[7.13] [ML] prevent accidentally asking for more resources when scaling down and improve scaling size estimations (#74691) #74782
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… and improve scaling size estimations (elastic#74691) This commit addresses two problems: - Our memory estimations are not very exact. Consequently, its possible to request for too much or too little by a handful of KBs, while this is not a large issue in ESS, for custom tier sizes, it may be. - When scaling down, it was possible that part of the scale down was actually a scale up! This was due to some floating point rounding errors and poor estimations. Even though are estimations are better, it is best to NOT request higher resources in a scale down, no matter what. One of the ways we improve the calculation is during JVM size calculations. Instead of having the knot point be `2gb` it has been changed to `1.2gb`. This accounts for the "window of uncertainty" for JVM sizes. closes: elastic#74709
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Pinging @elastic/ml-core (Team:ML) |
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run elasticsearch-ci/part-2 |
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Backports the following commits to 7.13: