Abstract: The present disclosure describes a distributed, advertisement-based, solution for scheduling virtual resources in cloud infrastructures such as the OpenStack. The scheduling algorithm distributes the scheduling requirements and host state feasibility checks to the individual hosts in the datacenter, which can periodically send a summarized advertisement to the scheduler controller listing the number of instances of different type(s) of virtual resources that a particular host can support. The scheduler controller, thus no longer has to compute and maintain individual host states, and the scheduling problem is reduced to selecting the feasible advertisements that satisfy a given request. The solution can be extended to a scenario of multiple scheduler controllers using the same distributed, advertisement-based, approach.

Abstract: In one embodiment, a server in a network reports one or more symptoms of a monitored device that is malfunctioning to a user interface via a particular chatbot session. The server receives, via the particular chatbot session, a triage request to enter a triage mode regarding the one or more reported symptoms. The server predicts a corrective action using the one or more reported symptoms as input to a machine learning model. The machine learning model is trained using a history of observed symptoms in the network, a history of corrective actions initiated via chatbot sessions and associated with the observed symptoms, and a history of feedback regarding the corrective actions received via the chatbot sessions. The server provides the predicted corrective action to the user interface via the particular chatbot session as a suggested corrective action, in response to the received triage request.

Abstract: In one embodiment, a device in a network receives a first plurality of measurements for network metrics captured during a first time period. The device determines a first set of correlations between the network metrics using the first plurality of measurements captured during the first time period. The device receives a second plurality of measurements for the network metrics captured during a second time period. The device determines a second set of correlations between the network metrics using the second plurality of measurements captured during the second time period. The device identifies a difference between the first and second sets of correlations between the network metrics as a network anomaly.

Abstract: Approaches are disclosed for improving performance of logical disks. A logical disk can comprise several storage devices. In an object storage system (OSS), when a logical disk stores a file, fragments of the file are stored distributed across the storage devices. Each of the fragments of the file is asymmetrically stored in (write) and retrieved from (read) the storage devices. The performance of the logical disk is improved by reconfiguring one or more of the storage devices based on an influence that each of the storage devices has on performance of the logical disk and the asymmetric read and write operations of each of the storage devices. For example, latency of the logical disk can be reduced by reconfiguring one or more of the plurality of storage disks based on a proportion of the latency of the logical device that is attributable to each of the plurality of storage devices.

Abstract: The present disclosure describes a method for virtual machine placement optimization based on generalized organizational scenarios. The method involves defining a variable matrix (wherein each entry of the variable matrix indicate whether a particular virtual machine is to be placed on a particular host server), a first set of variables (wherein each variable of the first set of variables indicate whether a particular host server has at least one virtual machine to be placed thereon), a second set of variables (wherein the second set of variables indicates for all possible pairs of host servers whether two particular host servers both have at least one virtual machine to be placed thereon). The method further involves determining a set of virtual machine to host server allocations by solving a constraints optimization problem over the first set of variables and the second set of variables based on a generalized organizational scenario.

Abstract: Systems and methods are described for allocating resources in a cloud computing environment. The method includes receiving a computing request, the request for use of at least one virtual machine and a portion of memory. In response to the request, a plurality of hosts is identified and a cost function is formulated using at least a portion of those hosts. Based on the cost function, at least one host that is capable of hosting the virtual machine and memory is selected.

Abstract: A method for ranking detected anomalies is disclosed. The method includes generating a graph based on a plurality of rules, wherein the graph comprises nodes representing metrics identified in the rules, edges connecting nodes where metrics associated with connected nodes are identified in a given rule, and edge weights of the edges each representing a severity level assigned to the given rule. The method further includes ranking nodes of the graph based on the edge weights. The method further includes ranking detected anomalies based on the ranking of the nodes corresponding to the metrics associated with the detected anomalies.

Abstract: Systems and methods are described for allocating resources in a cloud computing environment. The method includes receiving a computing request, the request for use of at least one virtual machine and a portion of memory. In response to the request, a plurality of hosts is identified and a cost function is formulated using at least a portion of those hosts. Based on the cost function, at least one host that is capable of hosting the virtual machine and memory is selected.

Abstract: A method for summarizing capabilities in a hierarchically arranged data center includes receiving capabilities information, wherein the capabilities information is representative of capabilities of respective nodes at a first hierarchical level in the hierarchically arranged data center, clustering nodes based on groups of capabilities information, generating a histogram that represents individual node clusters, and sending the histogram to a next higher level in the hierarchically arranged data center. Relative rankings of capabilities may be used to order a sequence of clustering operations.

Abstract: The present disclosure describes a distributed, advertisement-based, solution for scheduling virtual resources in cloud infrastructures such as the OpenStack. The scheduling algorithm distributes the scheduling requirements and host state feasibility checks to the individual hosts in the datacenter, which can periodically send a summarized advertisement to the scheduler controller listing the number of instances of different type(s) of virtual resources that a particular host can support. The scheduler controller, thus no longer has to compute and maintain individual host states, and the scheduling problem is reduced to selecting the feasible advertisements that satisfy a given request. The solution can be extended to a scenario of multiple scheduler controllers using the same distributed, advertisement-based, approach.

Abstract: A method, apparatus, computer readable medium, and system that includes receiving an indication identifying a tunnel between a first virtual machine, associated with a first protocol, and a second virtual machine, associated with a second protocol, determining that the first protocol is different than the second protocol, determining at least one translation directive that specifies for translation between the first protocol and the second protocol for the tunnel, and causing establishment of a translator based, at least in part, on the translation directive is disclosed.

