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What's the data transformation story; for ML on metrics?

Coroot builds a model of each system, allowing it to traverse the dependency graph and identify correlations between metrics. On top of that, we're experimenting with LLMs for summarization — here are a few examples: https://oopsdb.coroot.com/failures/cpu-noisy-neighbor/

That looks like a built-in feature. I'm asking about extensibility. How do we use custom metrics transformations (libraries), for example?

Currently, you can define custom SLIs (Service Level Indicators, such as service latency or error rate) for each service using PromQL queries. In the future, you'll be able to define custom metrics for each application, including explanations of their meaning, so they can be leveraged in Root Cause Analysis

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