Abstract: Determining a time-state metric includes receiving a stream of raw data values of an attribute. Each received raw data value of the attribute is associated with a timestamp. It further includes converting the received stream of raw data values into a timeline representation of the attribute over time. The timeline representation comprises a sequence of spans. A span comprises a span start time, a span end time, and a span value. The span value comprises an encoding of one or more values of the attribute over a time interval determined by the span start time and the span end time. It further includes determining a time-state metric according to a timeline request configuration. The timeline request configuration comprises one or more timeline operations. The time-state metric is computed at least in part by performing a timeline operation on the timeline representation of the attribute.

Abstract: Determining a time-state metric includes receiving a stream of raw data values of an attribute. Each received raw data value of the attribute is associated with a timestamp. It further includes converting the received stream of raw data values into a timeline representation of the attribute over time. The timeline representation comprises a sequence of spans. A span comprises a span start time, a span end time, and a span value. The span value comprises an encoding of one or more values of the attribute over a time interval determined by the span start time and the span end time. It further includes determining a time-state metric according to a timeline request configuration. The timeline request configuration comprises one or more timeline operations. The time-state metric is computed at least in part by performing a timeline operation on the timeline representation of the attribute.

Abstract: Visual composition of stateful metrics includes receiving, via a user interface, an indication of a user interaction with respect to a visual representation of a timeline operator included in a stateful metric that is being visually composed. It further includes, based on the indication of the user interaction with respect to the visual representation of the timeline operator, providing visual feedback.

Abstract: Automatic diagnostics alerts for streaming multiple types of content is disclosed. At a first time, a set of metrics for a plurality of groups of streaming sessions is computed. A streaming session in a group is associated with streaming of a piece of content encoded by an entity. The streaming of the piece of content encoded by the entity is associated with streaming of another piece of content. An anomaly is identified at least in part by performing anomaly detection using the set of metrics. A cause of the identified anomaly is diagnosed. An alert is generated based at least in part on the diagnosis.

Abstract: Generating automatic diagnostics alerts is disclosed. At a first time, a set of quality metrics for a plurality of groups of streaming sessions is computed. An anomaly is identified at least in part by performing anomaly detection using the set of quality metrics and historical information. A cause of the identified anomaly is diagnosed. An alert is generated based at least in part on the diagnosis.

Abstract: Determining a time-state metric includes receiving a stream of raw data values of an attribute. Each received raw data value of the attribute is associated with a timestamp. It further includes converting the received stream of raw data values into a timeline representation of the attribute over time. The timeline representation comprises a sequence of spans. A span comprises a span start time, a span end time, and a span value. The span value comprises an encoding of one or more values of the attribute over a time interval determined by the span start time and the span end time. It further includes determining a time-state metric according to a timeline request configuration. The timeline request configuration comprises one or more timeline operations. The time-state metric is computed at least in part by performing a timeline operation on the timeline representation of the attribute.

Abstract: Generating automatic diagnostics alerts is disclosed. At a first time, a set of quality metrics for a plurality of groups of streaming sessions is computed. An anomaly is identified at least in part by performing anomaly detection using the set of quality metrics and historical information. A cause of the identified anomaly is diagnosed. An alert is generated based at least in part on the diagnosis.

Abstract: Generating automatic diagnostics alerts is disclosed. At a first time, a set of quality metrics for a plurality of groups of streaming sessions is computed. An anomaly is identified at least in part by performing anomaly detection using the set of quality metrics and historical information. A cause of the identified anomaly is diagnosed. An alert is generated based at least in part on the diagnosis.

Abstract: Automatic diagnostics alerts for streaming multiple types of content is disclosed. At a first time, a set of metrics for a plurality of groups of streaming sessions is computed. A streaming session in a group is associated with streaming of a piece of content encoded by an entity. The streaming of the piece of content encoded by the entity is associated with streaming of another piece of content. An anomaly is identified at least in part by performing anomaly detection using the set of metrics. A cause of the identified anomaly is diagnosed. An alert is generated based at least in part on the diagnosis.

Abstract: Automatic diagnostics alerts for streaming multiple types of content is disclosed. At a first time, a set of metrics for a plurality of groups of streaming sessions is computed. A streaming session in a group is associated with streaming of a piece of content encoded by an entity. The streaming of the piece of content encoded by the entity is associated with streaming of another piece of content. An anomaly is identified at least in part by performing anomaly detection using the set of metrics. A cause of the identified anomaly is diagnosed. An alert is generated based at least in part on the diagnosis.

Abstract: Generating automatic diagnostics alerts is disclosed. At a first time, a set of quality metrics for a plurality of groups of streaming sessions is computed. An anomaly is identified at least in part by performing anomaly detection using the set of quality metrics and historical information. A cause of the identified anomaly is diagnosed. An alert is generated based at least in part on the diagnosis.

Abstract: Generating automatic diagnostics alerts is disclosed. At a first time, a set of quality metrics for a plurality of groups of streaming sessions is computed. An anomaly is identified at least in part by performing anomaly detection using the set of quality metrics and historical information. A cause of the identified anomaly is diagnosed. An alert is generated based at least in part on the diagnosis.

Abstract: Directing a content player to a content source is disclosed. A first manifest request from a client requesting content is received at a server. The manifest request includes information generated as a result of the client contacting a content management system and in response, receiving from the content management system information associated with the client and a direction to the server. Based at least in part on the received information, at least one of a bitrate and a content source is determined. Instructions are sent to the client based at least in part on the determination. The client is configured to obtain the requested content according to the instructions.

Abstract: Fault isolation in over-the-top content (OTT) broadband networks is disclosed. Network topology information associated with a network service provider is received. Session information associated with one or more streaming sessions is received. A predictive model is generated for predicting session quality at least in part by using at least some of the network topology and session summary information as features. The predictive model is used to determine a first prediction of session quality using a first set of feature values. A second set of feature values is generated at least in part by replacing a first feature value in the first set of feature values with a replacement value. The predictive model is used to determine a replacement prediction of session quality using the second set of feature values including the replacement value with which the first feature value was replaced.

Abstract: An apparatus, system, and method of dispersing solid forms of drugs or medications reliably and consistently may generally employ ultrasonic energy. The disclosed embodiments facilitate preparation of a liquid dose from solid medications for administration to a patient.

Abstract: An apparatus, system, and method of dispersing solid forms of drugs or medications reliably and consistently may generally employ ultrasonic energy. The disclosed embodiments facilitate preparation of a liquid dose from solid medications for administration to a patient.

Abstract: Directing a video player to a video source is disclosed. An indication that a client requires video streaming instructions is received. A past download performance for a plurality of clients that or correlated to the client requiring video streaming instructions is determined. At least one of: a content source, and a bitrate, is selected, based at least in part on the determined past download performance of the plurality of correlated clients. The client is provided with instructions based at least in part on the selection.

Abstract: An apparatus, system, and method of dispersing solid forms of drugs or medications reliably and consistently may generally employ ultrasonic energy. The disclosed embodiments facilitate preparation of a liquid dose from solid medications for administration to a patient.

Abstract: An apparatus, system, and method of dispersing solid forms of drugs or medications reliably and consistently may generally employ ultrasonic energy. The disclosed embodiments facilitate preparation of a liquid dose from solid medications for administration to a patient.