Managing Service Level Objectives for Storage Workloads

摘要

Described herein is a system and method for dynamically managing service-level objectives (SLOs) for workloads of a cluster storage system. Proposed states/solutions of the cluster may be produced and evaluated to select one that achieves the SLOs for each workload. A planner engine may produce a state tree comprising nodes, each node representing a proposed state/solution. New nodes may be added to the state tree based on new solution types that are permitted, or nodes may be removed based on a received time constraint for executing a proposed solution or a client certification of a solution. The planner engine may call an evaluation engine to evaluate proposed states, the evaluation engine using an evaluation function that considers SLO, cost, and optimization goal characteristics to produce a single evaluation value for each proposed state. The planner engine may call a modeler engine that is trained using machine learning techniques.

主权项

1. A system for evaluating a plurality of proposed states for a storage system that provides service to a plurality of workloads, the system comprising:
computer hardware configured for:
producing a state tree comprising a plurality of nodes arranged in a plurality of hierarchical levels comprising at least first and second levels, the first level comprising a start node representing a current state of the storage system, the second level comprising a plurality of proposed nodes, each proposed node representing a proposed state of the storage system produced by implementing a set of actions associated with the proposed state that changes the current state of the storage system to the proposed state, wherein the state tree is produced based on original planner information;receiving new planner information;adding at least one proposed node in the state tree based on the new planner information;removing at least one proposed node in the state tree based on the new planner information; andproducing a set of proposed nodes remaining in the state tree for selecting a proposed state to implement.