International Business Machines Corporation

Tao Tao

Chang-Shing Perng

Anca Sailer

Thomas E Chefalas

Frank Andre Schaffa

Alla Segal

Ignacio Silva-Lepe

Jim Alain Laredo

Rahul P Akolkar

Rong Nickle Chang

Edward Cholchin So

Yexi Jiang

Chunqiang Tang

Fausto Bernardini

Chun Zhang

Yang Zhou

Karthik Rajagopal Gomadam

Perng Chang-shing

Hidayatullah Habeebullah Shaikh

Liangzhao Zeng

Salman Abdul Baset

Shu Tao

Meir M Laker

Bao Hua Dai

Mihwa Choi

Offline functionality-based co-ranking and clustering is carried out on a knowledge base that characterizes a heterogeneous information technology services network including a plurality of services, a plurality of providers, and a plurality of attributes. Results of the functionality-based co-ranking and clustering are stored as annotations of the services and the providers in the knowledge base, to obtain an annotated knowledge base. A service requirement is obtained from a customer requiring information technology services. The annotated knowledge base is queried, based on the service requirement; and an ordered list of at least given ones of the services, based on the querying, is returned to the customer.

Complex service network ranking and clustering

A method for providing a cloud-based service includes receiving information from a customer of the service over a conversational interface, the information identifying a requirement of the customer related to a resiliency of the service, and identifying a service provider who provides the service in a manner that satisfies the requirement. A method for building a knowledge base of cloud-based service providers includes receiving information from a service provider, the information specifying at least one resiliency attribute of the service provider, matching the information to a standardized service descriptor, wherein the service descriptor is indexed within an ontology-based organizational framework that indexes a plurality of service descriptors, and storing the service descriptor for the service provider.

Providing information technology resiliency in a cloud-based services marketplace

Automatically upgrading a computing environment system may include automatically identifying a set of timeframes and nodes running user applications on physical machines, containers, or virtual machines (VMs) whose disruption during the identified timeframes minimally impact the user applications. The timeframes may be intelligently determined by leveraging the monitoring data obtained automatically and/or the hints supplied by the user.

Automatic online system upgrade

A computer-implemented method for determining resources utilized by a service request in a data processing system. The method includes determining monitored relationship types from monitoring data, determining relationship domains, determining intra-domain relationships from relationships that are internal to the relationship domains and determining cross-domain relationships from the intra-domain relationships that are linked between pairs of the relationship domains, and determining resources utilized by the service request from the intra-domain and cross-domain relationships. The domains are derived from one of the relationship types that is monitored by a single monitoring application.

System and method for determining and optimizing resources of data processing system utilized by a service request

In an approach for creating a service composition, a processor receives a plurality of software modules, wherein each software module performs part of a service requested by one or more users on a network. A processor collects one or more attributes and one or more dependencies for each of the plurality of software modules. A processor appends information about the attributes and the dependencies to each respective software module. A processor stores each of the plurality of software modules with the respective appended information in a database. A processor creates a service composition comprised of a combination of the plurality of software modules, based on the appended information and the service requested by the one or more users on the network.

Refining composition instrumentation for services

A natural language specification of at least one high level information technology services requirement is obtained from a user, via a conversational interface; the same is parsed into first pre-defined semi-structured data, using a conversation parser. Based on the first pre-defined semi-structured data, a subset of candidate information technology services is identified, with a dialog engine, from a plurality of candidate information technology services provided by a plurality of vendors, the dialog engine is used to formulate a response including second pre-defined semi-structured data. The response is reverse-parsed into a natural language response, using the conversation parser. The natural language response includes a question for the user to assist in further refining the subset of candidate information technology services; the natural language response is presented to the user via the conversational interface.

Interactive acquisition of remote services

Systems and methods for custom-fitting a service solution to consumer requirements are provided. A method for custom-fitting a service solution to consumer requirements, comprises acquiring a request for the service solution from a consumer via a conversational interface, and issuing a query to a service knowledge base to obtain a set of service knowledge representation items from the service knowledge base and analyzing each service knowledge representation item to determine whether a custom-fit service solution can be developed.

System and method for custom-fitting services to consumer requirements

High level characteristics are extracted from a virtual machine provisioning request stream for a cloud computing environment. A plurality of prediction models are generated for a plurality of different types of virtual machines. A regression-correlation ensemble is applied to appropriate ones of the prediction models to predict future virtual machine demand for the cloud computing environment.

Cloud provisioning accelerator

System and method for determining and optimizing resources of a data processing system utilized by a service request

Checking health of information technology infrastructure based on log data, in one aspect, may collect log data non-intrusively from a production system, said log data at least associated with transactions occurring in the production system and resource utilization of the production system, may normalize said log data into a plurality of log data types, may perform data regression analysis using said plurality of log data types to estimate resources consumed by each of said transactions and throughput of each of said transactions, and may use a queuing model to predict performance of the information technology infrastructure under various workloads.

Healthcheck of information technology infrastructure based on log data

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Briarcliff Manor, NY, United States of America

Tao Tao