Abstract: Systems and methods are described for intelligent software patch management. In an example, a system can receive a selection of device attributes. The system can associate a group of computing devices with attribute values that correspond to each device. The system can also create value pairs of unique pairs of values for each computing device. The system can select a set of computing devices for a deployment ring that maximizes diversity of the values or value pairs. The system can deploy the software patch to the selected devices and monitor device performance for a predetermined period of time before continuing to the next deployment ring or rolling back the update.

Abstract: An apparatus is provided for classifying content in one or more transactions. The apparatus includes a transaction boundary detector to detect boundaries of the one or more transactions associated with a first server or a first destination, wherein the one or more transactions include one or more requests from a client or a source and one or more corresponding responses from the first server or the first destination. A multimedia session generator generates a multimedia session object based on the detected boundaries of the one or more transactions. A multimedia classifier classifies the content associated with a first multimedia session. A traffic processing and policy enforcement unit applies traffic management to the first multimedia session based upon the classification.

Abstract: A system and method for facilitating management of cloud infrastructure by using smart bots is disclosed. The method includes obtaining one or more insights associated with one or more user accounts on a cloud infrastructure from one or more cloud infrastructure resources and determining one or more cloud infrastructure issues associated with the one or more user accounts by validating the obtained one or more insights based on a set of predefined rules. The method further includes creating one or more customized bots for the determined one or more cloud infrastructure issues based on one or more user parameters by using a rule engine based AI model and deploying the created one or more customized bots on the one or more cloud infrastructure resources. Further, the method includes managing the cloud infrastructure via the deployed one or more customized bots.

Abstract: An apparatus is provided for classifying content in one or more transactions. The apparatus includes a transaction boundary detector to detect boundaries of the one or more transactions associated with a first server or a first destination, wherein the one or more transactions include one or more requests from a client or a source and one or more corresponding responses from the first server or the first destination. A multimedia session generator generates a multimedia session object based on the detected boundaries of the one or more transactions. A multimedia classifier classifies the content associated with a first multimedia session. A traffic processing and policy enforcement unit applies traffic management to the first multimedia session based upon the classification.

Abstract: Systems and methods are described for intelligent software patch management. In an example, a system can receive a selection of device attributes. The system can associate a group of computing devices with attribute values that correspond to each device. The system can also create value pairs of unique pairs of values for each computing device. The system can select a set of computing devices for a deployment ring that maximizes diversity of the values or value pairs. The system can deploy the software patch to the selected devices and monitor device performance for a predetermined period of time before continuing to the next deployment ring or rolling back the update.

Abstract: Systems and methods are described for intelligent software patch management. In an example, a system can receive a selection of device attributes. The system can associate a group of computing devices with attribute values that correspond to each device. The system can also create value pairs of unique pairs of values for each computing device. The system can select a set of computing devices for a deployment ring that maximizes diversity of the values or value pairs. The system can deploy the software patch to the selected devices and monitor device performance for a predetermined period of time before continuing to the next deployment ring or rolling back the update.

Abstract: Systems and methods are described for intelligent software patch management. In an example, a system can receive a selection of device attributes. The system can associate a group of computing devices with attribute values that correspond to each device. The system can also create value pairs of unique pairs of values for each computing device. The system can select a set of computing devices for a deployment ring that maximizes diversity of the values or value pairs. The system can deploy the software patch to the selected devices and monitor device performance for a predetermined period of time before continuing to the next deployment ring or rolling back the update.

Abstract: A system and method for facilitating management of cloud infrastructure by using smart bots is disclosed. The method includes obtaining one or more insights associated with one or more user accounts on a cloud infrastructure from one or more cloud infrastructure resources and determining one or more cloud infrastructure issues associated with the one or more user accounts by validating the obtained one or more insights based on a set of predefined rules. The method further includes creating one or more customized bots for the determined one or more cloud infrastructure issues based on one or more user parameters by using a rule engine based AI model and deploying the created one or more customized bots on the one or more cloud infrastructure resources. Further, the method includes managing the cloud infrastructure via the deployed one or more customized bots.

Abstract: A system and method for facilitating management of application infrastructure for plurality of users is disclosed. The method includes identifying a set of infrastructure components corresponding to an application and determining configuration information associated with the application based on the set of infrastructure components. The method further includes identifying a plurality of patterns of the application based on the configuration information of the set of infrastructure components and generating one or more application fingerprints corresponding to the application based on the plurality of patterns. Further, the method includes determining one or more anomalies in the application based on the one or more application fingerprints and generating one or more recommendations for resolving the one or more anomalies based on the one or more application fingerprints and prestored information.

Abstract: An approach for continual learning in slowly-varying environments is provided. The approach receives one or more action requests from a decision agent. The approach deploys a first model to a decision engine. The approach initiates an observation period. The approach builds a second model, in which the second model comprises collected transaction data from the observation period. The approach initiates a test period. The approach determines a performance score for the first model and a performance score for the second model. The approach selects the model providing an optimized action.

