Add metrics correlation algorithm #3877

Naarcha-AWS · 2023-04-26T14:24:23Z

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dhrubo-os · 2023-04-26T19:03:32Z

_ml-commons-plugin/algorithms.md

+| Parameter | Type | Description | Default Value |
+|---|---|---|---|
+metrics | Integer | A list of metrics within the time series that can be correlated to anomalous behavior | N/A


input is a list of metrics. Every metrics is an array of numbers/float values.

A simplest example can be: {"metrics": [[1.0, 2.0, 3.0], [1.0, 2.0, 3.0]]}, here 2 metrics are provided and each metrics has 3 datapoints.

Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com>

_ml-commons-plugin/algorithms.md

greaa-aws · 2023-04-26T20:23:23Z

_ml-commons-plugin/algorithms.md

+
+1. For each metric, the input sequence has same T length.
+2. Before inputting, all input metrics should have the same corresponding set of timestamps.


"Before inputting" doesn't seem necessary here

greaa-aws · 2023-04-26T20:27:19Z

_ml-commons-plugin/algorithms.md

+{: .warning }
+
+The metrics correlation algorithm finds events in a set of metrics data. The algorithm defines events as a window in time where multiple metrics simultaneously display anomalous behavior. When given a time span and set of metrics, The algorithm correlates the number of events that occurred, when the event occurred, and determines which metrics were involved in each event.


Two minor notes here:

The algorithm is not given a time span, just a set of metrics.

"The algorithm correlates the number of events that occurred" is a little awkward. I would suggest "The algorithm automatically determines the number of events that occurred, when each event occurred, ..."

greaa-aws · 2023-04-26T20:30:20Z

_ml-commons-plugin/algorithms.md

+**Response**
+
+In the following example response, each item corresponds to an event discovered in the metrics data. The API returns the following information:


Should we add a line about the interpretation of this output? Basically:

The metrics correlation algorithm finds one event in this input data (indicated by the output list having length 1).

The event occurred between time points $t=52$ and $t=72$ (indicated by the "event window" field).

The event involved all three metrics (indicated by the "suspected metrics" field).

Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com>

dhrubo-os · 2023-04-26T21:16:03Z

_ml-commons-plugin/algorithms.md

+## Metrics correlation
+
+The metrics correlation feature is an experimental feature released in OpenSearch 2.7. It can't be used in a production environment. To leave feedback on improving the feature, leave an issue in the [ML Commons repository](https://github.com/opensearch-project/ml-commons).


Overall looks good to me. It can't be used in a production environment. seems bit unnecessary. Generally experimental feature means not ready for prod environment

_ml-commons-plugin/algorithms.md

Co-authored-by: Melissa Vagi <vagimeli@amazon.com> Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com>

natebower

@Naarcha-AWS Approved with noted comments and changes. Let me know if you have any questions. Thanks!

_ml-commons-plugin/algorithms.md

natebower · 2023-04-27T15:46:49Z

_ml-commons-plugin/algorithms.md

+{: .warning }
+
+The metrics correlation algorithm finds events in a set of metrics data. The algorithm defines events as a window in time where multiple metrics simultaneously display anomalous behavior. When given a set of metrics, the algorithm counts the number of events that occurred, when each event occurred, and determines which metrics were involved in each event.


Global: "metric data" instead of "metrics data"?

_ml-commons-plugin/algorithms.md

natebower · 2023-04-27T15:51:59Z

_ml-commons-plugin/algorithms.md

+- `suspected_metrics`: The set of metrics involved.
+
+In the following example response, each item corresponds to an event discovered in the metrics data. The algorithm finds one event in the input data of the request, as indicated by the output in `event_pattern` having a length of `1`.  `event_window` shows that the event occurred between time point $t$ = 52 and $t$ = 72. Lastly, the `suspected_metrics` shows that event involved all three metrics.


Add the noun after suspected_metrics. The suspected_metrics what?

Parameter. I removed the "the" here.

