Abstract: Described herein are methods and a system for analyzing the impact of multiple components with one another that support a cloud service. Events are collected in time series from the components and aggregated in a relationship tree that groups the components. Propositions as to the events are created from which a conjunctive normal form (CNF) statement is derived. The CNF statement is converted to one or more directed acyclic graphs (DAG). The DAGs are traversed to determine TRUE values used to provide remediations solutions.

Abstract: Described herein are methods and a system for to optimize utilization of rack space supporting components of an existing client site rack. Real time data as to the rack space is collected, along with an objective function as to expansion. Information as to an initial design configuration is retrieved. A reinforcement learning algorithm processes real time data, the objective function, and initial design configuration to determine a deployment recommendation.

Abstract: Embodiments for handling configuration drift in a data storage system having a plurality of storage nodes. A configuration drift manager system defines a golden configuration dataset for the data storage system, obtains a current configuration dataset of each storage node of the plurality of storage nodes, each of the golden and configuration datasets comprising a plurality of sentences defining a node configuration parameter; determines a distance between each sentence of the golden configuration dataset with each other sentence of the current configuration datasets for each of the plurality of storage nodes; ranks each node based on a distance of its sentences with the golden configuration dataset, and triggers an action on a corresponding node based on its respective ranking.

Abstract: Network fabric design and analysis is generally a manual process where the wiring diagram is manually created and analyzed. Because of the complexity of modern network fabric designs, it has become increasingly more difficult to manually detect potential issues with a network fabric design. Accordingly, embodiments herein help automate the analysis of network fabric designs. In one or more embodiments, a trained neural network model or network models receive as input a wiring diagram and analyzes it. In one or more embodiments, the trained model may generate a real-valued score that represents the quality of the design. In one or more embodiments, the trained neural network may classify a particular issue or issues of the network fabric design.

Abstract: A board damage classification system includes a Convolutional Neural Network (CNN) sub-engine and a Graph Convolutional Network (GCN) sub-engine that were trained based on digital images of structures that have experienced natural disasters. The CNN sub-engine receives a board digital image of a board, analyzes the board digital image to identify board features, and determines a board feature damage classification for the board features. The CGN sub-engine receives a board feature graph that was generated using the board digital image and that includes nodes that correspond to the board features in the board digital image, and defines relationships between the nodes included in the board feature graph. The board feature damage classification determined by the CNN sub-engine and the relationships defined by the GCN sub-engine are then used to generate a board damage classification that includes a damage probability for board features in the board digital image.

Abstract: An apparatus comprises a processing device configured to select prioritization criteria for a plurality of virtual computing resources and to determine, for at least one criterion in the selected prioritization criteria, at least one directional correlation between the at least one criterion and at least one other criterion in the selected prioritization criteria. The processing device is also configured to generate a prioritization of the plurality of virtual computing resources utilizing a multi-criteria decision analysis algorithm. The multi-criteria decision analysis algorithm is based at least in part on the determined at least one directional correlation. The processing device is further configured to perform one or more scheduling operations for the plurality of virtual computing resources based at least in part on the generated prioritization of the plurality of virtual computing resources.

Abstract: A design of an infrastructure deployment is used for new deployments or as part of an addition to an existing deployment. Because of the complexity of modern infrastructure deployment designs, these designs are subject to a number of problems that are too complex and extensive for manual detection of potential issues. Furthermore, these infrastructure deployments are often critical infrastructure, which means their timely deployment and proper functioning are necessary. While improper design can cause functional problems, selection of an infrastructure element that suffers a supply chain delay so as to delay deployment can be as negatively impactful as a poor design. Accordingly, embodiments herein help automate the analysis of an infrastructure deployment design. In one or more embodiments, a trained neural network receives as input a design and analyzes it to classify a particular issue or issues of the design.

Abstract: Methods, systems, and devices for providing computer implemented services using managed systems are disclosed. To provide the computer implemented services, the managed systems may be deployed to a location and operate in a predetermined manner conducive to, for example, execution of applications that provide the computer implemented services. When deployed to a location, the managed systems may be housed in a managed system frame. The managed system frames may include systems to guide placement of managed system in preferred frame units, remotely identify occupancy of the frame units, and/or the frame units against unexpected removals of or insertion of devices in the frame units.

Abstract: Methods, systems, and devices for providing computer implemented services using managed systems are disclosed. To provide the computer implemented services, the managed systems may be deployed to a location and operate in a predetermined manner conducive to, for example, execution of applications that provide the computer implemented services. When deployed to a location, the managed systems may be housed in a managed system frame. The managed system frames may include systems to guide placement of managed system in preferred frame units, remotely identify occupancy of the frame units, and/or the frame units against unexpected removals of or insertion of devices in the frame units.

Abstract: Methods, systems, and devices for providing computer implemented services using managed systems are disclosed. To provide the computer implemented services, the managed systems may be deployed to a location and operate in a predetermined manner conducive to, for example, execution of applications that provide the computer implemented services. When deployed to a location, the managed systems may be housed in a managed system frame. The managed system frames may include systems to guide placement of managed system in preferred frame units, remotely identify occupancy of the frame units, and/or the frame units against unexpected removals of or insertion of devices in the frame units.

Abstract: Methods, systems, and devices for providing computer implemented services using managed systems are disclosed. To provide the computer implemented services, the managed systems may be deployed to a location and operate in a predetermined manner conducive to, for example, execution of applications that provide the computer implemented services. When deployed to a location, the managed systems may be housed in a managed system frame. The managed system frames may include systems to guide placement of managed system in preferred frame units, remotely identify occupancy of the frame units, and/or the frame units against unexpected removals of or insertion of devices in the frame units.

