Conviva Inc.

Yan Li

Jibin Zhan

Henry Milner

Rui Zhang

Aditya Ravikumar Ganjam

Hui Joyce Zhang

Ion Stoica

Faisal Zakaria Siddiqi

Alexey Serbin

Davis Shepherd

Xi Liu

Xi Xiong

Vyas Sekar

Jose Caldeira Jesus

Bodicherla Aditya Prakash

Harshil Shah

Harshavardhan Kamarthi

Yasar Arafath Rafi Ahmed

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.

Multi-cohort replay storage and retrospective anomaly detection analysis

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.

Automated surfacing of multi-dimensional insights

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.

IP classification

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.

Automatic diagnostics alerts

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.

Automatic diagnostics alerts for streaming content encoded by multiple entities

Generating streaming decisions at one or more remote servers on behalf of a local client is disclosed. An indication of a content request, multi-dimensional client information, and local state information are received from a client device. A record specific to the client device is generated, in a data store, using the received local state information. The data store includes a plurality of records corresponding to respective different client devices. A set of instructions usable by the client device to obtain and play content is determined based at least in part the local state information received from the client device. The determined set of instructions is transmitted to the client device.

Streaming decision in the cloud

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Foster City, CA, United States of America

Yan Li