Abstract: Systems and methods for key performance benchmarking may include receiving for a plurality of client devices of a tenant, a duration for performing a plurality of actions to log into a resource. The systems and methods can include determining metrics for each action of the plurality of actions. The systems and methods can include generating, by the one or more processors, one or more recommendations corresponding to at least one action of the plurality of actions, to reduce the duration to log into the resource.

Abstract: Described embodiments provide systems and methods for intelligent load balancing of hosted sessions. A processor can determine a plurality of metrics for each of a plurality of machines configured to connect client devices with hosted sessions. The processor can receive, from a client device, a request to establish a connection with one of the plurality of machines to access a hosted session. The processor can determine a score for each of the plurality of machines based at least on the plurality of metrics for each of the plurality of machines. The processor can select a machine from the plurality of machines as a function of the score and a resource cost of the machine. The processor can cause the client device to connect to the selected machine for the hosted session.

Abstract: Described embodiments provide systems and methods for classifying a machine by performance. A device may identify, for a first time window, a first plurality of attributes of a machine and a session provided by the machine. The device may determine a first score based at least on a weight applied to each of the first plurality of attributes. The weight may be updated using a second plurality of attributes of the machine and the session provided by the machine for a second time window. The device may determine a probability of failure for the session by applying the first plurality of attributes to a model. The device may generate a second score indicating a performance of the machine as a function of the first score and the probability of failure. The device may classify the machine into a performance level in accordance with the second score.

Abstract: A server computer system configured to proactively predict a session failure of a virtual service is provided. The server computer system includes a memory and at least one processor coupled to the memory. The at least one processor is configured to receive one or more feature values associated with the virtual service. The processor can then evaluate a likelihood of session failure of the virtual service, such as a session launch failure, unresponsive state, or persistent session failure, in a future time interval based on the received feature values. The processor can then determine that the likelihood of session failure satisfies a classification test indicating the session failure is likely. Responsive to the determination, the processor can then execute a corrective operation, such as to end a user session, disable the virtual service, restart the virtual service, or render a user notification.

Abstract: A computer system configured to identify errors in a session launch initiated by a client application is provided. The computer system includes a memory and at least one processor coupled to the memory. The at least one processor is configured to receive one or more events from one or more applications or devices involved in the session launch, wherein an event of the one or more events comprises information from an application or device call (e.g., an application programming interface (API) call) communicated during the session launch, the information comprising destination information; build a primary Directed Acyclic Graph (DAG) based on the information from the API call; determine an error identifier based on the primary DAG; retrieve a troubleshooting recommendation from a library based on the error identifier; and send the troubleshooting recommendation to the client application.

Abstract: A computer system configured to identify errors in a session launch initiated by a client application is provided. The computer system includes a memory and at least one processor coupled to the memory. The at least one processor is configured to receive one or more events from one or more applications or devices involved in the session launch, wherein an event of the one or more events comprises information from an application or device call (e.g., an application programming interface (API) call) communicated during the session launch, the information comprising destination information; build a primary Directed Acyclic Graph (DAG) based on the information from the API call; determine an error identifier based on the primary DAG; retrieve a troubleshooting recommendation from a library based on the error identifier; and send the troubleshooting recommendation to the client application.

Abstract: Systems and methods for scoring audio/video (A/V) sessions may include a first client which identifies an A/V signal for a session of an A/V application between the first client and a second client, and metrics of a network path between the first client and the second client. The first client may determine a first score for the A/V signal by applying one or more features corresponding to the A/V signal to a model trained to generate the first score. The client may generate a session score for the session based on the first score and the metrics of the network path.

Abstract: Systems and methods for proactively alerting administrators of upcoming or possible network outages include a server which receives metrics for usage of one or more networks for each workspace application of plurality of workspace applications of a plurality of endpoints across a plurality of different locations of an enterprise. The server may determine a network download speed for each location of the plurality of different locations according to the metrics for each workspace application. The server may generate an alert to be provided to a device of a user associated with a first location of the plurality of different locations responsive to the network download speed for a network of the one or more networks falling below a threshold.

