Abstract: A technique of allocating shared resources in a computer network-based storage system comprises taking periodic performance samples on a running storage system; evaluating an objective function that takes as input the performance samples to quantify how aligned a current state of the storage system is with organizational objectives; building and maintaining models of behavior and capabilities of the storage system by using the performance samples as input; determining how resources of the storage system should be allocated among client computers in the storage system by selecting one among many possible allocations based on predictions generated by the models in order to maximize a value of the objective function; calculating a confidence statistic value for a chosen resource allocation based on an accuracy of the models; and enforcing the chosen resource allocation on the running storage system when the confidence statistic value is at or above a predetermined threshold value.

Abstract: Embodiments herein present a method, system, computer program product, etc. for automated management using a hybrid of prediction models and feedback-based systems. The method begins by calculating confidence values of models. Next, the method selects a first model based on the confidence values and processes the first model through a constraint solver to produce first workload throttling values. Following this, workloads are repeatedly processed through a feedback-based execution engine, wherein the feedback-based execution engine is controlled by the first workload throttling values. The first workload throttling values are applied incrementally to the feedback-based execution engine, during repetitions of the processing of the workloads, with a step-size that is proportional to the confidence values. The processing of the workloads is repeated until an objective function is maximized, wherein the objective function specifies performance goals of the workloads.

Abstract: Data is migrated by moving a set of the data in a data storage system of a computer system. The method includes monitoring a performance of at least one executing application while moving the data in the data storage system. A change in the rate of moving is calculated in response to the monitored performance of the executing application. The rate of moving is modified in accordance with the calculated change.

Abstract: A computer storage system includes a controller and a storage device array. The storage device array includes a first sub-array and a fast storage device sub-array. The first sub-array includes one or more log-structured storage devices storing data. The fast storage device sub-array includes one or more fast storage devices storing a copy of the data stored in the first sub-array.

Abstract: A computer storage system includes a controller and a storage device array. The storage device array includes a first sub-array and a fast storage device sub-array. The first sub-array includes one or more log-structured storage devices storing data. The fast storage device sub-array includes one or more fast storage devices storing a copy of the data stored in the first sub-array.

Abstract: A method and system for a migration executor of an on-line data migration engine is utilized to provide data migration of a user's data in a data storage system while maintaining application performance guarantees. In particular, the migration executor includes a monitor module configured to monitor performance metrics of a computer system executing foreground applications and the on-line data migration, where quality-of-service parameters computed from the performance metrics are forwarded to a controller module. The controller module of the migration executor is configured to compare the quality-of-service parameters of the computer system with performance goals for the foreground applications. The controller module may be further configured to issue commands to an actuator module that is configured to increase or decrease the rate of the data migration, where the actuator module is further configured to perform the data migration by executing a migration plan.