algo: fix metric name fetching

traas-stack · Oct 27, 2023 · 41f3894 · 41f3894
1 parent 0d434da
commit 41f3894
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Showing 2 changed files with 4 additions and 11 deletions.
diff --git a/algorithm/kapacity/portrait/horizontal/predictive/main.py b/algorithm/kapacity/portrait/horizontal/predictive/main.py
@@ -196,11 +196,7 @@ def fetch_metrics_history(args, env, hp_cr):
                                                                   scale_target, start, end)
             metric_ctx.replicas_history = replica_history.rename(columns={'value': 'replicas'})
         else:
-            if metric_type == 'Object':
-                metric_name = metric['object']['metric']['name']
-            elif metric_type == 'External':
-                metric_name = metric['external']['metric']['name']
-            else:
+            if metric_type != 'Object' and metric_type != 'External':
                 raise RuntimeError('MetricTypeError')
             traffic_history = query.fetch_metrics(env.metrics_server_addr, env.namespace, metric, scale_target, start, end)
             metric_ctx.traffics_history_dict[metric_name] = traffic_history
@@ -215,7 +211,7 @@ def compute_resource_target(namespace, resource, scale_target):
     if target['type'] == 'Value':
         raise RuntimeError('UnsupportedResourceTargetType')
     elif target['type'] == 'AverageValue':
-        return target['averageValue']
+        return float(utils.parse_quantity(target['averageValue']))
     elif target['type'] == 'Utilization':
         return (target['averageUtilization'] / 100) * fetch_workload_pod_request(namespace, resource_name, scale_target)
 

diff --git a/algorithm/kapacity/timeseries/forecasting/train.py b/algorithm/kapacity/timeseries/forecasting/train.py
@@ -98,12 +98,9 @@ def fetch_history_metrics(args, target):
                                         metric=metric,
                                         start=start,
                                         end=end)
-        if metric['type'] == 'Object':
-            df_metric['metric'] = metric['object']['metric']['name']
-        elif metric['type'] == 'External':
-            df_metric['metric'] = metric['external']['metric']['name']
-        else:
+        if metric['type'] != 'Object' and metric['type'] != 'External':
             raise RuntimeError('UnsupportedMetricType')
+        df_metric['metric'] = metric['name']
         df_metric['workload'] = '%s/%s' % (workload_namespace, workload_name)
         df = pd.concat([df, df_metric])
     return df