International Business Machines Corporation

Norman Christopher Böwing

Qais Noorshams

Pradeep Parameshwaran

Marco Selig

Simon Spinner

Dieter Wellerdiek

Juliet C Candee

Michael Groetzner

Horst Sinram

Anastasiia Didkovska

Tobias Huschle

Tobias Orth

Jason Matthew Stapels

Peter Klett

In an approach to optimizing dynamic system reconfiguration, a computer receives an active system configuration and a target system configuration from a system administrator, where the target system configuration includes two or more logical partitions. A computer determines one or more reconfiguration actions required to transform the active system configuration to the target system configuration. A computer generates a dependency graph based on the determined reconfiguration actions. A computer divides the dependency graph along the two or more logical partitions. A computer sorts the determined reconfiguration actions by associated dependencies. A computer orders the determined reconfiguration actions based on a priority of each of the two or more logical partitions. A computer runs a first simulation of the determined reconfiguration actions for each of the two or more logical partitions. A computer performs the determined reconfiguration actions for each of the two or more logical partitions.

Dynamic system reconfiguration by partition

A partition function is transferred from a source system to a multi-tenant target environment. The transfer is executed from a source system to a multi-tenant target environment. Physical and logical input/output (I/O) configuration settings of a partition image are separated on the source system, moving logical I/O configuration settings from the source system to a remote multi-tenant target environment. A dedicated target system of the remote multi-tenant target environment is selected. Physical information about hardware and connections of the dedicated target system are added to the logical I/O configuration settings. The logical I/O configuration settings combined with the physical information in the target system are activated. An operating system with the activated logical I/O configuration is started such that the partition function is transferred.

Transferring an operating image into a multi-tenant environment

A method for selectively generating suggested default values for I/O configurations is provided. The method identifies a first selection including a first input value for an I/O configuration. The method determines a set of remaining input options based on the first selection. The method accesses a set of decision trees based on the set of remaining input options and selects a decision tree of the set of decision trees based on the first input value. The method generates a suggested value for a subsequent selection for the I/O configuration and causes presentation of the suggested value and a user interface element representing the subsequent selection.

Selective enhancement of interactive configuration interfaces

An embodiment of the invention may include a method, computer program product, and computer system for reconfiguration of a computing environment from an as-is input/output (I/O) configuration to a to-be I/O configuration. An embodiment may include normalizing respective hierarchical models of the as-is and the to-be I/O configurations. The hierarchical models each comprise a hierarchical structure of leaf and non-leaf nodes. Normalizing comprises the application of syntactical transformation rules to the hierarchical models such that their respective I/O configurations are defined in a syntactically consistent manner. An embodiment may include creating respective hash tree representations of the first hierarchical model and the second hierarchical model. Nodes of the hash tree representations are checksum values. Nodes of the hash tree representations reflect the hierarchical structure of their respective hierarchical models. An embodiment may include pruning one or more nodes of the hash tree representations.

Selective pruning of a system configuration model for system reconfigurations

Proactively performing tasks based on estimating hardware reconfiguration times. A determination is made, prior to performing one or more reconfiguration actions to reconfigure a configuration of the computing environment, at least one estimated reconfiguration time to perform the one or more reconfiguration actions. At least one reconfiguration action of the one or more reconfiguration actions is performed, and one or more tasks are initiated prior to completing the one or more reconfiguration actions. The initiating is based on the at least one estimated reconfiguration time.

Proactively performing tasks based on estimating hardware reconfiguration times

Performance predictions in a computing cluster can be provided by sampling and storing historic workload request data of the computing cluster as time-stamped workload values, forecasting an expected total number of workload requests for a defined time interval in the future based on a time-series analysis of the time-stamped workload values, where the time-series analysis detects cyclic and repeating events in the time-stamped workload values. In response to a result of the time-series analysis, training a workload prediction model by using additional data about acyclic events in expected workload requests, where the training applies a statistical regression technique for predicting a future workload demand for the computing cluster, and in response to exceeding a predefined threshold value of the predicted future workload demand, reassigning resources of the computing cluster.

Workload management for computing cluster

A method for enhancing a workload manager for a computer system includes sampling and storing usage of a resource of the computer system as resource usage values, comparing said resource usage values with predetermined performance goal values, assigning a time-stamped priority value to an application that is running based on at least one of the performance goal values by the workload manager, retrieving a portion of the resource usage values and a related portion of the performance goal values for the application, identifying a future workload demand value by applying a time-series analysis algorithm to the resource usage values and the performance goal values for the application resulting in workload demand time frames and related amplitudes of the workload demand time frames, and adjusting a dispatch priority value for the application by setting a minimum dispatch priority for the application based on the future workload demand value.

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Boeblingen, Germany

Norman Christopher Böwing