International Business Machines Corporation

Kyndryl, Inc.

Gravitant, Inc.

Manish Mahesh Modh

Peter C Bahrs

Raphael P Chancey

Barry Alan Feigenbaum

Sean Michael Sundberg

Raghunath Sapuram

John Allen Hubert Woolfrey

Mohammed Farooq

Kishor Grandhe

Viktors Berstis

Robert W Erickson

Ilyas Mohamed Iyoob

Balaji Narasimhan

Sai Zeng

Emrah Zarifoglu

Braulio Gabriel Dumba

Matthew X Staffelbach

Kedar Dave

Umar Mohamed Iyoob

Liang Liu

Shikhar Kwatra

Donald A James

Jun Duan

Omar Odibat

Michael Wilfrid Brown

Sockalingam Radhakrishnan

Keri Wheatley

Murthy Lakshmana Mantha

Fenil Raj Kumar Santhi

Raghuram Krishnan

Zehra Yalcin

According to one embodiment, a method, computer system, and computer program product for provisioning a tag schema. The embodiment may include determining data types for tag-keys within an existing ecosystem of tags. Each tag of the existing ecosystem comprises a tag-key and a tag-value. The embodiment may include performing pairwise clustering of the tags within the ecosystem. The embodiment may include identifying a main tag-key within each cluster of tags. The embodiment may include grouping the clusters into a broader category. The embodiment may include providing a tag schema recommendation for the ecosystem based on the grouped clusters.

Automatically provisioned tag schema for hybrid multicloud cost and chargeback analysis

A machine learning assessment system is provided. The system identifies multiple datasets and multiple machine learning (ML) modeling algorithms based on the client profile. The system assesses a cost of data collection for each dataset of the multiple datasets. The system assesses a performance metric for each ML modeling algorithm of the multiple modeling algorithms. The system recommends a dataset from the multiple datasets and an ML modeling algorithm from the multiple ML modeling algorithm based on the assessed costs of data collection for the multiple datasets and the assessed performance metrics for the multiple ML modeling algorithms.

Efficiency driven data collection and machine learning modeling recommendation

A system, computer program product, and method to deriving a cost model and dynamic adjustment of the derived model responsive to dynamic modification of one or more of the resources in a hybrid shared resource environment. Resources and corresponding configuration information are collected while monitoring runtime utilization of resource performance. As changes to the resources are discovered, the changes are subject to an assessment. A hybrid cost model is derived and configured to account for the one or more resources. The derived hybrid cost model is leveraged to conduct a multi-dimensional resource evaluation of the assessed changed configuration information. Responsive to the multi-dimensional evaluation, a generated resource utilization optimization of the one or more resources is selectively implemented.

Resource and asset lifecycle costing

A method and system for operating an enterprise via an optimized business model. An output benchmark value is generated. An initial benchmark value for a resource of an enterprise is updated based on the output benchmark value. The business model is updated. A process is iteratively performed based on the updated benchmark value and model, until the benchmark value is changed by less than a predetermined threshold to generate the optimized business model. The enterprise is operated in accordance with the optimized model which includes: generating performance measures of usage of a computer resource, dynamically displaying a dashboard of the performance measures, determining from the displayed performance measures that the computer resource is a current bottleneck or is likely to become a bottleneck in the near future, and optimizing the computer resource's usage using the displayed performance measures to reduce data throughput delay and increase throughput of bottleneck operations.

Optimizing a business model of an enterprise

A method and system for operating an enterprise in accordance with an optimized enterprise level business model. A model optimization engine is iteratively processed based on an updated benchmark value and model, until updating the benchmark value involves changing the benchmark value by less than a predetermined benchmark value error threshold to generate the optimized enterprise-level business model. The enterprise is operated in accordance with the optimized enterprise level business model, including: generating and dynamically displaying real-time performance measures of usage of a computer resource during execution of a business process, determining from the performance measures that the computer resource is a bottleneck, and the computer resource's usage is optimized using the performance measures to reduce data throughput delay and increase throughput of bottleneck operations during execution of the business process. Optimizing the computer resource's usage includes making a computer system work more efficiently and/or use fewer resources.

A method and system for operating an enterprise in accordance with an optimized enterprise level business model. A model optimization engine is iteratively processed based on an updated benchmark value and model, until updating the benchmark value involves changing the benchmark value by less than a predetermined benchmark value error threshold to generate the optimized enterprise-level business model. The enterprise is operated in accordance with the optimized enterprise-level business model, including: generating and dynamically displaying real-time performance measures of usage of a computer resource during execution of a business process, determining from the performance measures that the computer resource is a bottleneck, and the computer resource's usage is optimized using the performance measures to reduce data throughput delay and increase throughput of bottleneck operations during execution of the business process. Optimizing the computer resource's usage includes making a computer system work more efficiently and/or use fewer resources.

