fix metric family

exporter.py

@@ -75,7 +75,7 @@ class TencentExporter(Exporter):
                     with_factor_metric_family.add_metric(
                         ['{}*{}'.format(instance_name,rds_factor), instance_type, service_provider], 
                         value*rds_factor, timestamp)
-            metrics_to_export.extend([avg_metric_family, with_factor_metricname])
+            metrics_to_export.extend([avg_metric_family, with_factor_metric_family])
 
         return metrics_to_export
 
@@ -139,7 +139,6 @@ class AliyunExporter(Exporter):
         
             metrics_to_export.extend([avg_metric_family, max_metric_family, with_factor_metric_family])
 
-        print(metrics_to_export)
         return metrics_to_export
 
 if __name__ == "__main__":

main.py

@@ -6,76 +6,21 @@ import math
 
 import yaml
 from prometheus_client import start_http_server
-from prometheus_client.core import GaugeMetricFamily, REGISTRY
+from prometheus_client.core import REGISTRY
 
-from aliyun import CMS
-
-aliyun_cms = CMS()
-with open('config.yaml', 'r') as f:
-    config = yaml.load(f)
-
-# rds_instances = settings.RDS_INSTANCES
-rds_instances = config['rds_instances']
-queryname_metricname = config['metrics']
+from exporter import TencentExporter, AliyunExporter
 
 class RDSCollector(object):
+    def __init__(self):
+        self.exporter_list = [
+            TencentExporter(),
+            # AliyunExporter(),
+        ]
+
     def collect(self):
         metrics = []
-        # 阿里云SDK查询字段与prometheus metric name的映射
-        # queryname_metricname = {
-        #     'CpuUsage': 'rds_cpu_usage_ratio',
-        #     # 'DiskUsage': 'rds_disk_usage_ratio',
-        #     'MemoryUsage': 'rds_memory_usage_radio',
-        #     'ConnectionUsage': 'rds_connection_usage_radio',
-        #     'IOPSUsage': 'rds_iops_usage_radio',
-        # }
-        metrics_from_aliyun = {}
-        # all_rds_id = list(rds_instances.keys())
-        all_rds_id = rds_instances.keys()
-
-        # get metrics from aliyun
-        for label in queryname_metricname.keys():
-            metrics_from_aliyun[label] = []
-
-            for i in range(0, int(math.ceil(len(all_rds_id)/10.0))):
-                instance_id_list = all_rds_id[10*i : 10*(i+1)]
-                try:
-                    res = aliyun_cms.get_rds_metric(instance_id_list, label)
-                    metrics_from_aliyun[label].extend(res['Datapoints'])
-                except Exception as e:
-                    print(e)
-
-        # transform to prometheus metric format
-        for queryname, datapoints in metrics_from_aliyun.items():
-            metric = queryname_metricname[queryname]
-            metricname = metric['name']
-            factor = metric.get('factor', None)
-            avg_metric_family = GaugeMetricFamily(metricname, metricname,
-                    labels=['rds_name', 'type'])
-            max_metricname = '{}_max'.format(metricname)
-            max_metric_family = GaugeMetricFamily(max_metricname,
-                    max_metricname, labels=['rds_name', 'type'])
-            with_factor_metricname = '{}_with_factor'.format(metricname)
-            with_factor_metric_family = GaugeMetricFamily(with_factor_metricname, 
-                    with_factor_metricname, labels=['rds_name', 'type'])
-
-            for point in datapoints:
-                # rds_name = rds_instances[point['instanceId']]
-                rds = rds_instances[point['instanceId']]
-                rds_name = rds['name']
-                rds_type = rds.get('type', 'master')
-                # 当前queryname，当前rds实例的因子，若没有配置，默认为1
-                rds_factor = rds.get(factor, 1)
-                avg_metric_family.add_metric([rds_name, rds_type],
-                        point['Average']/100.0, point['timestamp']/1000)
-                max_metric_family.add_metric([rds_name, rds_type],
-                        point['Maximum']/100.0, point['timestamp']/1000)
-                with_factor_metric_family.add_metric(['{}*{}'.format(rds_name,rds_factor), rds_type],
-                        point['Average']*rds_factor/100.0, point['timestamp']/1000)
-
-            metrics.extend([avg_metric_family, max_metric_family,
-                with_factor_metric_family])
-
+        for exporter in self.exporter_list:
+            metrics.extend(exporter.export_prometheus_data())
         for m in metrics:
             yield m