Abstract: A method may include running virtual sessions on a virtualization server corresponding to a published application for client devices associated with respective users. The client devices may have user input devices associated therewith, and the virtual sessions may be responsive to user input device traffic from different virtual drivers at the client devices over respective virtual channels. The method may further include collecting USB traffic relating to file copying based upon the traffic from the virtual drivers during the virtual sessions, determining baseline user input traffic patterns for the collected USB traffic and a normal usage pattern for the published application, monitoring traffic over the virtual channels at the virtualization server during a new virtual session for a given client device and detecting an anomaly therein relative to the baseline user input traffic patterns and the normal usage pattern, and generating an anomaly alert.

Abstract: Described embodiments provide for associating a user experience score with a location of a client. A device may identify a session between the client and an application service established via a first network. The device may receive, via the application service, a network address of the client associated with a second network. The device may determine a location of the client accessing the application service via the first network based at least on the network address associated with the second network. The device may receive, from an instrumentation service, performance factors for the client. Each of the performance factors may be associated with access to the application service by the client. The device may generate a user experience score for the client based at least on the performance factors. The device may provide an instruction based at least on an association between the user experience score and the location.

Abstract: Described embodiments provide for associating a user experience score with a location of a client. A device may identify a session between the client and an application service established via a first network. The device may receive, via the application service, a network address of the client associated with a second network. The device may determine a location of the client accessing the application service via the first network based at least on the network address associated with the second network. The device may receive, from an instrumentation service, performance factors for the client. Each of the performance factors may be associated with access to the application service by the client. The device may generate a user experience score for the client based at least on the performance factors. The device may provide an instruction based at least on an association between the user experience score and the location.

Abstract: A method may include running virtual sessions on a virtualization server for a plurality of client devices associated with respective users, with the virtual sessions being responsive to traffic from the client devices. The method may further include generating baseline traffic patterns for the users based upon the traffic from respective client devices during the virtual sessions, monitoring traffic during a new virtual session for a given client device and detecting an anomaly therein relative to at least one of the baseline traffic patterns, and generating an anomaly alert based upon detecting the anomaly.

Abstract: Described embodiments provide systems and method for determining a root cause of a failure of a session to an application, device or server. A failure of a session with an application can be identified. A device can generate a mapping between characteristics of data from the application associated with the failure and data from monitoring a plurality of sessions between a plurality of end points and a plurality of applications hosted by a plurality of computing devices. The device can determine, responsive to the mapping indicating an association between at least one characteristic of the data from the application and the data from the monitoring, a cause of the failure of the session with the application.

Abstract: Described embodiments provide a method, computer program product, and computer system for creating, by a client device, an application probe, the application probe configured to monitor at least one attribute of an application accessible via the client device. The client device may receive data indicative of the at least one attribute of the application in response to the application being monitored by the application probe. The client device may determine a value for the at least one attribute based upon, at least in part, the received data. The client device may compare the determined value with a threshold to identify an issue with the application. The client device may provide an indication to a computing device in response to the comparison of the determined value with the threshold, so as to enable the computing device to modify operation of the application to address the issue.

Abstract: A method may include running virtual sessions on a virtualization server for a plurality of client devices associated with respective users, with the virtual sessions being responsive to traffic from the client devices. The method may further include generating baseline traffic patterns for the users based upon the traffic from respective client devices during the virtual sessions, monitoring traffic during a new virtual session for a given client device and detecting an anomaly therein relative to at least one of the baseline traffic patterns, and generating an anomaly alert based upon detecting the anomaly.

Abstract: At least a method and a system for migrating a plurality of endpoint computing devices of an organization are described herein. User applications, data, and settings are migrated from a plurality of endpoint computing devices of the organization into a client server operating environment employing a thin client implementation. A server may execute software for deploying the thin client implementation. By way of creating a personalized virtualization disk for each endpoint computing device, migration to a thin client virtualized desktop implementation may be easily performed by the organization without modification, change, or loss of user installed applications, personalized settings, and user data.