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The output of the probable cause ranking should also have an "explainability UI" similar to that of temporal correlation and seasonality which explains why the events in a topological correlation were assigned their probable cause rankings accordingly. End users do not have any way to get further insight into how the probable cause ranking was calculated beyond the numbers that rank each event. Customers have questions about how and why the probable cause algorithms came to its conclusions. This is difficult for us to explain, and there is no explanation for this in the UI. Other AIOps tools on the market may provide a small text summary of the probable cause findings and the evidence for those findings. We need to include a feature like this or something similar for better usability and explainability of our models.
Idea priority | High |
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