International Business Machines Corporation

Anna Levin

Eran Raichstein

Katherine Barabash

Rami Cohen

Yaniv Ben-Itzhak

Amitabha Biswas

Liane Lewin-Eytan

Hani Talal Jamjoom

Elliot Karl Kolodner

Shriram Rajagopalan

Nimrod Megiddo

Shelly-Erika Garion

Machines, systems and methods for managing quality of service (QoS) in a multi-tenant virtualized computing environment, the method comprising: collecting transmission rate statistics associated with data communicated in a virtual network, wherein at least one virtual switch monitors communications initiated by at least a virtual machine (VM) executed on a host machine serviced by the virtual switch; determining, by way of the virtual switch, profile parameters associated with a first communication initiated by the VM belonging to at least a first group, wherein a connection request is submitted by the virtual switch to a traffic controller to assist in establishing the first communication; classifying the connection request for establishing the first communication according to the profile parameters associated with the first communication; determining a first aggregated transmission rate associated with the VM that initiated the first communication based on the classifying.

Bandwidth control in multi-tenant virtual networks

Embodiments of the present systems and methods may provide techniques for finding failing components in a distributed storage system. For example a method may comprise measuring problems and health of a plurality of physical and logical components in a distributed storage system, the plurality of physical and logical components forming nodes of the distributed storage system, and generating a graph of the nodes organized in a plurality of hierarchical levels, generating, for each node in the graph, a score summarizing the measured problems and health of the node, determining a highest score at a highest hierarchical level of the graph and determining the associated node as a failing component at a most significant level.

Method for finding failing components in a large distributed storage system connectivity

A method, computerized apparatus and a computer program product for anomaly detection in a distributed system. The method comprises obtaining measurements of metrics of the distributed system within a timeframe. Each measurement comprises a time-series of values to a metric associated with an action of a component of the distributed system that was measured within the timeframe. A set of percentiles of the measurements is computed, whereby a dimensionality of the sets of percentiles is larger than a dimensionality of the metrics. A multivariate anomaly detection is performed based on the weights of the percentiles to determine an anomaly in the sets of percentiles. In response to detecting an anomaly, a source of the anomaly is identified based on a subset of the percentiles having weights above a threshold, by determining common components or actions that are common to at least a portion of the subset of the percentiles.

Multivariate anomaly detection and identification

Embodiments of the present invention provide methods, computer program products, and systems for fulfilling a service chain request. Embodiments of the present invention can be used to collect network data of a plurality of instances of services and connections between the plurality of instances of services and redefine service chains to direct flow to an alternative instance of a service responsive to determining that an instance of a service in a service chain has become inaccessible. Embodiments of the present invention can be used to fulfill a service chain request and avoid one or more instances of services (and/or connections there between) that could cause a delay between transmitting data packets through the service chain.

Adaptive service chain management

A learning-based computer network security system may include a service delivery controller executing on one or more of hardware processors that receives requests for transmitting network flows to one or more destination machines via a communication network. The service delivery controller may group the network flows into one or more similarity groups, and direct the network flows in a particular similarity group to a learning-based security appliance instance designated for the particular similarity group. Based on receiving feedback from the security appliance instance, the service delivery controller may regroup the similarity groups, and/or redirect the network flows, and/or redistribute the training results between the appliances, and/or modify assignment of appliances to similarity groups.

Service delivery controller for learning network security services

A method includes converting, by a computer, a set of context-aware data forwarding policies to a set of network configuration forwarding rules for one or more data forwarding devices in a network having a dynamic context, and conveying, to the data forwarding devices, the set of network configuration forwarding rules. Upon detecting a change in the dynamic context of the network, the set of network configuration forwarding rules ae updated based on the set of context-aware data forwarding policies and the change in the dynamic context, and the updated set of network configuration forwarding rules are conveyed to the data forwarding devices.

Context-aware network service policy management

An approach is provided in which a local module receives a discovery message from a virtual network endpoint that is devoid of a corresponding virtual IP address. The local module sends one or more unicast network configuration messages to a dynamic configuration service and, in turn, the local module receives one or more unicast network configuration responses from the dynamic configuration service. One of the unicast network configuration responses includes one or more network configuration parameters. The local module configures the virtual network endpoint according to one or more of the network configuration parameters.

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Haifa, Israel

Anna Levin