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https://issues.apache.org/jira/browse/AIRFLOW-3125?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16632138#comment-16632138
]
ASF GitHub Bot commented on AIRFLOW-3125:
-----------------------------------------
feng-tao closed pull request #3966: [AIRFLOW-3125] Monitor Task Instances
creation rates
URL: https://github.com/apache/incubator-airflow/pull/3966
This is a PR merged from a forked repository.
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diff --git a/airflow/models.py b/airflow/models.py
index e4a50bc476..9d1d64ee73 100755
--- a/airflow/models.py
+++ b/airflow/models.py
@@ -5282,6 +5282,9 @@ def verify_integrity(self, session=None):
continue
if task.task_id not in task_ids:
+ Stats.incr(
+ "task_instance_created-{}".format(task.__class__.__name__),
+ 1, 1)
ti = TaskInstance(task, self.execution_date)
session.add(ti)
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> Add monitoring on Task Instance creation rate
> ---------------------------------------------
>
> Key: AIRFLOW-3125
> URL: https://issues.apache.org/jira/browse/AIRFLOW-3125
> Project: Apache Airflow
> Issue Type: Improvement
> Reporter: Mingye Xia
> Assignee: Mingye Xia
> Priority: Major
>
> Monitoring on Task Instance creation rate can give us some visibility on how
> much workload we are putting on Airflow. It can be used for resource
> allocation in the long run (i.e. to determine when we should scale up
> workers) and and debugging in scenarios like creation rate for certain types
> of Task Instances spike.
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