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Decision taken in 3iab on 16 October 2024.
We don’t have any near-term plans to introduce support for Flink ML. However, we are going to bookmark your request for Python support and monitor future requests from other customers as well - as of today, we don't have enough customers pushing to traction this request.
This idea will be marked as "Not Under Consideration".
We have received an update to this idea from the AMEX team.
The EP team will be taking this up in the next 3iab for further discussion.
See response below
EVI-I-132 addresses AMEX’s need to identify single metric anomalies. However, we also need to identify anomalies associated with correlated multiple metrics (ex. Memory vs Response times). If Flink ML is not going to be supported, then we will need the capability to build our own custom operators in Python. We are currently testing multiple ML algorithms to determine which options actually work best with our data.
Within Event Processing we are focused on integrating with externally hosted ML models, where the models are running with tooling to monitor accuracy and drift - an important consideration when operationalising ML models. Flink ML is an extension to Flink is maturing, but doesn't currently make operationalising models easy, hence isn't part of our near term roadmap. Ideas has been marked as "Not Under Consideration."