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TimeSeriesData<Usage> -> ResourceRecommendations
Calculate recommended Kubernetes container CPU and memory requests and limits from historical utilization time-series data using configurable statistical strategies (e.g., percentiles, max usage).
Problem it solves
Static resource allocations lead to either waste (over-provisioning) or performance degradation (under-provisioning).
Consumes
Emits
The real projects this mechanism was found in. Attribution is the point — this is how the best teams actually do it.