Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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 ontology based resource provisioning and management for services. For example, such an ontology based approach can be utilized in conjunction with a business support system which may be employed in conjunction with a cloud computing environment.

Abstract: A service catalog may be stored on a storage device and represent systems management tools with types, managed component types the systems management tools can manage, and dependencies associated with the systems management tools. A portal comprises a user interface receiving a request for a systems management tool from the service catalog. A configuration management database stores registered state of the systems management tools and the managed components managed by the systems management tools. An orchestration component is capable of coupling a computer-executable plugin to activate, deactivate, and run the systems management tool on a managed component.