Abstract: Methods, systems, and devices for providing computer implemented services using managed systems are disclosed. To provide the computer implemented services, the managed systems may need to operate in a predetermined manner conducive to, for example, execution of applications that provide the computer implemented services. Similarly, the managed system may need access to certain hardware resources (e.g., and also software resources such as drivers, firmware, etc.) to provide the desired computer implemented services. To improve the likelihood of the computer implemented services being provided, the managed systems may be managed using a subscription based model. The subscription model may utilize a highly accessible service to facilitate system management. To facilitate system management, the highly available service may utilize various types of reporting models to identify use of the managed systems. The identified use may be used to drive management decisions.

Abstract: Methods, systems, and devices for providing computer implemented services using managed systems are disclosed. To provide the computer implemented services, the managed systems may need to operate in a predetermined manner conducive to, for example, execution of applications that provide the computer implemented services. Similarly, the managed system may need access to certain hardware resources and software resources to provide the desired computer implemented services. To improve the likelihood of the computer implemented services being provided, the managed devices may be managed using a subscription based model. The subscription model may utilize a highly accessible service to facilitate system management. To facilitate system management, the highly available service may take into account both historic use of managed systems and changes to subscriptions to ascertain point in time when subscription limits may be reached. The identified points in time may be used to drive management decisions.

Abstract: Described herein are systems and methods for neural machine translation (NMT) of languages between network operation systems. The languages may be a query language, such as a XML path, to navigate through elements and attributes in an XML document. An NMT model comprises an encoder and a decoder to implement the machine translation. The encoder encodes a source sentence as a sequence of encoder hidden states. The decoder may incorporate attention mechanism to generate a target sentence, conditioned on the encoder hidden states. The NMT model may also use a modified beam search with variable beam width and search scope for each search step to speed up search process with a balance of accuracy and processing cost. Evaluation results demonstrate that embodiments of the present disclosure may be used in a recommender system for XPath auto-generation between different network operation systems.

Abstract: Systems and methods for implementing a workload fairness policy at the data cache level within a non-volatile memory express solid-state drive utilizes a prioritization technique that predicts a degree of intensity for workloads based on a request generation rate. The degree of intensity is used to prioritize and rank workloads, thereby, avoiding interference between requests from each other.

Abstract: Security drift can be automatically handled in cloud environments. A security audit engine can be configured to extract security configuration datasets from cloud resources and create text sentences from the datasets as well as from a golden configuration. These text sentences can be encoded as vectors in an n-dimensional space. Probability distributions can then be generated using the vectors such as by using an unsupervised clustering algorithm. Distance matrixes can then be generated from the probability distributions. A probability distribution pertaining to a dataset and a probability distribution pertaining to the golden configuration can then be compared and normalized using a transport to thereby yield a security drift score representing a divergence of the corresponding security settings from the golden configuration. When a security drift score exceeds a threshold, the security audit engine can take appropriate action.

Abstract: Methods, systems, and devices for providing computer implemented services using managed systems are disclosed. To provide the computer implemented services, the managed systems and/or communication devices may need to operate in a predetermined manner conducive to, for example, execution of applications that provide the computer implemented services. To manage communications in such systems, a highly available service may, upon changes in topology of a deployment including managed system and communication devices, initiate a cooperative process for determining how to communicate in the deployment. The process may be performed to select a new global maximum transmission unit (MTU). Once selected, the deployment may be reconfigured based on the selected global MTU to limit the size of network data units. The global MTU may be selected to limit network data unit fragmentation, network data unit dropping, and unused space in data transmissions.

Abstract: A physical networking/virtual infrastructure management integration system includes a physical networking infrastructure management system providing physical networking infrastructure management subsystems, a virtual infrastructure management system providing virtual infrastructure management subsystems, and a network integration system. The network integration system identifies at least one affiliation between service endpoints provided by the physical networking infrastructure management subsystems and the virtual infrastructure management subsystems, and generates an affiliation graph that identifies each of the service endpoints and each affiliation between pairs of the service endpoints.

Abstract: An apparatus comprises a processing device configured to obtain workload traces characterizing resource execution metrics associated with workloads executing in an information technology infrastructure and to generate sets of workload causality profiles characterizing relationships between the resource execution metrics, the sets of workload causality profiles comprising first and at least second sets of workload causality profiles generated using first and at least second different types of models. The processing device is also configured to determine sets of causal topics comprising recurring patterns of the relationships between different ones of the resource execution metrics found in each of the sets of workload causality profiles. The processing device is further configured to identify clusters of causal topics each comprising at least one causal topic that is part of the first and second sets of causal topics, and to perform diagnosis of issues affecting the workloads based on the identified clusters.

Abstract: Presented herein are embodiments that use a language model to embed or encode configuration elements (e.g., commands, prompts, etc.) into dense, latent representations that incorporate semantic and contextual information. Using a trained language model, a configuration for a network device may be converted into a set of configuration path sentences. Given a first set of encoded configuration path sentences for a first configuration and a second set of encoded configuration path sentences for a second configuration, these two sets may be compared to gauge a degree of difference between the two sets. In one or more embodiments, an Optimal Transport method with Wasserstein distance metric may be used to obtain a comparison value that gauges difference between the two configurations. In one or more embodiments, the comparison valuation may be labeled or classified by comparing the comparison value to one or more pre-defined thresholds.