Abstract: Example techniques for adaptive time window-based log message deduplication are described. In an example, message values are obtained from received log messages. Further, the number of log messages received in a time window having a message value is counted. A log message from which the message value is obtained and the counted number are transmitted upon expiry of the time window. A length of a time window in which a subsequent counting of log messages is to be performed is determined based on various parameters.

Abstract: Example techniques for adaptive time window-based log message deduplication are described. In an example, message values are obtained from received log messages. Further, the number of log messages received in a time window having a message value is counted. A log message from which the message value is obtained and the counted number are transmitted upon expiry of the time window. A length of a time window in which a subsequent counting of log messages is to be performed is determined based on various parameters.

Abstract: End-to-end topology stitching and representation is described. An example includes instructions for receiving, at a server, a set of configuration data for an infrastructure stack, the set of configuration data including configuration data for each of a plurality of domains of the infrastructure stack; parsing the received set of configuration data; stitching together an end-to-end topology for the plurality of domains of the infrastructure stack based at least in part on the parsed set of configuration data; and generating a representation of the end-to-end topology of the infrastructure stack.

Abstract: Example techniques for adaptive time window-based log message deduplication are described. In an example, message values are obtained from received log messages. Further, the number of log messages received in a time window having a message value is counted. A log message from which the message value is obtained and the counted number are transmitted upon expiry of the time window. A length of a time window in which a subsequent counting of log messages is to be performed is determined based on various parameters.

Abstract: Example techniques for adaptive time window-based log message deduplication are described. In an example, message values are obtained from received log messages. Further, the number of log messages received in a time window having a message value is counted. A log message from which the message value is obtained and the counted number are transmitted upon expiry of the time window. A length of a time window in which a subsequent counting of log messages is to be performed is determined based on various parameters.

Abstract: Example techniques of data management in a network environment are described. In an example, a semantic pattern in a data stream transmitted from a source device to an edge device in the network environment is determined. The semantic pattern indicates relevance of data samples in the data stream for analysis of the data stream. The data stream is processed based on the semantic pattern, for storage and transmission in the network environment.

Abstract: Example aspects for transformation of video streams include searching for a first signature of a segment of a video stream in an index comprising a first level signature of each of a plurality of stored segments. In response to identifying a first set of similar segments from the stored segments, a second signature of the segment may be determined. In response to identifying a second set of similar segments from the first set of similar segments based on the second signature, a matching segment may be ascertained from the second set of similar segments. The matching segment may be provided for being stored in place of the segment in a storage medium.

Abstract: Example aspects for transformation of video streams include searching for a first signature of a segment of a video stream in an index comprising a first level signature of each of a plurality of stored segments. In response to identifying a first set of similar segments from the stored segments, a second signature of the segment may be determined. In response to identifying a second set of similar segments from the first set of similar segments based on the second signature, a matching segment may be ascertained from the second set of similar segments. The matching segment may be provided for being stored in place of the segment in a storage medium.

Abstract: Example techniques of data streaming between datacenters are described. In an example, a delta data may be replicated at a specific time interval from a first filesystem of a first stream-processing platform implemented at a first datacenter or source datacenter to a second filesystem of a second stream-processing platform implemented at a second datacenter or a target datacenter. The delta data indicates modifications to data of the data stream stored in the first filesystem, during the specific time interval.

Abstract: Example techniques of data management in a network environment are described. In an example, a semantic pattern in a data stream transmitted from a source device to an edge device in the network environment is determined. The semantic pattern indicates relevance of data samples in the data stream for analysis of the data stream. The data stream is processed based on the semantic pattern, for storage and transmission in the network environment.

Abstract: A method and system for a provisioning advisor are described which estimates the input/output operation performance of a workload on a storage system. A regression module in a provisioning advisor estimates a maximum IOPS on the storage system for buckets, or combinations of values, for various characteristics of the workloads running on the system by modeling a relationship between the workload characteristics and performance metrics gathered from the storage system. A performance module can use the estimated maximum IOPS for each bucket to update a set of working tables for the provisioning advisor, which can then be used to predict the input/output performance of a new workload to be provisioned on the storage system.

Abstract: A method and system for a provisioning advisor are described which estimates the input/output operation performance of a workload on a storage system. A regression module in a provisioning advisor estimates a maximum IOPS on the storage system for buckets, or combinations of values, for various characteristics of the workloads running on the system by modeling a relationship between the workload characteristics and performance metrics gathered from the storage system. A performance module can use the estimated maximum IOPS for each bucket to update a set of working tables for the provisioning advisor, which can then be used to predict the input/output performance of a new workload to be provisioned on the storage system.