        if response["status"] == "success":
          metric_results[query_name] = float(response["data"]["result"][0]["value"][1])
          print("%s: %s" % (query_name, response["data"]["result"][0]["value"][1]))
        else:
          print("Cloud Monitoring PromQL Error: %s" % (response["error"]))
      else:
        print("HTTP Error: %s" % (response))
    server_metrics[metric] = metric_results
  return server_metrics