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of the TTL, the service completes a next data request received, then notifies the client that the connection is no longer valid, thereby requiring a new connection through the load balancer and rebalancing system traffic.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: Systems and methods for preemptive adjustments of connections in a server connection pool are provided. In example embodiments, a number of quality of service engines analyze server connection pool metrics data to generate instructions to increase or decrease the number of connections in a connection pool, preemptively, before shortages or surpluses of connections occur. Corrective engines can analyze performance of the quality of service engines and can, when necessary, instruct the quality of service engines to modify their prediction mechanisms.

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 preemptive adjustments of connections in a server connection pool are provided. In example embodiments, a number of quality of service engines analyze server connection pool metrics data to generate instructions to increase or decrease the number of connections in a connection pool, preemptively, before shortages or surpluses of connections occur. Corrective engines can analyze performance of the quality of service engines and can, when necessary, instruct the quality of service engines to modify their prediction mechanisms.

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 preemptive adjustments of connections in a server connection pool are provided. In example embodiments, a number of quality of service engines analyze server connection pool metrics data to generate instructions to increase or decrease the number of connections in a connection pool, preemptively, before shortages or surpluses of connections occur. Corrective engines can analyze performance of the quality of service engines and can, when necessary, instruct the quality of service engines to modify their prediction mechanisms.

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: Systems and methods for preemptive adjustments of connections in a server connection pool are provided. In example embodiments, a number of quality of service engines analyze server connection pool metrics data to generate instructions to increase or decrease the number of connections in a connection pool, preemptively, before shortages or surpluses of connections occur. Corrective engines can analyze performance of the quality of service engines and can, when necessary, instruct the quality of service engines to modify their prediction mechanisms.

Abstract: Systems and methods for preemptive adjustments of connections in a database connection pool are provided. In example embodiments, a number of quality of service engines analyze database connection pool metrics data to generate instructions to increase or decrease the number of connections in a connection pool, preemptively, before shortages or surpluses of connections occur. Corrective engines can analyze performance of the quality of service engines and can, when necessary, instruct the quality of service engines to modify their prediction mechanisms.

Abstract: Systems and methods for preemptive adjustments of connections in a database connection pool are provided. In example embodiments, a number of quality of service engines analyze database connection pool metrics data to generate instructions to increase or decrease the number of connections in a connection pool, preemptively, before shortages or surpluses of connections occur. Corrective engines can analyze performance of the quality of service engines and can, when necessary, instruct the quality of service engines to modify their prediction mechanisms.

Abstract: According to one or more embodiments, a method may include obtaining a connection request to communicate with a database. The method may further include determining a predicted wait time for the connection request. The predicted wait time may include a predicted amount of time until a connection with the database will be available to communicate with the database. The method may further include determining whether to shed the connection request before a connection request timeout time. The determination as to whether to shed the connection request may be based on whether the predicted wait time exceeds the connection request timeout time.

Abstract: According to one or more embodiments, a method may include obtaining a connection request to communicate with a database. The method may further include determining a predicted wait time for the connection request. The predicted wait time may include a predicted amount of time until a connection with the database will be available to communicate with the database. The method may further include determining whether to shed the connection request before a connection request timeout time. The determination as to whether to shed the connection request may be based on whether the predicted wait time exceeds the connection request timeout time.