Co-authored-by: Nathan Bower <nbower@amazon.com> Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com>

* Add metrics correlation algorithm Signed-off-by: Naarcha-AWS <naarcha@amazon.com> * Update algorithms.md Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> * Update algorithms.md Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> * Update algorithms.md Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> * Update _ml-commons-plugin/algorithms.md Co-authored-by: Melissa Vagi <vagimeli@amazon.com> Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> * Update _ml-commons-plugin/algorithms.md Co-authored-by: Melissa Vagi <vagimeli@amazon.com> Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> * Update _ml-commons-plugin/algorithms.md Co-authored-by: Melissa Vagi <vagimeli@amazon.com> Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> * Update _ml-commons-plugin/algorithms.md Co-authored-by: Melissa Vagi <vagimeli@amazon.com> Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> * Apply suggestions from code review Co-authored-by: Nathan Bower <nbower@amazon.com> Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> --------- Signed-off-by: Naarcha-AWS <naarcha@amazon.com> Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> Co-authored-by: Melissa Vagi <vagimeli@amazon.com> Co-authored-by: Nathan Bower <nbower@amazon.com>

This reverts commit 2486b2a.

* Add metrics correlation algorithm Signed-off-by: Naarcha-AWS <naarcha@amazon.com> * Update algorithms.md Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> * Update algorithms.md Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> * Update algorithms.md Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> * Update _ml-commons-plugin/algorithms.md Co-authored-by: Melissa Vagi <vagimeli@amazon.com> Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> * Update _ml-commons-plugin/algorithms.md Co-authored-by: Melissa Vagi <vagimeli@amazon.com> Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> * Update _ml-commons-plugin/algorithms.md Co-authored-by: Melissa Vagi <vagimeli@amazon.com> Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> * Update _ml-commons-plugin/algorithms.md Co-authored-by: Melissa Vagi <vagimeli@amazon.com> Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> * Apply suggestions from code review Co-authored-by: Nathan Bower <nbower@amazon.com> Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> --------- Signed-off-by: Naarcha-AWS <naarcha@amazon.com> Signed-off-by: Naarcha-AWS <97990722+Naarcha-AWS@users.noreply.github.com> Co-authored-by: Melissa Vagi <vagimeli@amazon.com> Co-authored-by: Nathan Bower <nbower@amazon.com>

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Revert "Add metrics correlation algorithm (#3877)"

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This reverts commit 2486b2a.

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Add metrics correlation algorithm #3877

Add metrics correlation algorithm #3877

Naarcha-AWS commented Apr 26, 2023

dhrubo-os Apr 26, 2023

greaa-aws Apr 26, 2023

greaa-aws Apr 26, 2023

greaa-aws Apr 26, 2023

dhrubo-os Apr 26, 2023

natebower left a comment

natebower Apr 27, 2023

natebower Apr 27, 2023

Naarcha-AWS Apr 27, 2023


		1. For each metric, the input sequence has same T length.
		2. Before inputting, all input metrics should have the same corresponding set of timestamps.

		{: .warning }

		The metrics correlation algorithm finds events in a set of metrics data. The algorithm defines events as a window in time where multiple metrics simultaneously display anomalous behavior. When given a time span and set of metrics, The algorithm correlates the number of events that occurred, when the event occurred, and determines which metrics were involved in each event.

		Response

		In the following example response, each item corresponds to an event discovered in the metrics data. The API returns the following information:

		## Metrics correlation

		The metrics correlation feature is an experimental feature released in OpenSearch 2.7. It can't be used in a production environment. To leave feedback on improving the feature, leave an issue in the [ML Commons repository](https://github.com/opensearch-project/ml-commons).

		- `suspected_metrics`: The set of metrics involved.

		In the following example response, each item corresponds to an event discovered in the metrics data. The algorithm finds one event in the input data of the request, as indicated by the output in `event_pattern` having a length of `1`. `event_window` shows that the event occurred between time point $t$ = 52 and $t$ = 72. Lastly, the `suspected_metrics` shows that event involved all three metrics.

Add metrics correlation algorithm #3877

Add metrics correlation algorithm #3877

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Naarcha-AWS commented Apr 26, 2023

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