Abstract: Techniques are provided to generate and store a network graph database comprising information that indicates a service node topology, and virtual or physical network services available at each node in a network. A service request is received for services to be performed on packets traversing the network between at least first and second endpoints. A subset of the network graph database is determined that can provide the services requested in the service request. A service chain and service chain identifier is generated for the service based on the network graph database subset. A flow path is established through the service chain by flow programming network paths between the first and second endpoints using the service chain identifier.

Abstract: A method for assisting evaluation of anomalies in a distributed storage system is disclosed. The method includes a step of monitoring at least one system metric of the distributed storage system. The method further includes steps of maintaining a listing of patterns of the monitored system metric comprising patterns which previously did not result in a failure within one or more nodes of the distributed storage system, and, based on the monitoring, identifying a pattern (i.e., a time series motif) of the monitored system metric as a potential anomaly in the distributed storage system. The method also includes steps of automatically (i.e. without user input) performing a similarity search to determine whether the identified pattern satisfies one or more predefined similarity criteria with at least one pattern of the listing, and, upon positive determination, excepting the identified pattern from being identified as the potential anomaly.

Abstract: In one embodiment, a scale out policy service for processing a stream of messages includes a distributed stream processing computation system comprising distributed stream processing nodes, a distributed storage system, and a rules engine. A stream processing engine of the distributed stream processing computation system can receive the stream of messages comprising requests and/or events, and assign a first message to be processed by one or more distributed stream processing nodes based on one or more properties of the message. The one or more distributed stream processing nodes can be communicably connected to the distributed storage system and/or the rules engine to provide (1) an answer in response to the first message and/or (2) cause an action to be executed based on the first message.

Abstract: A method for assisting evaluation of anomalies in a distributed storage system is disclosed. The method includes a step of monitoring at least one system metric of the distributed storage system. The method further includes steps of maintaining a listing of patterns of the monitored system metric comprising patterns which previously did not result in a failure within one or more nodes of the distributed storage system, and, based on the monitoring, identifying a pattern (i.e., a time series motif) of the monitored system metric as a potential anomaly in the distributed storage system. The method also includes steps of automatically (i.e. without user input) performing a similarity search to determine whether the identified pattern satisfies one or more predefined similarity criteria with at least one pattern of the listing, and, upon positive determination, excepting the identified pattern from being identified as the potential anomaly.

Abstract: A method for assisting evaluation of anomalies in a distributed storage system is disclosed. The method includes monitoring at least one system metric of the system and creating a mapping between values and/or patterns of the system metric and one or more services configured to generate logs for the system. The method further includes detecting a potential anomaly in the system based on the monitoring, the potential anomaly being associated with a value and/or a pattern of the monitored system metric. The method also includes using the mapping to identify one or more logs associated with the potential anomaly, displaying a graphical representation of at least a part of monitoring the system metric, the graphical representation indicating the potential anomaly, and providing an overlay over the graphical representation, the overlay comprising an indicator of a number of the logs associated with the potential anomaly.

Abstract: A first network device determines capabilities of resources in a section of a network that is accessible using the first network device. The first network device groups the resources into a resource cluster. The first network device advertises the resource cluster in the network, wherein each of a plurality of network devices advertise a resource cluster associated with sections of the network. A second network device receives a request for providing a service. The second network device groups the request into a plurality of request clusters. The second network device selects at least one resource cluster for providing the service based on information associated with the request clusters and the advertised resource clusters. The second network device allocates resources included in the at least one resource cluster for providing the service based on selecting the at least one resource cluster.

Abstract: The present disclosure describes a method for virtual machine placement optimization based on generalized organizational scenarios. The method involves defining a variable matrix (wherein each entry of the variable matrix indicate whether a particular virtual machine is to be placed on a particular host server), a first set of variables (wherein each variable of the first set of variables indicate whether a particular host server has at least one virtual machine to be placed thereon), a second set of variables (wherein the second set of variables indicates for all possible pairs of host servers whether two particular host servers both have at least one virtual machine to be placed thereon). The method further involves determining a set of virtual machine to host server allocations by solving a constraints optimization problem over the first set of variables and the second set of variables based on a generalized organizational scenario.

Abstract: The present disclosure describes, among other things, a method for optimizing task scheduling in an optimally placed virtualized cluster using network cost optimizations. The method comprises computing a first network cost matrix for a plurality of available physical nodes, determining a first solution to a first optimization problem of virtual machine placement onto the plurality of available physical nodes based on the first network cost matrix, wherein the first solution comprises one or more optimally placed virtual machines, computing a second network cost matrix for allocating one or more tasks to one or more possible optimally placed virtual machines of the first solution, and determining a second solution to a second optimization problem of task allocation onto one or more possible optimally placed virtual machines of the first solution based on the second network cost matrix.

Abstract: The present disclosure describes, among other things, a method for managing and optimizing distributed object storage on a plurality of storage devices of a storage cluster. The method comprises computing, by a states engine, respective scores associated with the storage devices based on a set of characteristics associated with each storage device and a set of weights corresponding to the set of characteristics, and computing, by the states engine, respective bucket weights for leaf nodes and parent node(s) of a hierarchical map of the storage cluster based on the respective scores associated with the storage devices, wherein each leaf nodes represent a corresponding storage device and each parent node aggregates one or more storage devices.