Abstract

Presented herein are techniques for machine-learning of leading indicators from a plurality of services and the use of these leading indicators to perform memory management operations on another plurality of services with correlating memory usage profiles. The techniques presented herein include collecting, as leading indicators, service event logs from a plurality of services. Machine-learning is then used to cross-correlate the leading indicators with memory use pattern snapshots at subsequent times for another plurality of services to predict the optimal when, how much, and how for execution of memory garbage collection on the latter set of services.

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Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

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