Abstract: The load level on a server system is regulated by determining time-to-live (TTL) values to provide to requesting devices that request a content resource from the server system, thereby affecting the frequency of subsequent requests. This dynamic determination of TTL values may provide resilience to system load, for example by using longer TTL values when the system is under greater load to reduce the rate at which subsequent requests are received. A dynamic TTL service may calculate a TTL value based on one or more factors, such as overall system load, resource load, hardware load, and/or software load.

Abstract: Time to live (“TTL”) values are determined based on one or more factors. The TTL values may be included in responses to requests for resources, thereby affecting the frequency of subsequent requests. This dynamic determination of TTL values may provide resilience to system load, for example by using longer TTL values when the system is under greater load in order to reduce the rate at which subsequent requests are received. A dynamic TTL service may calculate a TTL value based on one or more factors, such as overall system load, resource load, hardware load, and/or software load. In various embodiments, a dynamic TTL service may act natively within a service, within a system framework, as a proxy, as a cluster, and/or as a broker.

Abstract: Features are disclosed for analyzing requests for network accessible content, including but not limited to web pages, to determine which topics and other characteristics are popular or are gaining in popularity (“trending”). Content items or sources may be profiled to determine characteristics that two or more content items or sources may have in common. Content requests from multiple client devices may be tracked and analyzed to determine the trending or popular characteristics. Data feeds or reports regarding the summarized content requests may be generated and distributed to content servers and other entities. The data feeds may be used to tailor content, such as by highlighting or featuring content associated with the most-requested content characteristics, or utilizing demographic data to tailor content for different users.

Abstract: Features are disclosed for analyzing requests for network accessible content, including but not limited to web pages, to determine which topics and other characteristics are popular or are gaining in popularity (“trending”). Content items or sources may be profiled to determine characteristics that two or more content items or sources may have in common. Content requests from multiple client devices may be tracked and analyzed to determine the trending or popular characteristics. Data feeds or reports regarding the summarized content requests may be generated and distributed to content servers, advertisers, and other entities. The data feeds may be used to tailor content, such as by highlighting or featuring content associated with the most-requested content characteristics, or utilizing demographic data to tailor content for different users.

Abstract: Features are disclosed for determining a sequence of content, including but not limited to web pages, that a user of a client device is likely to request or otherwise find interesting based on previous content requests (of that user and/or other users), and to making the sequence of content available for viewing on the client device. The identified pattern may later be used as a basis to prefetch the content, and to make the sequence of prefetched content available on the client device as a “suggested browsing session.” The suggested browsing session may include a sequence of content pages typically requested by the user, and/or may include linked pages and recommendations that the user is otherwise likely to find interesting.

Abstract: Features are provided for facilitating prioritized transmission of content between content providers and content requesters. A content provider or intermediary entity obtains prioritization rules for transmitting network resources, such as resources embedded in or otherwise associated with web pages. The prioritization rules can be general rules applying to the transmission of all network resources or a large number thereof, or they can be customized for a specific network resource or small group thereof. The prioritization rules can be applied to the relative bandwidth utilization or data transfer rates of network resources. The relative bandwidth utilization or data transfer rates can be adjusted in response to network or user events.

Abstract: Features are provided for facilitating prioritized transmission of content between content providers and content requesters. A content provider or intermediary entity obtains prioritization rules for transmitting network resources, such as resources embedded in or otherwise associated with web pages. The prioritization rules can be general rules applying to the transmission of all network resources or a large number thereof, or they can be customized for a specific network resource or small group thereof. The prioritization rules can be applied to the relative bandwidth utilization or data transfer rates of network resources. The relative bandwidth utilization or data transfer rates can be adjusted in response to network or user events.

Abstract: Features are provided for facilitating prioritized transmission of content between content providers and content requesters. A content provider or intermediary entity obtains prioritization rules for transmitting network resources, such as resources embedded in or otherwise associated with web pages. The prioritization rules can be general rules applying to the transmission of all network resources or a large number thereof, or they can be customized for a specific network resource or small group thereof. The prioritization rules can be applied to the relative bandwidth utilization or data transfer rates of network resources. The relative bandwidth utilization or data transfer rates can be adjusted in response to network or user events.

Abstract: A connection-aggregation proxy service disclosed in various embodiments receives connection requests from a plurality of local initiating services, where the connection requests are not targeted at the connection-aggregation proxy service. The connection-aggregation proxy service establishes connections with the local initiating services, receives packets over those connections, and transmits the packets across the same connection when the packets are for the same external target. A local connection-aggregation proxy service in one example executes on the same physical computing device as the local initiating services. A gateway connection-aggregation proxy service in another example resides at a network edge between the local initiating services and the external target that the network local initiating services are requesting.

Abstract: Processes are disclosed for identifying site-specific or domain-specific URL parameters that are likely associated with personally identifiable information (PII). The processes involve analyzing the browsing session records of multiple users to assess, for a given site or domain, the uniqueness levels of particular URL parameters. These uniqueness levels, alone or in combination with other criteria, are used to determine whether each such parameter is likely associated with PII. The results of this analysis may be used to filter likely PII from session records, such as by modifying and/or deleting the URLs likely to contain PII.