International Business Machines Corporation

Rakesh Jain

Ramani Ranjan Routray

Yang Song

Sumant Padbidri

Mu Qiao

Divyesh Jadav

John Jason Auvenshine

Stanley C Wood

James E Olson

Eric Kevin Butler

Chung-hao Tan

Pankaj S Bavishi

Jorge D Acuña

Dachuan Huang

Min Li

Sandeep Gopisetty

Sunhwan Lee

Thomas D Griffin

Luis Angel Bathen

Gabor Madl

Stephen Buckley

Embodiments of the invention are directed to a computer system that includes a memory electronically coupled to a processor system. The processor system is operable to perform processor system operations that include accessing a graph model representation of a computer network. The graph model is used to implement a resiliency-problem identification analysis that identifies a set of resiliency problems in the graph model. The graph model is used to apply a resiliency-problem solution analysis to a resiliency problem in the set of resiliency problems to generate a set of resiliency-problem solutions. Each resiliency-problem solution in the set of resiliency-problem solutions is ranked.

Data center resiliency recommender

An apparatus includes a cable having two ends and at least two object markers coupled to the cable configured to enable augmented reality (AR) detection of each end of the cable among a plurality of cables. A computer-implemented method using augmented reality (AR) technology includes selecting a cable of interest and identifying an object marker positioned toward a first end of the cable of interest. The method also includes storing the object marker, scanning a plurality of cables, and identifying a second end of the cable of interest based an instance of the object marker positioned toward the second end of the cable of interest. A computer program product for detecting ends of cables using augmented reality (AR) technology includes a computer readable storage medium having program instructions embodied therewith. The program instructions are executable by a computer to cause the computer to perform the foregoing method.

Identifying cable ends using augmented reality

A method, computer system, and a computer program for quick disaster recovery of cloud-native environments is provided. The present invention may include replicating at a secondary server site software executing in a cloud-native environment on a primary server site. The present invention may also include detecting a failure associated with the software executing in the cloud-native environment. The present invention may then include whether the detected failure is causing down time for the software executing in the cloud environment. The present invention may further include deploying the replicated software on the secondary server site in response to determining that the detected failure is causing down time.

Quick disaster recovery in distributed computing environment

Provided are a method, system and program for requesting storage performance models for a configuration pattern of storage resources to deploy at a client computing environment. A determination is made of a new configuration pattern of storage resources to deploy. A request is sent to a service provider with information on the new configuration pattern. A result set is received from the service provider having at least one provided configuration pattern having a degree of similarity to the new configuration pattern and a storage performance model for each of the provided configuration patterns. Each of the storage performance models indicate workload and performance characteristics for one of the provided configuration patterns. One of the provided configuration patterns is selected from the result set and the storage performance model for the selected configuration pattern is used to model performance at the client.

Requesting storage performance models for a configuration pattern of storage resources to deploy at a client computing environment

A computer-implemented method according to one embodiment includes receiving a data object from a first application running on a computing device, a unique identifier (ID) of the data object assigned by the first application, and an access permission for the data object from the first application. The computer-implemented method also includes storing the data object, the unique ID, and the access permission in a data repository in a data distributor layer on the computing device. The computer-implemented method also includes receiving, at an access controller layer of the computing device, a request for the data object from a second application, the request including the unique ID, and retrieving, by the access controller layer, the data object from the data distributor layer using the unique ID in response to the request. The computer-implemented method includes providing, by the access controller layer, the data object to the second application.

Adaptive on-device storage management across multiple applications

Provided are a method, system and program for publishing configuration patterns for storage resources and storage performance models from client systems to share with client systems in a network computing environment. A determination is made of a configuration pattern of storage resources within the client computing environment and storage performance metrics for the configuration pattern of storage resources within the client. At least one storage performance model is created based on the determined storage performance metrics. Information on the at least one storage performance model and the configuration pattern of the storage resources for which the storage performance metrics were determined are published to the service provider.

Publishing configuration patterns for storage resources and storage performance models from client systems to share with client systems in a network computing environment

An apparatus includes a cable having two ends and at least two object markers coupled to the cable configured to enable augmented reality (AR) detection of each end of the cable among a plurality of cables. A computer-implemented method using augmented reality (AR) technology includes selecting a cable of interest, identifying an object marker at a first end of the cable of interest, and storing the object marker. The method also includes scanning a plurality of cables, detecting a second instance of the object marker, and identifying a second end of the cable of interest based on the object marker. A computer program product for detecting ends of cables using augmented reality (AR) technology, includes a computer readable storage medium having program instructions embodied therewith. The program instructions executable by a computer to cause the computer to perform the foregoing method.

One embodiment provides a method for diagnosing data center incidents including receiving a data center incident report including information technology (IT) device incident information. Augmented reality (AR) is applied for an AR interface for receiving incident evidence information based on the IT device incident information. The incident evidence information is sent to a cognitive analytical process. Using the cognitive analytical process, statistical inference is determined and an incident diagnosis recommendation including analytical results is generated. The analytical results are received by the AR interface for determining a root cause of the incident report.

Diagnosis of data center incidents with augmented reality and cognitive analytics

A method and associated systems for a workload-aware thin-provisioning system that allocates physical storage to virtual resources from pools of physical storage volumes. The system receives constraints that limit the amount of storage that can be allocated from each pool and the total workload that can be directed to each pool. It also receives lists of previous workloads and allocations associated with each volume at specific times in the past. The system then predicts future workloads and allocation requirements for each volume by regressing linear equations derived from the received data. If the predicted values indicate that a pool will at a future time violate a received constraint, the system computes the minimum costs to move each volume of the offending pool to a less-burdened pool. It then selects the lowest-cost combination of volume and destination pool and then moves the selected volume to the selected pool.

Workload-aware storage-allocation system

Provided are a computer program product, method, and system for providing information on published configuration patterns of storage resources to client systems in a network computing environment. Published configuration patterns of storage resources and storage performance models for the published configuration patterns are received from the client systems and stored in a catalog. The published storage performance models are based on storage performance and workloads realized at the configuration patterns of the storage resources. A determination is made from the catalog of at least one published configuration pattern that is similar to a requested configuration pattern requested by a client system according to at least one storage attribute. A result set is generated indicating the determined at least one published configuration pattern and the storage performance model and sent to the requesting client system.

Providing information on published configuration patterns of storage resources to client systems in a network computing environment

Low-cost storage-allocation system

In one embodiment, a method includes determining a first set of similarity metrics for a first storage environment, the first set of similarity metrics being based on predetermined parameters related to the first storage environment, at least one of the predetermined parameters being relating to a redundancy of connections and devices in the first storage environment. In addition, the method includes obtaining a second set of similarity metrics for a second storage environment. Also, the method includes determining that the second storage environment is similar to the first storage environment by calculating a similarity measurement score between the sets of similarity metrics for the first and second storage environments. Moreover, the method includes re-aligning the first storage environment according to one or more identified aspects of the second storage environment that improve performance of the first storage environment.

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San Jose, CA, United States of America

Rakesh Jain