A cloud services brokerage platform system includes a virtual data center (VDC) and an architecture management interface. The virtual data center (VDC) includes a plurality of resource groups. Each one of the resource groups includes one or more VDC resources. Each one of the VDC resources is associated with a respective set of resource group specification parameters. The architecture management interface enables an architectural layout of the one or more VDC resources to be displayed. The architectural layout includes a visual depiction of the one or more VDC resources of each one of the resource groups. An arrangement of the visual depiction is dependent upon the respective set of resource group specification parameters.

Creating, provisioning and managing virtual data centers

The present disclosure relates to methods and systems for developing, implementing, transforming, and governing a business model of an enterprise. In some embodiments, a method of implementing and managing a business model of an enterprise includes defining a business model using a business model tool that is executed by a computer, wherein the business model is based on interrelated business strategy, business goal and business constraint data, and includes a business service, inputting into the computer a first set of data representing a benchmark performance value of the business service, and operating the enterprise in accordance with the business model. The enterprise is monitored to determine an actual performance value of the business service, and the actual performance value and the benchmark performance value are processed in the computer to affect a comparison therebetween. The business model is modified based on the comparison.

Developing, implementing, transforming and governing a business model of an enterprise

Implementation of cross provider security in accordance with the disclosures made herein enables users of a system (e.g., a cloud services brokerage platform) in a cloud environment provides for system-managed provisioning and management of keys to cloud resources thereby allowing the user to manage data security and enable secured access to their cloud resources. To this end, cross provider security management functionality in accordance with the disclosures made herein can include provisioning system-generated keys across different regions in a provider, provisioning cloud brokerage system-generated keys across different providers; and associating (i.e., managing) the keys from the system to a hardware security module. The keys can be managed by/though a variety of different resources (e.g., brokering system, VDC, user group concepts, etc).

Cross provider security management functionality within a cloud service brokerage platform

A computer-implemented method of implementing comparison of cloud service provider package offerings comprises a plurality of operations. An operation of creating a cloud services architecture specification defining a cloud infrastructure that supports deployment of an application thereto is performed. An operation of determining a cloud services offering price for each one of the plurality of cloud service offerings to characterize implementation of the cloud infrastructure using cloud services thereof on a basis of pricing of such cloud services is performed. Determining the cloud services offering price for a particular one of the cloud service offerings includes mapping the cloud services architecture specification to cloud service pricing information for the particular one of the cloud service offerings.

Implementing comparison of cloud service provider package offerings

A system configured to facilitate brokering hybrid cloud services selects information requests for characterizing an information technology application. The system responses to the information requests and determines a plurality of sets of the responses each used for deriving a value of a respective one of a plurality of factor functions. The system determines a plurality of assessment results each derived using values for of a respective set of the factor functions. Each one of the assessment results characterizes a respective aspect of deploying the information technology application within a cloud environment.

Assessment of best fit cloud deployment infrastructures

A fulfillment bridge orchestrates various types of fulfillment that fall generally into three categories of fulfillment: CSB platform based automated provisioning; external automated provisioning; and manual workflow provisioning. External automated provisioning is implemented through fulfillment agents. The fulfillment agents can implements self-registration for allowing the fulfillment bridge to understand the capabilities of the fulfillment agent. Examples of such capabilities include, but are not limited to, supported actions and input/output parameters. Adapters of the fulfillment bridge interface with the fulfillment agents and fulfillment scripts that are independently operated with respect to the CSB platform can be use to interface with the fulfillment adapters.

Fulfillment of cloud service orders

A method, system and computer program product for accurately predicting capacity requirements for Information Technology (IT) resources in physical, virtual, cloud and hybrid cloud environments. The business demand is translated into IT application demand, which is translated into IT architecture layer demand. Resource groups are created for each IT application, IT architecture layer and resource type combination. The utilization for each IT resource group within the IT architecture layers is computed using the created resource groups, IT application demand and IT architecture layer demand. Under or over-utilized IT resource groups may be identified using the computed utilization for each IT resource group. Upon identifying such IT resources, an optimal resource profile (e.g., number of servers) for each resource group is computed. In this manner, the utilization of IT resources can be more accurately predicted thereby allowing the IT resources to be used more effectively without over-utilizing or underutilizing these resources.

Accurately predicting capacity requirements for information technology resources in physical, virtual and hybrid cloud environments

A method and apparatus in a data processing system for displaying a component or container. The container is displayed within a display using a first component. A location of the component or container is controlled within the display using a second component, wherein the second component controls the location and geometry of the component or container in response to receiving an event. The component or container is selectively displayed using a third component, wherein the third component generates the event.

Method and apparatus in a data processing system for systematically separating application graphical user interface component placement from component sequencing and compound creation

Growing community of inventors

Round Rock, TX, United States of America

Manish Mahesh Modh