Abstract: Systems and methods for are provided for predicting impending failure of a database and preemptively initiating mitigating failover actions, for example by shedding connections or redirecting connection requests to an alternate database that can fulfill resources being requested. In an example embodiment, to detect a slow or unstable database, connection wait times are monitored over a rolling window of time intervals, a quantity of intervals in which at least one excessive wait time event occurred are counted during the time window, and if the quantity exceeds a threshold, the database is deemed unavailable, thereby triggering connection adjustments.

Abstract: In the implementation of techniques for distributing digital content with edge devices, a system receives a request including digital content from a client device for uploading the digital content. Based on the request, the system identifies a nearest edge device from a plurality of edge devices. The system transmits instructions to the nearest edge device to generate a unique identifier corresponding to the digital content and to store the digital content. The system initiates one or more requests to a predefined number of one or more edge devices from the plurality of edge devices to store the digital content. The system receives confirmation from the predefined number of one or more edge devices that the digital content is stored. The system generates a response including content corresponding to the unique identifier, which is usable to access the digital content stored. The system broadcasts the response to the client device.

Abstract: Systems and methods for are provided for predicting impending failure of a database and preemptively initiating mitigating failover actions, for example by shedding connections or redirecting connection requests to an alternate database that can fulfill resources being requested. In an example embodiment, to detect a slow or unstable database, connection wait times are monitored over a rolling window of time intervals, a quantity of intervals in which at least one excessive wait time event occurred are counted during the time window, and if the quantity exceeds a threshold, the database is deemed unavailable, thereby triggering connection adjustments.

Abstract: Systems and methods for are provided for predicting impending failure of a database and preemptively initiating mitigating failover actions, for example by shedding connections or redirecting connection requests to an alternate database that can fulfill resources being requested. In an example embodiment, to detect a slow or unstable database, connection wait times are monitored over a rolling window of time intervals, a quantity of intervals in which at least one excessive wait time event occurred are counted during the time window, and if the quantity exceeds a threshold, the database is deemed unavailable, thereby triggering connection adjustments.

Abstract: Systems and methods for are provided for predicting impending failure of a database and preemptively initiating mitigating failover actions, for example by shedding connections or redirecting connection requests to an alternate database that can fulfill resources being requested. In an example embodiment, to detect a slow or unstable database, connection wait times are monitored over a rolling window of time intervals, a quantity of intervals in which at least one excessive wait time event occurred are counted during the time window, and if the quantity exceeds a threshold, the database is deemed unavailable, thereby triggering connection adjustments.

Abstract: Systems and methods for are provided for predicting impending failure of a database and preemptively initiating mitigating failover actions, for example by shedding connections or redirecting connection requests to an alternate database that can fulfill resources being requested. In an example embodiment, to detect a slow or unstable database, connection wait times are monitored over a rolling window of time intervals, a quantity of intervals in which at least one excessive wait time event occurred are counted during the time window, and if the quantity exceeds a threshold, the database is deemed unavailable, thereby triggering connection adjustments.

Abstract: In a networked data system, a discovery protocol enables clients to establish connections to one a plurality of database servers to utilize a distributed connection service. The service manages connections between application servers, i.e. clients, and databases. An initial request from the client is received by a load balancer. The load balancer responds to the client by identifying an assigned connection to one of the database servers based on load considerations. The client sends a secondary request directly to the assigned connection, bypassing the load balancer. The service establishes a persistent link on the assigned connection and assigns a time-to-live (TTL), during which the service connects data requests to the databases. Upon expiration of the TTL, the service completes a next data request received, then notifies the client that the connection is no longer valid, thereby requiring a new connection through the load balancer and rebalancing system traffic.

Abstract: Systems and methods for are provided for predicting impending failure of a database and preemptively initiating mitigating failover actions, for example by shedding connections or redirecting connection requests to an alternate database that can fulfill resources being requested. In an example embodiment, to detect a slow or unstable database, connection wait times are monitored over a rolling window of time intervals, a quantity of intervals in which at least one excessive wait time event occurred are counted during the time window, and if the quantity exceeds a threshold, the database is deemed unavailable, thereby triggering connection adjustments.

