Abstract: Affinity based hierarchical container scheduling is disclosed. For example, a hierarchical map identifies relationships between a plurality of nodes and hardware devices, subzones, and zones. Affinity values of containers of a distributed service are measured, quantifying the containers' hierarchical relationship to other containers. A first affinity distribution of the distributed service is calculated based on affinity values, then used to calculate a first value of a performance metric of the distributed service. The value is iteratively adjusted by repeatedly: terminating and redeploying containers; measuring affinity values; calculating a new affinity distribution; and calculating a new value of the performance metric of the distributed service configured in the new affinity distribution, such that second and third values of the performance metric corresponding to second and third affinity distributions are calculated.

Abstract: Container deployment scheduling with constant time rejection request filtering is disclosed. For example, each node in a multi-node system includes system resources with available amounts quantitatively represented by values. An amplified label set with multiple labels representing each node is created. Labels are generated for first and second nodes, each label representing a system resource and a searchable value of the system resource of a node, searchable values being less than or equal to the value of the respective system resource. A hash value is generated for each label creating a hash filter. A scheduler filter receives a request to launch an isolated guest then generates a new hash value of system resource requirements of the isolated guest to query the hash filter thereby determining whether to submit the request to a scheduler based on a match between the new hash value and a hash value of the hash filter.