src/naarad/utils.py
def check_slas(metric):
  """
  Check if all SLAs pass
  :return: 0 (if all SLAs pass) or the number of SLAs failures
  """
  if not hasattr(metric, 'sla_map'):
    return
  for metric_label in metric.sla_map.keys():
    for sub_metric in metric.sla_map[metric_label].keys():
      for stat_name in metric.sla_map[metric_label][sub_metric].keys():
        sla = metric.sla_map[metric_label][sub_metric][stat_name]
        if stat_name[0] == 'p' and hasattr(metric, 'calculated_percentiles'):
          if sub_metric in metric.calculated_percentiles.keys():
            percentile_num = int(stat_name[1:])
            if isinstance(percentile_num, float) or isinstance(percentile_num, int):
              if percentile_num in metric.calculated_percentiles[sub_metric].keys():
                if not sla.check_sla_passed(metric.calculated_percentiles[sub_metric][percentile_num]):
                  logger.info("Failed SLA for " + sub_metric)
                  metric.status = CONSTANTS.SLA_FAILED
        if sub_metric in metric.calculated_stats.keys() and hasattr(metric, 'calculated_stats'):
          if stat_name in metric.calculated_stats[sub_metric].keys():
            if not sla.check_sla_passed(metric.calculated_stats[sub_metric][stat_name]):
              logger.info("Failed SLA for " + sub_metric)
              metric.status = CONSTANTS.SLA_FAILED
  # Save SLA results in a file
  if len(metric.sla_map.keys()) > 0 and hasattr(metric, 'get_sla_csv'):
    sla_csv_file = metric.get_sla_csv()
    with open(sla_csv_file, 'w') as FH:
      for metric_label in metric.sla_map.keys():
        for sub_metric in metric.sla_map[metric_label].keys():
          for stat, sla in metric.sla_map[metric_label][sub_metric].items():
            FH.write('%s\n' % (sla.get_csv_repr()))
def check_slas(metric):
  """
  Check if all SLAs pass
  :return: 0 (if all SLAs pass) or the number of SLAs failures
  """
  if not hasattr(metric, 'sla_map'):
    return
  for metric_label in metric.sla_map.keys():
    for sub_metric in metric.sla_map[metric_label].keys():
      for stat_name in metric.sla_map[metric_label][sub_metric].keys():
        sla = metric.sla_map[metric_label][sub_metric][stat_name]
        if stat_name[0] == 'p' and hasattr(metric, 'calculated_percentiles'):
          if sub_metric in metric.calculated_percentiles.keys():
            percentile_num = int(stat_name[1:])
            if isinstance(percentile_num, float) or isinstance(percentile_num, int):
              if percentile_num in metric.calculated_percentiles[sub_metric].keys():
                if not sla.check_sla_passed(metric.calculated_percentiles[sub_metric][percentile_num]):
                  logger.info("Failed SLA for " + sub_metric)
                  metric.status = CONSTANTS.SLA_FAILED
        if sub_metric in metric.calculated_stats.keys() and hasattr(metric, 'calculated_stats'):
          if stat_name in metric.calculated_stats[sub_metric].keys():
            if not sla.check_sla_passed(metric.calculated_stats[sub_metric][stat_name]):
              logger.info("Failed SLA for " + sub_metric)
              metric.status = CONSTANTS.SLA_FAILED
  # Save SLA results in a file
  if len(metric.sla_map.keys()) > 0 and hasattr(metric, 'get_sla_csv'):
    sla_csv_file = metric.get_sla_csv()
    with open(sla_csv_file, 'w') as FH:
      for metric_label in metric.sla_map.keys():
        for sub_metric in metric.sla_map[metric_label].keys():
          for stat, sla in metric.sla_map[metric_label][sub_metric].items():
            FH.write('%s\n' % (sla.get_csv_repr()))
def check_slas ( metric ) : if not hasattr ( metric , 'sla_map' ) : return for metric_label in metric . sla_map . keys ( ) : for sub_metric in metric . sla_map [ metric_label ] . keys ( ) : for stat_name in metric . sla_map [ metric_label ] [ sub_metric ] . keys ( ) : sla = metric . sla_map [ metric_label ] [ sub_metric ] [ stat_name ] if stat_name [ 0 ] == 'p' and hasattr ( metric , 'calculated_percentiles' ) : if sub_metric in metric . calculated_percentiles . keys ( ) : percentile_num = int ( stat_name [ 1 : ] ) if isinstance ( percentile_num , float ) or isinstance ( percentile_num , int ) : if percentile_num in metric . calculated_percentiles [ sub_metric ] . keys ( ) : if not sla . check_sla_passed ( metric . calculated_percentiles [ sub_metric ] [ percentile_num ] ) : logger . info ( "Failed SLA for " + sub_metric ) metric . status = CONSTANTS . SLA_FAILED if sub_metric in metric . calculated_stats . keys ( ) and hasattr ( metric , 'calculated_stats' ) : if stat_name in metric . calculated_stats [ sub_metric ] . keys ( ) : if not sla . check_sla_passed ( metric . calculated_stats [ sub_metric ] [ stat_name ] ) : logger . info ( "Failed SLA for " + sub_metric ) metric . status = CONSTANTS . SLA_FAILED # Save SLA results in a file if len ( metric . sla_map . keys ( ) ) > 0 and hasattr ( metric , 'get_sla_csv' ) : sla_csv_file = metric . get_sla_csv ( ) with open ( sla_csv_file , 'w' ) as FH : for metric_label in metric . sla_map . keys ( ) : for sub_metric in metric . sla_map [ metric_label ] . keys ( ) : for stat , sla in metric . sla_map [ metric_label ] [ sub_metric ] . items ( ) : FH . write ( '%s\n' % ( sla . get_csv_repr ( ) ) )
Check if all SLAs pass
  :return: 0 (if all SLAs pass) or the number of SLAs failures
Check if all SLAs pass : return : 0 ( if all SLAs pass ) or the number of SLAs failures