Abstract: Content creation techniques are described that leverage content analytics to provide insight and guidance as part of content creation. To do so, content features are extracted by a content analytics system from a plurality of content and used by the content analytics system as a basis to generate a content dataset. Event data is also collected by the content analytics system from an event data source. Event data describes user interaction with respective items of content, including subsequent activities in both online and physical environments. The event data is then used to generate an event dataset. An analytics user interface is then generated by the content analytics system using the content dataset and the event dataset and is usable to guide subsequent content creation and editing.

Abstract: Content creation techniques are described that leverage content analytics to provide insight and guidance as part of content creation. To do so, content features are extracted by a content analytics system from a plurality of content and used by the content analytics system as a basis to generate a content dataset. Event data is also collected by the content analytics system from an event data source. Event data describes user interaction with respective items of content, including subsequent activities in both online and physical environments. The event data is then used to generate an event dataset. An analytics user interface is then generated by the content analytics system using the content dataset and the event dataset and is usable to guide subsequent content creation and editing.

Abstract: Content creation techniques are described that leverage content analytics to provide insight and guidance as part of content creation. To do so, content features are extracted by a content analytics system from a plurality of content and used by the content analytics system as a basis to generate a content dataset. Event data is also collected by the content analytics system from an event data source. Event data describes user interaction with respective items of content, including subsequent activities in both online and physical environments. The event data is then used to generate an event dataset. An analytics user interface is then generated by the content analytics system using the content dataset and the event dataset and is usable to guide subsequent content creation and editing.

Abstract: A web content extension system and platform is described. Web content extensions include tags as well as actionable code that supports deeper integration with web content than that supported by conventional tags, e.g., through interaction with APIs of the web content. The web content extensions are made available by developers of the extension to content creators via an extension catalog. The extension catalog thus supports a platform that unites developers of the web content extensions with content creators of web content. Further, this platform may be configured to support developer control of integration of the web content extension through use of an extension user interface that is created by the developer.

Abstract: A load manager comprises a configuration manager and a load monitor. The load manager is configured to monitor and manage aspects of a distributed computer system comprising a plurality of servers. Each server is configured to perform tasks according to a respective time-based scheduler configuration. In some embodiments, the load monitor monitors one or more load metrics of each of the one or more servers. In response to one or more load metrics exceeding a threshold, the configuration manager determines the current time-based task scheduler configuration of the server exceeding the threshold. The load manager is further configured to modify the time-based task scheduler configuration to adjust a further task load on the server based on the at least one or more load metrics.

Abstract: A load manager comprises a configuration manager and a load monitor. The load manager is configured to monitor and manage aspects of a distributed computer system comprising a plurality of servers. Each server is configured to perform tasks according to a respective time-based scheduler configuration. In some embodiments, the load monitor monitors one or more load metrics of each of the one or more servers. In response to one or more load metrics exceeding a threshold, the configuration manager determines the current time-based task scheduler configuration of the server exceeding the threshold. The load manager is further configured to modify the time-based task scheduler configuration to adjust a further task load on the server based on the at least one or more load metrics.

Abstract: A load manager comprises a configuration manager and a load monitor. The load manager is configured to monitor and manage aspects of a distributed computer system comprising a plurality of servers. Each server is configured to perform tasks according to a respective time-based scheduler configuration. In some embodiments, the load monitor monitors one or more load metrics of each of the one or more servers. In response to one or more load metrics exceeding a threshold, the configuration manager determines the current time-based task scheduler configuration of the server exceeding the threshold. The load manager is further configured to modify the time-based task scheduler configuration to adjust a further task load on the server based on the at least one or more load metrics.

Abstract: A load manager comprises a configuration manager and a load monitor. The load manager is configured to monitor and manage aspects of a distributed computer system comprising a plurality of servers. Each server is configured to perform tasks according to a respective time-based scheduler configuration. In some embodiments, the load monitor monitors one or more load metrics of each of the one or more servers. In response to one or more load metrics exceeding a threshold, the configuration manager determines the current time-based task scheduler configuration of the server exceeding the threshold. The load manager is further configured to modify the time-based task scheduler configuration to adjust a further task load on the server based on the at least on or more load metrics.

Abstract: A load manager comprises a configuration manager and a load monitor. The load manager is configured to monitor and manage aspects of a distributed computer system comprising a plurality of servers. Each server is configured to perform tasks according to a respective time-based scheduler configuration. In some embodiments, the load monitor monitors one or more load metrics of each of the one or more servers. In response to one or more load metrics exceeding a threshold, the configuration manager determines the current time-based task scheduler configuration of the server exceeding the threshold. The load manager is further configured to modify the time-based task scheduler configuration to adjust a further task load on the server based on the at least on or more load metrics.