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2dc5586afe
The ML info endpoint returns the max_model_memory_limit setting if one is configured. However, it is still possible to create a job that cannot run anywhere in the current cluster because no node in the cluster has enough memory to accommodate it. This change adds an extra piece of information, limits.effective_max_model_memory_limit, to the ML info response that returns the biggest model memory limit that could be run in the current cluster assuming no other jobs were running. The idea is that the ML UI will be able to warn users who try to create jobs with higher model memory limits that their jobs will not be able to start unless they add a bigger ML node to their cluster. Backport of #55529
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