Abstract: A dataflow controller technology. A dataflow execution graph (such as a directed acyclic graph) receives or is to receive one or more data streams for processing. The control of the dataflow execution graph is performed by a set of one or more dataflow controllers that are dedicated to that dataflow execution graph. Each dataflow execution graph is instantiated and assigned to the dataflow execution graph such that the assignment results in the dataflow controller executing dataflow control functions for that dataflow execution graph. By dedicating controller(s) to only one dataflow execution graph, the risk of failure of the controller is bound to a single dataflow execution graph.

Abstract: At least some embodiments described herein relate to the automatic tuning of a dataflow execution graph. Such dataflow execution graphs are often used to execute some processing against a stream of data messages. A performance parameter of the dataflow execution graph is monitored, and compared against a service level objective. Based on the comparison, it is automatically decided whether a configuration of the dataflow execution graph should be changed. If a change is decided to be made, the configuration of the dataflow execution graph is altered. Thus, rather than require explicit instructions to change the configuration of a dataflow execution graph, the configuration of a dataflow execution graph is changed (or tuned) depending on compliance of performance with a service level objective.

Abstract: Disclosed herein is a system and method for generating an enhanced index for documents contained in a knowledge base. Documents or configuration snapshots are tokenized and then passed through a number of filters. The filters modify the token stream to generate an enhanced token stream for the document by removing words from the stream and adding domain level knowledge to the tokens in the stream. The token stream is then added to the index for the document so that searches can be completed against the knowledge base when searches are generated from configuration snapshots or from inputted search queries.

Abstract: Mechanisms to modify a dataflow execution graph that processes a data stream. An intermediate dataflow execution graph is used during modification of the dataflow execution graph from one configuration (the old dataflow execution graph) to the next (the new dataflow execution graph). Data messages of the data stream may continue to feed into the intermediate dataflow execution graph, thereby reducing latency and maintaining throughput during reconfiguration of the dataflow execution graph. Control message(s) that are structured to accomplish the reconfiguration is/are also passed into the intermediate dataflow execution graph during reconfiguration. As the control message(s) are all processed by the intermediate dataflow execution graph, the intermediate dataflow execution graph assumes the topology of the new dataflow execution graph.

Abstract: When a computing device has an issue, a detector receives (or retrieves) data associated with the computing device. The data may include parameter key-value pairs. The detector creates queries based on the data and distributes the queries to one or more matching engines, such as an exact matching engine or a proximity matching engine. The one or more matching engines look for matches in an index of database documents. The results from the one or more matching engines are ranked based on relevancy scores. In some cases, users may provide feedback regarding the relevancy of the results and the feedback may be used to recalibrate how the relevancy scores are determined.

Abstract: Described herein are various technologies pertaining to providing assistance to an operator in a data center with respect to failures in the data center. An alarm is received, and a failing device is identified based upon content of the alarm. Failure conditions of the alarm are mapped to a failure symptom that may be exhibited by the failing device, and troubleshooting options previously employed to mitigate the failure symptom are retrieved from historical data. Labels are respectively assigned to the troubleshooting options, where a label is indicative of a probability that a troubleshooting option to which the label has been assigned will mitigate the failure symptom.

Abstract: Described herein are various technologies pertaining to providing assistance to an operator in a data center with respect to failures in the data center. An alarm is received, and a failing device is identified based upon content of the alarm. Failure conditions of the alarm are mapped to a failure symptom that may be exhibited by the failing device, and troubleshooting options previously employed to mitigate the failure symptom are retrieved from historical data. Labels are respectively assigned to the troubleshooting options, where a label is indicative of a probability that a troubleshooting option to which the label has been assigned will mitigate the failure symptom.

Abstract: A hierarchical network analytics system operated by a computing device or system is described. In some example techniques, the analytics system may determine results of a plurality of first level analyses each based at least in part on results of a respective plurality of data queries that return respective subsets of a plurality of types of network data. The analytics system may determine a result of a second level analysis based at least in part on results of the plurality of first level analyses.

Abstract: A hierarchical network analytics system operated by a computing device or system is described. In some example techniques, the analytics system may determine results of a plurality of first level analyses each based at least in part on results of a respective plurality of data queries that return respective subsets of a plurality of types of network data. The analytics system may determine a result of a second level analysis based at least in part on results of the plurality of first level analyses.

Abstract: Disclosed herein is a system and method for searching or processing queries for searching for documents contained in a domain specific knowledge base. The system takes a query and generates from the query a modified version of the query by passing the query through one or more filters in a query processor. The query processor adds or removes terms from the query. The query processor can add or recognize that two words that appear to be separate words actually identify a specific software entity or can determine that a number appearing in a query is not just a number but refers to a specific version or a number relevant to the specific problem.

