Abstract: Disclosed is a system for customizing protections provided to different application programming interfaces (“APIs”) and different functions of an API based on different API context and user context associated with the different APIs and the different functions of each API. The system receives a particular API, determines API context for proper usage of one or more functions of the particular API, and determines user context associated with endpoints properly accessing the one or more functions. The system generates a model for differentiating between proper and improper use of the one or more functions based on contextual relationships between different combinations of the API context and the user context. The system monitors usage of the one or more functions based on the model, and performs an action that is associated with the model in response to the usage violating the contextual relationships for the one or more functions.

Abstract: Disclosed is a system for customizing protections provided to different application programming interfaces (“APIs”) and different functions of an API based on different API context and user context associated with the different APIs and the different functions of each API. The system receives a particular API, determines API context for proper usage of one or more functions of the particular API, and determines user context associated with endpoints properly accessing the one or more functions. The system generates a model for differentiating between proper and improper use of the one or more functions based on contextual relationships between different combinations of the API context and the user context. The system monitors usage of the one or more functions based on the model, and performs an action that is associated with the model in response to the usage violating the contextual relationships for the one or more functions.

Abstract: Some embodiments provide intelligent predictive stream caching for live, linear, or video-on-demand streaming content using prefetching, segmented caching, and request clustering. Prefetching involves retrieving streaming content segments from an origin server prior to the segments being requested by users. Prefetching live or linear streaming content segments involves continually reissuing requests to the origin until the segments are obtained or a preset retry duration is completed. Prefetching is initiated in response to a first request for a segment falling within a particular interval. Request clustering commences thereafter. Subsequent requests are queued until the segments are retrieved. Segmented caching involves caching segments for one particular interval. Segments falling within a next interval are not prefetched until a first request for one such segment in the next interval is received.

Abstract: Some embodiments provide intelligent predictive stream caching for live, linear, or video-on-demand streaming content using prefetching, segmented caching, and request clustering. Prefetching involves retrieving streaming content segments from an origin server prior to the segments being requested by users. Prefetching live or linear streaming content segments involves continually reissuing requests to the origin until the segments are obtained or a preset retry duration is completed. Prefetching is initiated in response to a first request for a segment falling within a particular interval. Request clustering commences thereafter. Subsequent requests are queued until the segments are retrieved. Segmented caching involves caching segments for one particular interval. Segments falling within a next interval are not prefetched until a first request for one such segment in the next interval is received.

Abstract: Some embodiments provide intelligent predictive stream caching for live, linear, or video-on-demand streaming content using prefetching, segmented caching, and request clustering. Prefetching involves retrieving streaming content segments from an origin server prior to the segments being requested by users. Prefetching live or linear streaming content segments involves continually reissuing requests to the origin until the segments are obtained or a preset retry duration is completed. Prefetching is initiated in response to a first request for a segment falling within a particular interval. Request clustering commences thereafter. Subsequent requests are queued until the segments are retrieved. Segmented caching involves caching segments for one particular interval. Segments falling within a next interval are not prefetched until a first request for one such segment in the next interval is received.

Abstract: Some embodiments provide a system for simultaneously monitoring a content stream that is streamed using any of a plurality of streaming protocols from different points-of-presence (PoP) from within a distributed platform in real-time without the need for manual visual verification. The system is implemented with different emulation engines, each providing client-side player emulation for a different streaming protocol. The client-side player emulation involves requesting and downloading content stream chunks from a specified PoP according to the streaming protocol that is used by the distributed platform to stream the content stream under test. As part of the emulation, each instance inspects the downloaded chunks without decoding or rendering in order to track real-time performance and any errors in the server-side transmission of the content stream under test.

Abstract: Some embodiments dynamically test capacity of a streaming server under test (SUT). The dynamic testing involves a test server generating different test scenarios. Each test scenario specifies a mix of different streaming protocols, content streams, and content stream upload to download ratio. The test server tests the SUT with a gradually increasing traffic load from each test scenario while monitoring SUT performance under each load. The test server records each load from each test scenario under which the SUT becomes saturated. The test server produces a grid mapping the observed SUT saturation points to the test loads that caused them. The grid is used when the SUT is deployed to a production environment to determine if SUT saturation is imminent based on current traffic patterns being serviced by the SUT in the production environment. If so, a remedial action is dynamically performed to prevent the saturation from occurring.

Abstract: Some embodiments provide intelligent predictive stream caching for live, linear, or video-on-demand streaming content using prefetching, segmented caching, and request clustering. Prefetching involves retrieving streaming content segments from an origin server prior to the segments being requested by users. Prefetching live or linear streaming content segments involves continually reissuing requests to the origin until the segments are obtained or a preset retry duration is completed. Prefetching is initiated in response to a first request for a segment falling within a particular interval. Request clustering commences thereafter. Subsequent requests are queued until the segments are retrieved. Segmented caching involves caching segments for one particular interval. Segments falling within a next interval are not prefetched until a first request for one such segment in the next interval is received.

Abstract: Some embodiments dynamically test capacity of a streaming server under test (SUT). The dynamic testing involves a test server generating different test scenarios. Each test scenario specifies a mix of different streaming protocols, content streams, and content stream upload to download ratio. The test server tests the SUT with a gradually increasing traffic load from each test scenario while monitoring SUT performance under each load. The test server records each load from each test scenario under which the SUT becomes saturated. The test server produces a grid mapping the observed SUT saturation points to the test loads that caused them. The grid is used when the SUT is deployed to a production environment to determine if SUT saturation is imminent based on current traffic patterns being serviced by the SUT in the production environment. If so, a remedial action is dynamically performed to prevent the saturation from occurring.

Abstract: Some embodiments provide a system for simultaneously monitoring a content stream that is streamed using any of a plurality of streaming protocols from different points-of-presence (PoP) from within a distributed platform in real-time without the need for manual visual verification. The system is implemented with different emulation engines, each providing client-side player emulation for a different streaming protocol. The client-side player emulation involves requesting and downloading content stream chunks from a specified PoP according to the streaming protocol that is used by the distributed platform to stream the content stream under test. As part of the emulation, each instance inspects the downloaded chunks without decoding or rendering in order to track real-time performance and any errors in the server-side transmission of the content stream under test.