International Business Machines Corporation

Andrzej P Kochut

Hidayatullah Habeebullah Shaikh

Alexei A Karve

Michael Reuben Head

Anca Sailer

Yu Deng

Kirk Alan Beaty

Charles Otto Schulz

Jonathan Paul Munson

Murthy V Devarakonda

Rafah A Hosn

Randy Allan Rendahl

Rajdeep Bhowmik

Li Feng Zhang

Thomas E Chefalas

Parijat Dube

Junghwan Rhee

Alla Segal

Norman Bobroff

Anshul Gandhi

Ruchi Mahindru

Mahesh Viswanathan

Hui Lei

Clifford A Pickover

Komminist S Weldemariam

Sambit Sahu

Curtis E Hrischuk

Steven James Mastrianni

Ali Anwar

Angel E Tomala-Reyes

Naresh Nayar

Birgit Monika Pfitzmann

Danny Harnik

Minkyong Kim

Dmitry Sotnikov

Salman Abdul Baset

Ramesh Ambat Gopinath

Florian Graf

Han Chen

Zhe Zhang

Gautam Kar

Guo Ning Liu

Jayaram Kallapalayam Radhakrishnan

Daniel Dean

Zhiming Shen

Chun Feng Wu

Alexander P Amies

Kathiravan M Ramaswami

Deng Yu

Gunjan Khanna

Daniel Salinas

Yi Shuai Wang

Robin C Arnold

Reconstituting a machine image separates constituent parts of a machine image, and for each part, determines whether an exact version of the part is available on the target machine. If an exact version of the part is not available on the target machine, an inexact part is looked for on the target machine. Whether an inexact part is found may be determined based on attribute policy specification and similarity computation. For the inexact part found on the target machine, any dependencies may be identified and processed as a part to be reconstituted for the machine image. If no exact part and no inexact part are found on the target machine, the part is transferred from a source machine to the target machine. A machine image is created based on parts.

Inexact reconstitution of virtual machine images

A computer-implemented method includes receiving a template for creating a virtual machine (VM) instance; separating the template into a repeated portion and a unique portion; determining whether the repeated portion is stored in a cache; creating based on determining that the repeated portion is stored in the cache, the VM instance using the repeated portion stored in the cache; completing the unique portion of the VM instance to create a completed VM instance; and deploying the completed VM instance.

Expediting the provisioning of virtual machines based on cached repeated portions of a template

Systems and methods are provided for dynamic metering adjustment for service management of a computing platform. For example, a plurality of virtual machines are provisioned across a plurality of computing nodes of a computing platform. Data samples are collected for a metric that is monitored with regard to resource utilization in the computing platform by the virtual machines. The data samples are initially collected at a predefined sampling frequency. The data samples collected over time for the metric are analyzed to determine an amount of deviation in values of the collected data samples. A new sampling frequency is determined for collecting data samples for the metric based on the determined amount of deviation. The new sampling frequency is applied to collect data samples for the metric, wherein the new sampling frequency is less than the predefined sampling frequency.

Dynamic metering adjustment for service management of computing platform

A drone-based system determines a user cohort for one or more users to assemble an object. The drone-based system assesses a task for the one or more users to assemble the object. Based on the determined user cohort and the assessed task, a drone of the drone-based system provides help to the one or more users as the one or more users assemble the object. The drone-based system may comprise a drone and one or more memories and computer readable code and one or more processors. The one or more processors, in response to execution of the computer readable code, cause the drone-based system to perform operations. The drone-based system may be only the drone or the drone and one or more servers.

Drone and drone-based system and methods for helping users assemble an object

Methods and systems for data transfer include adding a data chunks to a priority queue in an order based on utilization priority. A reducibility score for the data chunks is determined. A data reduction operation is performed on a data chunk having a highest reducibility in the priority queue using a processor if sufficient resources are available. The data chunk having the lowest reducibility score is moved from the priority queue to a transfer queue for transmission if the transfer queue is not full.

Network utilization improvement by data reduction based migration prioritization

A method to generate executables for a business process execution language server includes: defining a process definition that defines a sequence of activities to be performed without specifying computer code used to implement the executables; binding each activity in the sequence to an action within a data type that is representative of a service associated with the corresponding activity; binding each data type to an instance of the corresponding data type that is representative of the service and a provider of the service; and generating the computer code based on the bindings.

Late binding composite service specification for business process execution language

Managing data in a cloud computing environment, including data transfers. File level and block level similarities are identified, including for archive and nested archive files, residing on datacenters and regional repositories. A replication plan is generated based on receiving a replication instruction, and further based on similarity clusters by transferring unique data blocks and files from best available sources including regional repositories.

Data synchronization using redundancy detection

A method to generate an executable orchestration process includes: querying a user to enter first computer code for activating a service; querying the user to enter second computer code for undoing actions performed in the activating; loading pre-defined third computer code for determining whether the activated service is a success or has an error, based on the service; loading pre-defined fourth computer code for correcting the error; generating an executable orchestration function from the first through fourth computer code; and generating the orchestration process from the executable orchestration function.

Orchestration process template for generation of orchestration process to tolerate errors

Systems and methods are provided to support service management in cloud computing networks. For example, a method for managing a computing platform includes provisioning a plurality of virtual machines across a plurality of computing nodes of a computing platform, wherein the provisioned virtual machines are configured to execute service workloads to provide one or more services to customers, and utilizing one or more of the provisioned virtual machines which execute the service workloads to further perform service management operations for managing the computing platform. The service management operations for managing the computing platform include, e.g., mediation and rating operations for revenue management of the computing platform.

Scalable metering for cloud service management based on cost-awareness

A computer-implemented method includes: receiving, by a computing device, a template for creating a virtual machine (VM) instance; separating, by the computing device, the template into a repeated portion and a unique portion; determining, by the computing device, whether the repeated portion is stored in a cache; creating, by the computing device and based on determining that the repeated portion is stored in the cache, the VM instance using the repeated portion stored in the cache; completing, by the computing device, the unique portion of the VM instance to create a completed VM instance; and deploying, by the computing device, the completed VM instance.

Techniques are disclosed for integration, provisioning and management of entities and processes in a computing system such as, by way of example only, business entities and business processes. In particular, techniques are disclosed for implementing an extensible support system for multiple service offerings. For example, such a support system can be a business support system which may be employed in conjunction with a cloud computing environment.

Extensible support system for service offerings

A computer executes a first version of a code module in a first test environment, collects a first set of execution measurements, and creates a first profile based on the first set of execution measurements. The computer executes the first version of the code module in a second test environment, collects a second set of execution measurements, and creates a second profile based on the second set of execution measurements. In response to a difference between the first profile and the second profile exceeding a threshold, the computer provides diagnostic data characterizing the difference, analyzes an impact of the difference on the execution of the code module, calculates a risk of code module failure value based on analyzing the impact of the difference, and provides a recommended action based on analyzing the impact of the difference and the calculated risk of code module failure value.

Early risk identification in DevOps environments

A method for scaling a cloud infrastructure, comprises receiving at least one of resource-level metrics and application-level metrics, estimating parameters of at least one application based on the received metrics, automatically and dynamically determining directives for scaling application deployment based on the estimated parameters, and providing the directives to a cloud service provider to execute the scaling.

Scaling a cloud infrastructure

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Croton-on-Hudson, NY, United States of America

Andrzej P Kochut