Abstract: An apparatus is provided for estimating one or more quality of experience (QoE) parameters associated with a specific terminal. The apparatus includes a traffic processor configured to acquire a plurality of transactions for providing multimedia content to a specific terminal. At least one of such transactions is a secured transaction. The apparatus further includes a QoE parameter estimator configured to detect a quality level variation event based on the transactions and the sizes of the transactions, and to estimate one or more QoE parameters based on the detection of the quality level variation event.

Abstract: A system and method is provided for providing a composite Quality of Experience (QoE) metrics associated with a multimedia transmitted via a network. The method includes obtaining multimedia data corresponding to the multimedia transmitted via the network and acquiring metrics associated with the multimedia data. The metrics includes at least one multimedia transmitting metrics and at least one multimedia quality metrics. The method also includes normalizing the metrics and determining, based on the one or more normalized metrics, the composite multimedia QoE metrics.

Abstract: An apparatus is provided for detecting the presence of multimedia content in one or more transactions and for classifying the multimedia content in the one or more transactions. The apparatus can include a traffic processor configured to acquire one or more handshake messages associated with the transactions. The apparatus can also include a multimedia detector configured to determine a domain name requested by a specific terminal based on the one or more handshake messages, and to detect the presence of the multimedia content data in the transactions using the determined domain name. The detection of the presence of the multimedia content can be used for at least one of optimizing or reporting of the multimedia content before the multimedia content is provided to the specific terminal.

Abstract: An apparatus is provided for classifying content in one or more transactions. The apparatus includes a transaction boundary detector to detect boundaries of the one or more transactions associated with a first server or a first destination, wherein the one or more transactions include one or more requests from a client or a source and one or more corresponding responses from the first server or the first destination. A multimedia session generator generates a multimedia session object based on the detected boundaries of the one or more transactions. A multimedia classifier classifies the content associated with a first multimedia session. A traffic processing and policy enforcement unit applies traffic management to the first multimedia session based upon the classification.

Abstract: An apparatus is provided for classifying content in one or more transactions. The apparatus includes a transaction boundary detector configured to detect boundaries of the transactions associated with a first server or a first destination. The apparatus further includes a multimedia session generator configured to generate a multimedia session object based on the detected boundaries of the one or more transactions. The apparatus further includes a multimedia classifier configured to classify the content associated with a first multimedia session as being communicated under at least one of: HTTP live streaming (HLS) protocols, dynamic adaptive streaming over HTTP (DASH) protocols, adaptive bit rate protocols, progressive download protocols, or non-multimedia protocols.

Abstract: A system and method is provided for controlling multimedia data transmission to a communication device via a network. The system comprises a de-muxer configured to obtain a first multimedia data for transmission and a flow controller configured to evaluate an estimated buffer time associated with the communication device. If the estimated buffer time satisfies a first threshold condition, the flow controller updates a current transmitting state to be a pacing state. And if the estimated buffer time satisfies a second threshold condition, the flow controller updates the current transmitting state to be a bursting state. The system also comprises a muxer configured to transmit the first multimedia data at a transmitting rate corresponding to the bursting state or the pacing state.

Abstract: An apparatus is provided for estimating one or more quality of experience (QoE) parameters associated with a specific terminal. The apparatus includes a traffic processor configured to acquire a plurality of transactions for providing multimedia content to a specific terminal. At least one of such transactions is a secured transaction. The apparatus further includes a QoE parameter estimator configured to detect a quality level variation event based on the transactions and the sizes of the transactions, and to estimate one or more QoE parameters based on the detection of the quality level variation event.

Abstract: An apparatus is provided for estimating one or more quality of experience (QoE) parameters associated with a specific terminal. The apparatus includes a traffic processor configured to acquire a plurality of transactions for providing multimedia content to a specific terminal. At least one of such transactions is a secured transaction. The apparatus further includes a QoE parameter estimator configured to detect a quality level variation event based on the transactions and the sizes of the transactions, and to estimate one or more QoE parameters based on the detection of the quality level variation event.

Abstract: A system and method is provided for determining a client device identity. In one implementation, a method is provided that can include receiving a request from a client device. The method can also include determining, based on the client device request, a subscriber identification. After determining the subscriber identification, the method can include acquiring, from a transactional history database, transactional device data associated with the subscriber identification. In some embodiments, the transactional device data can include one or more counts associated with one or more device types. The method can also include determining, based on the transactional device data, the client device identity. In some embodiments, the determination of the client device identity can include selecting a device type of the one or more device types with the maximum count and setting the client device identity to the selected device type.

Abstract: An approach for dynamically segmenting traffic in a distributed computing environment is provided. The approach initiates a model allocation table by allocating traffic to one or more models. The approach retrieves a model identifier from a traffic segmentation table. The approach retrieves a current traffic allocation and a desired traffic allocation for the model identifier. The approach indicates a slot of the model identifier as free in the traffic segmentation table. The approach determines a number of slots to allocate to the model. The approach assigns one or more free slots to the model.