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: Delivering an advertisement is disclosed. Local user information is collected. Examples of local user information include language settings, web browser history, and actions taken by a user with respect to various applications. An advertisement is selected from a plurality of advertisements based at least in part on the local user information. The selected advertisement is caused to be displayed.

Abstract: Remote multi-target client monitoring for streaming content is disclosed. Raw data generated within a remote client device is received from the client device. The raw data is associated with content playback. An adaptor is used to translate the raw data into a unified data model. The translating comprises determining, from the raw data, a designation of at least one of a start and an end of a monitoring session.

Abstract: In various embodiments, a process includes obtaining, from a first entity external to a client device, a data capture configuration specifying fields permitted to be captured on the client device from a network request and/or a corresponding network response. The process includes intercepting, on the client device, the network request and/or the corresponding network response. The network request may be generated by the application and associated with an application event. In response to intercepting the network request and/or the corresponding network response, the process determines the fields permitted to be captured based at least in part on the data capture configuration and captures select field-value pairs from a header and/or a body of the network request and/or a corresponding network response according to the data capture configuration. The process includes reporting, to a second entity external to the client device, the captured select field-value pairs.

Abstract: Facilitating analytics such as retrospective analysis includes ingesting session data. It further includes summarizing the session data and generating leaf-level summarizations of leaf groups present in the session data. It further includes storing the leaf-level summarizations. It further includes deriving parent-level summarizations for a parent group from leaf-level summarizations of leaf groups that are children of the parent group.

Abstract: Evaluating multi-dimensional information includes providing a plurality of initial dimensions. Each dimension represents a factor related to performance. It further includes receiving a first selection of a value for a first dimension in the plurality of initial dimensions. It further includes providing a plurality of potentially significant dimensions from among a set of dimensions. It further includes receiving a second selection of a second dimension from among the plurality of potentially significant dimensions. It further includes determining the plurality of potentially significant dimensions based on an indication of presence of outliers in the potentially significant dimension. A dimension that significantly affects performance is identified.

Abstract: A set of Internet Protocol (IP) addresses is received wherein each IP address is associated with a corresponding set of features. For an IP address in the set, the IP address is evaluated based at least in part on a set of inclusion criteria. For the IP address in the set, a likelihood that the IP address is residential or non-residential is generated based at least in part on the corresponding set of features and the evaluation of the IP address based at least in part on the set of inclusion criteria. For the IP address in the set, a training sample is generated that includes the IP address, at least some of the corresponding set of features, and a label. A labeled training data set is output that includes the training sample, where an IP address classifier is trained using the labeled training data set.

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: Facilitating a decision of a content player is disclosed. In some cases, performance information associated with a content player is received. The information is received from a client. A determination is made that an update should be sent to the client. The update is sent to the client. In other cases, information is received from an external entity. Based at least in part on the received information, an instruction is sent to a content player.

Abstract: Establishing a data store of content metadata includes receiving, from a content player executing on a client device, an indication of content played by the content player, the indication comprising one or more pieces of metadata associated with the content. It further includes selecting a set of one or more rules applicable to parsing the metadata associated with the content. It further includes processing the metadata at least in part by applying the selected parsing rules to at least a portion of the metadata associated with the content. It further includes storing, to a data store, at least some of the processed metadata associated with the content.

Abstract: Determining a stateful metric includes receiving a first mapped event that is generated based on semantic mapping of a first raw event associated with a first time. It further includes receiving a second mapped event that is generated based on semantic mapping of a second raw event associated with a second time that is subsequent to the first time. It further includes determining a stateful metric based on the first mapped event and the second mapped event.

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: Resource allocation includes generating a resource allocation identifier corresponding to a resource allocation request. The resource allocation request pertains to allocation of a resource associated with streaming of an audiovisual content item. The resource allocation identifier comprises a first portion and a second portion, the first portion comprising a key, and the second portion comprising information associated with contextual metadata pertaining to the corresponding resource allocation request. It further includes performing a first transmission of a first message including the resource allocation identifier. The first message including the resource allocation identifier is directed to a first address associated with a first entity. It further includes performing a second transmission of a second message. Transmission of the second message causes transmission of the resource allocation request. The second message is directed to a second address associated with a second entity.

Abstract: Establishing a data store of content metadata includes receiving, from a content player executing on a client device, an indication of content played by the content player, the indication comprising one or more pieces of metadata associated with the content. It further includes selecting a set of one or more rules applicable to parsing the metadata associated with the content. It further includes processing the metadata at least in part by applying the selected parsing rules to at least a portion of the metadata associated with the content. It further includes storing, to a data store, at least some of the processed metadata associated with the content.

Abstract: Per-viewer engagement-based video optimization is disclosed. A request for content associated with a first client is received. A model associated with the first client is obtained. The obtained model comprises at least one of behavior and playback preferences of a viewer associated with the first client. The obtained model is used to determine, for the first client, an optimal set of instructions usable to obtain content. A different set of instructions is determined to be optimal for a second client. The optimal set of instructions determined for the client is provided as output. The first client is configured to obtain content according to the optimal set of instructions determined for the first client.

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: Correlating information associated with playback of video segments is disclosed. Information associated with playback of a first video segment is obtained. Information associated with playback of a second video segment is obtained. The information associated with playback of the first video segment is correlated with the information associated with playback of the second video segment based at least in part on at least one of a client application identifier, a video session identifier, and a set of timestamps. Output is provided based at least in part on the correlating.

Abstract: Resource allocation includes generating a resource allocation identifier corresponding to a resource allocation request. The resource allocation request pertains to allocation of a resource associated with streaming of an audiovisual content item. The resource allocation identifier comprises a first portion and a second portion, the first portion comprising a key, and the second portion comprising information associated with contextual metadata pertaining to the corresponding resource allocation request. It further includes performing a first transmission of a first message including the resource allocation identifier. The first message including the resource allocation identifier is directed to a first address associated with a first entity. It further includes performing a second transmission of a second message. Transmission of the second message causes transmission of the resource allocation request. The second message is directed to a second address associated with a second entity.

Abstract: Correlating information associated with playback of video segments is disclosed. Information associated with playback of a first video segment is obtained. Information associated with playback of a second video segment is obtained. The information associated with playback of the first video segment is correlated with the information associated with playback of the second video segment based at least in part on at least one of a client application identifier, a video session identifier, and a set of timestamps. Output is provided based at least in part on the correlating.