Abstract:
Approaches are disclosed for distributing messages across multiple data centers where the data centers do not store messages using a same message queue protocol. In some embodiment, a network element translates messages from a message queue protocol (e.g., Kestrel, RABBITMQ, APACHE Kafka, and ACTIVEMQ) to an application layer messaging protocol (e.g., XMPP, MQTT, WebSocket protocol, or other application layer messaging protocols). In other embodiments, a network element translates messages from an application layer messaging protocol to a message queue protocol. Using the new approaches disclosed herein, data centers communicate using, at least in part, application layer messaging protocols to disconnect the message queue protocols used by the data centers and enable sharing messages between messages queues in the data centers. Consequently, the data centers can share messages regardless of whether the underlying message queue protocols used by the data centers (and the network devices therein) are compatible with one another.
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:
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:
There is disclosed in an example a computer-implemented method of providing automated log analysis, including: receiving a log stream comprising a plurality of transaction log entries, the log entries comprising a time stamp, a component identification (ID), and a name value pair identifying a transaction; creating an index comprising mapping a key ID to a name value pair of a log entry; and selecting from the index a key ID having a relatively large number of repetitions. There is also disclosed an apparatus and computer-readable medium for performing the method.
Abstract:
There is disclosed in an example a computer-implemented method of providing automated log analysis, including: receiving a log stream comprising a plurality of transaction log entries, the log entries comprising a time stamp, a component identification (ID), and a name value pair identifying a transaction; creating an index comprising mapping a key ID to a name value pair of a log entry; and selecting from the index a key ID having a relatively large number of repetitions. There is also disclosed an apparatus and computer-readable medium for performing the method.
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:
Approaches are disclosed for distributing messages across multiple data centers where the data centers do not store messages using a same message queue protocol. In some embodiment, a network element translates messages from a message queue protocol (e.g., Kestrel, RABBITMQ, APACHE Kafka, and ACTIVEMQ) to an application layer messaging protocol (e.g., XMPP, MQTT, WebSocket protocol, or other application layer messaging protocols). In other embodiments, a network element translates messages from an application layer messaging protocol to a message queue protocol. Using the new approaches disclosed herein, data centers communicate using, at least in part, application layer messaging protocols to disconnect the message queue protocols used by the data centers and enable sharing messages between messages queues in the data centers. Consequently, the data centers can share messages regardless of whether the underlying message queue protocols used by the data centers (and the network devices therein) are compatible with one another.
Abstract:
Approaches are disclosed for distributing messages across multiple data centers where the data centers do not store messages using a same message queue protocol. In some embodiment, a network element translates messages from a message queue protocol (e.g., Kestrel, RABBITMQ, APACHE Kafka, and ACTIVEMQ) to an application layer messaging protocol (e.g., XMPP, MQTT, WebSocket protocol, or other application layer messaging protocols). In other embodiments, a network element translates messages from an application layer messaging protocol to a message queue protocol. Using the new approaches disclosed herein, data centers communicate using, at least in part, application layer messaging protocols to disconnect the message queue protocols used by the data centers and enable sharing messages between messages queues in the data centers. Consequently, the data centers can share messages regardless of whether the underlying message queue protocols used by the data centers (and the network devices therein) are compatible with one another.
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:
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.