Abstract: Defects are identified in a pre-production version of an application. Input used to test the pre-production version is derived from input received by a production version of the application. Input to the production version may be selectively filtered and/or amplified before being provided as test input to the pre-production version. In this way, the makeup and rate of the test input can be controlled while maintaining the character, pattern, and unpredictable nature of real-world input. Defects may be identified when the test input causes the pre-production version to crash, hang, write to an error log, or otherwise manifest or report a malfunction. In addition to identifying defects, filtered and amplified input may also be used to perform regression testing, load testing, performance testing, etc.

Abstract: Systems and methods for are provided for predicting impending failure of a database and preemptively initiating mitigating failover actions, for example by shedding connections or redirecting connection requests to an alternate database that can fulfill resources being requested. In an example embodiment, to detect a slow or unstable database, connection wait times are monitored over a rolling window of time intervals, a quantity of intervals in which at least one excessive wait time event occurred are counted during the time window, and if the quantity exceeds a threshold, the database is deemed unavailable, thereby triggering connection adjustments.

Abstract: Defects are identified in a pre-production version of an application. Input used to test the pre-production version is derived from input received by a production version of the application. Input to the production version may be selectively filtered and/or amplified before being provided as test input to the pre-production version. In this way, the makeup and rate of the test input can be controlled while maintaining the character, pattern, and unpredictable nature of real-world input. Defects may be identified when the test input causes the pre-production version to crash, hang, write to an error log, or otherwise manifest or report a malfunction. In addition to identifying defects, filtered and amplified input may also be used to perform regression testing, load testing, performance testing, etc.

Abstract: In a networked data system, a discovery protocol enables clients to establish connections to one a plurality of database servers to utilize a distributed connection service. The service manages connections between application servers, i.e. clients, and databases. An initial request from the client is received by a load balancer. The load balancer responds to the client by identifying an assigned connection to one of the database servers based on load considerations. The client sends a secondary request directly to the assigned connection, bypassing the load balancer. The service establishes a persistent link on the assigned connection and assigns a time-to-live (TTL), during which the service connects data requests to the databases. Upon expiration of the TTL, the service completes a next data request received, then notifies the client that the connection is no longer valid, thereby requiring a new connection through the load balancer and rebalancing system traffic.

Abstract: In a networked data system, a discovery protocol enables clients to establish connections to one a plurality of database servers to utilize a distributed connection service. The service manages connections between application servers, i.e. clients, and databases. An initial request from the client is received by a load balancer. The load balancer responds to the client by identifying an assigned connection to one of the database servers based on load considerations. The client sends a secondary request directly to the assigned connection, bypassing the load balancer. The service establishes a persistent link on the assigned connection and assigns a time-to-live (TTL), during which the service connects data requests to the databases. Upon expiration of the TTL, the service completes a next data request received, then notifies the client that the connection is no longer valid, thereby requiring a new connection through the load balancer and rebalancing system traffic.

Abstract: Systems and methods for are provided for predicting impending failure of a database and preemptively initiating mitigating failover actions, for example by shedding connections or redirecting connection requests to an alternate database that can fulfill resources being requested. In an example embodiment, to detect a slow or unstable database, connection wait times are monitored over a rolling window of time intervals, a quantity of intervals in which at least one excessive wait time event occurred are counted during the time window, and if the quantity exceeds a threshold, the database is deemed unavailable, thereby triggering connection adjustments.

Abstract: In a networked data system, a discovery protocol enables clients to establish connections to one a plurality of database servers to utilize a distributed connection service. The service manages connections between application servers, i.e. clients, and databases. An initial request from the client is received by a load balancer. The load balancer responds to the client by identifying an assigned connection to one of the database servers based on load considerations. The client sends a secondary request directly to the assigned connection, bypassing the load balancer. The service establishes a persistent link on the assigned connection and assigns a time-to-live (TTL), during which the service connects data requests to the databases. Upon expiration of the TTL, the service completes a next data request received, then notifies the client that the connection is no longer valid, thereby requiring a new connection through the load balancer and rebalancing system traffic.