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https://issues.apache.org/jira/browse/AIRFLOW-3125?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16631191#comment-16631191
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ASF GitHub Bot commented on AIRFLOW-3125:
-----------------------------------------
mingyexia opened a new pull request #3966: [AIRFLOW-3125] Monitor Task
Instances creation rates
URL: https://github.com/apache/incubator-airflow/pull/3966
Make sure you have checked _all_ steps below.
### Jira
- [x] My PR addresses the following
[AIRFLOW-3125](https://issues.apache.org/jira/browse/AIRFLOW-3125)
### Description
- [x] Here are some details about my PR, including screenshots of any UI
changes:
Montor Task Instances creation rates by Operator type.
These stats can provide some visibility on how much workload Airflow is
getting. They can be used for resource allocation in the long run (i.e. to
determine when we should scale up workers) and debugging in scenarios like the
creation rate of certain type of Task Instances spikes.
### Tests
- [x] My PR adds the following unit tests __OR__ does not need testing for
this extremely good reason:
Just adding stats.
### Commits
- [x] My commits all reference Jira issues in their subject lines, and I
have squashed multiple commits if they address the same issue. In addition, my
commits follow the guidelines from "[How to write a good git commit
message](http://chris.beams.io/posts/git-commit/)":
1. Subject is separated from body by a blank line
1. Subject is limited to 50 characters (not including Jira issue reference)
1. Subject does not end with a period
1. Subject uses the imperative mood ("add", not "adding")
1. Body wraps at 72 characters
1. Body explains "what" and "why", not "how"
### Documentation
- [ ] In case of new functionality, my PR adds documentation that describes
how to use it.
- When adding new operators/hooks/sensors, the autoclass documentation
generation needs to be added.
### Code Quality
- [x] Passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
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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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