Abstract: Disclosed herein is a system and method for generating an enhanced index for documents contained in a knowledge base. Documents or configuration snapshots are tokenized and then passed through a number of filters. The filters modify the token stream to generate an enhanced token stream for the document by removing words from the stream and adding domain level knowledge to the tokens in the stream. The token stream is then added to the index for the document so that searches can be completed against the knowledge base when searches are generated from configuration snapshots or from inputted search queries.

Abstract: Disclosed herein is a system and method for generating an enhanced index for documents contained in a knowledge base. Documents or configuration snapshots are tokenized and then passed through a number of filters. The filters modify the token stream to generate an enhanced token stream for the document by removing words from the stream and adding domain level knowledge to the tokens in the stream. The token stream is then added to the index for the document so that searches can be completed against the knowledge base when searches are generated from configuration snapshots or from inputted search queries.

Abstract: Aspects of the subject disclosure are directed towards automatically inferring the significant parts of bug reports, including by querying a knowledge base built by mining information from a large number of earlier bug reports. Common phrases in the earlier bug reports are filtered to provide a subset of phrases relevant to a bug domain, which are stored in the knowledge base and mapped to an ontology model of the knowledge base. When a new bug report is received for inference/analysis, the phrases therein are tagged based upon the ontology model, and the knowledge base queried with the tagged phrases to determine problems, activities and actions that are likely related to the new bug report.

Abstract: Disclosed herein is a system and method for taking a snapshot or input from a source and identifying appropriate documents in a knowledge base that are applicable to the input. The system identifies documents that are applicable to the query by identifying comparative features/statements found in the natural language text documents and evaluating those comparative features with the conditions of the input. When the conditions of the comparative features evaluate with the input conditions the document is considered a match. The system processes the documents through a value type filter to understand the mathematical equivalent of the comparative feature and uses this mathematical equivalent in the evaluation of the document and input.

Abstract: When a computing device has an issue, a detector receives (or retrieves) data associated with the computing device. The data may include parameter key-value pairs. The detector creates queries based on the data and distributes the queries to one or more matching engines, such as an exact matching engine or a proximity matching engine. The one or more matching engines look for matches in an index of database documents. The results from the one or more matching engines are ranked based on relevancy scores. In some cases, users may provide feedback regarding the relevancy of the results and the feedback may be used to recalibrate how the relevancy scores are determined.

Abstract: The described implementations relate to processing of electronic data. One implementation is manifest as a system that that can include an event analysis component and one or more processing devices configured to execute the event analysis component. The event analysis component can be configured to obtain events from event logs, the events reflecting failures by one or more network devices in one or more data centers and characterize a service level of an application or a network device based on the events. For example, the event analysis component can be configured to characterize the availability of an application based on one or more network stamps of the application.

Abstract: Disclosed herein is a system and method for taking a snapshot or input from a source and identifying appropriate documents in a knowledge base that are applicable to the input. The system identifies documents that are applicable to the query by identifying comparative features/statements found in the natural language text documents and evaluating those comparative features with the conditions of the input. When the conditions of the comparative features evaluate with the input conditions the document is considered a match. The system processes the documents through a value type filter to understand the mathematical equivalent of the comparative feature and uses this mathematical equivalent in the evaluation of the document and input.

Abstract: The discussion relates to middlebox reliability. One example can apply event filters to a dataset of middlebox error reports to separate redundant middlebox error reports from a remainder of the middlebox error reports of the dataset. The example can categorize the remainder of the middlebox error reports of the dataset by middlebox device type. The example can also generate a graphical user interface that conveys past reliability and predicted future reliability for an individual model of an individual middlebox device type.

Abstract: The described implementations relate to processing of electronic data. One implementation is manifested as a system that can include an inference engine and at least one processing device configured to execute the inference engine. The inference engine can be configured to perform automated detection of concepts expressed in failure logs that include unstructured data. For example, the inference engine can analyze text of support tickets or diary entries relating to troubleshooting of an electronic network to obtain concepts identifying problems, actions, or activities. The inference engine can also be configured to generate output that reflects the identified concepts, e.g., via a visualization or queryable programming interface.

Abstract: Described herein are various technologies pertaining to providing assistance to an operator in a data center with respect to failures in the data center. An alarm is received, and a failing device is identified based upon content of the alarm. Failure conditions of the alarm are mapped to a failure symptom that may be exhibited by the failing device, and troubleshooting options previously employed to mitigate the failure symptom are retrieved from historical data. Labels are respectively assigned to the troubleshooting options, where a label is indicative of a probability that a troubleshooting option to which the label has been assigned will mitigate the failure symptom.