A method, apparatus and computer program product for scheduling placement of containers in association with a set of hosts. The technique utilizes metrics that characterize container-specific risks. A first metric is a host interface risk for a container that quantifies how similar or dissimilar the container is relative to other containers running on a host. Preferably, host interface risk is derived with respect to a system call interface comprising a set of system calls, and the metric is based at least in part on a measure of dissimilarity among system calls. A second metric is a data sensitivity score that quantifies a degree to which sensitive data accesses are associated to the container. Based at least in part on the host interface risk scores and the data sensitivity scores, one or more containers are automatically scheduled for placement on the set of hosts to minimize security risk for the set of hosts.

A method of specifying behavior among a group of computing tasks included in a request to be performed in a domain of computing resources is disclosed. Method steps include receiving, at a scheduler operably coupled to the domain, a p/f request, the received p/f request including a first group and a first relationship, the first group comprising at least a first p/f group element and a second p/f group element, the first relationship defining a desired behavior of the first and second p/f group elements with respect to each other during performance of the p/f request; determining whether the domain includes available computing resources capable of satisfying the first relationship; and in response to a determination that the domain includes available computing resources capable of satisfying the first relationship, allocating, with the scheduler, at least one available computing resource to fulfill the p/f request.

Software performance can be automatically managed in a distributed computing environment. In one example, a system that can receive metrics information describing resource usage by a first instance of a service in a distributed computing environment. The system can also determine a quality-of-service (QoS) constraint for the service. The system can then modify a definition file based on the metrics information and the QoS constraint, the definition file being configured for deploying instances of the service in the distributed computing environment. The system can deploy a second instance of the service in the distributed computing environment using the modified definition file. As a result, the second instance can more closely satisfy the QoS constraint than the first instance.

Methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to implement and manage software defined silicon products are disclosed. Example semiconductor devices disclosed herein include circuitry configurable to provide one or more features. Disclosed example semiconductor devices also include a license processor to activate or deactivate at least one of the one or more features based on a license received via a network from a first remote enterprise system. Disclosed example semiconductor devices further include an analytics engine to report telemetry data associated with operation of the semiconductor device to at least one of the first remote enterprise system or a second remote enterprise system, the analytics engine to report the telemetry data in response to activation or deactivation of the at least one of the one or more features based on the license.

Techniques described herein relate to a method for composition for complex solutions. The method may include receiving, by a system control processor manager, a composition request to compose a composed information handling system, the request comprising a solution manifest file; parsing, by the system control processor manager, the solution manifest file to identify a solution requirement set; performing, using the solution requirement set, an analysis of a telemetry data map and a topology and connectivity graph; making a determination, based on the analysis, that the composition request may be satisfied using resources represented in the topology and connectivity graph; and composing the composed information handling system based on the determination.

Apparatuses, systems, and techniques to configure processor partitioning for a multi-process service. In at least one embodiment, a multi-process service configures a set of streaming multiprocessors of one or more parallel processing units to perform one or more threads in response to an application programming interface (API).

Methods and systems disclosed herein relate generally to evaluating resource loads to determine when to transform queues and to specific techniques for transforming at least part of queues so as to correspond to alternative resources.

A management system manages an infrastructure system configured to provide a resource for operating a business system and included a plurality of infrastructures with different architecture. The management system comprises a monitoring module configured to monitor a usage state of the resource of the business system; and an analysis module configured to identify a business system being a migration target. The analysis module is configured to: analyze a usage tendency of the resource of the business system, determine which of the infrastructures is appropriate for the business system, and store a result of determining as a first determination result; identify a target infrastructure, which is an infrastructure for which the resource is predicted to become insufficient; select a business system being the migration target from among business systems operating on the target infrastructure based on the first determination result; and migrate the selected business system.

A computer-implemented method according to one aspect includes identifying environmental information for a hyper-converged infrastructure (HCI) system; and adjusting one or more resources allocated to one or more applications within the HCI system, based on the environmental information.

A computer system that includes a plurality of compute clusters that are located at different geographical locations. Each compute cluster is powered by a local energy source at a geographical location of that compute cluster. Each local energy source has a pattern of energy supply that is variable over time based on an environmental factor. The computer system further includes a server system that executes a global scheduler that distributes virtual machines that perform compute tasks for server-executed software programs to the plurality of compute clusters of the distributed compute platform. To distribute virtual machines for a target server-executed software program, the global scheduler is configured to select a subset of compute clusters that have different complementary patterns of energy supply such that the subset of compute clusters aggregately provide a target compute resource availability for virtual machines for the target server-executed software program.