Abstract: We propose a rule-based system, whereby API requests issued by an application program are screened by policy rules before being acted on by an API, where the policy rules are sensitive to the runtime environment. A policy manager is arranged to screen API requests transmitted by the application program against a set of rules to decide whether a particular API request should be allowed to proceed to the API unchanged or be trapped. Trapping an API request causes an API response to be generated according to the rule that trapped the API request, and then transmission of the generated API response to the application program. This allows dynamic modification of the application program's behavior by the customer in order to respond to changes in the server runtime environment without having to modify the application program by configuring one or more policy rules to influence API request handling.

Abstract: Generating a performance policy for a server. A plurality of system metrics of a first server is monitored, and a benchmark for the plurality of system metrics based on the monitored plurality of system metrics is stored. The benchmark indicates desirable system metrics of the first server. An operating policy for a second server is generated from the stored benchmark. The operating policy includes desirable system metrics of the second server based on the desirable system metrics of the first server.

Abstract: Generating a performance policy for a server. A plurality of system metrics of a first server is monitored, and a benchmark for the plurality of system metrics based on the monitored plurality of system metrics is stored. The benchmark indicates desirable system metrics of the first server. An operating policy for a second server is generated from the stored benchmark. The operating policy includes desirable system metrics of the second server based on the desirable system metrics of the first server.

Abstract: A search facility is used to predict the impact of change on events detected in application logic, where the change may involve a computing resource used by or referenced by the application logic and/or by event detection logic. The search may be performed prior to making a change, in order to judge potential impact of the change, or after the change has been made. The search makes the prediction by evaluating semantics of conditions that specify when and/or and how an event will be detected at run-time.

Abstract: A search facility is used to predict the impact of change on events detected in application logic, where the change may involve a computing resource used by or referenced by the application logic and/or by event detection logic. The search may be performed prior to making a change, in order to judge potential impact of the change, or after the change has been made. The search makes the prediction by evaluating semantics of conditions that specify when and/or and how an event will be detected at run-time.

Abstract: A search facility is used to predict the impact of change on events detected in application logic, where the change may involve a computing resource used by or referenced by the application logic and/or by event detection logic. The search may be performed prior to making a change, in order to judge potential impact of the change, or after the change has been made. The search makes the prediction by evaluating semantics of conditions that specify when and/or how an event will be detected at run-time.

Abstract: A search facility is used to predict the impact of change on events detected in application logic, where the change may involve a computing resource used by or referenced by the application logic and/or by event detection logic. The search may be performed prior to making a change, in order to judge potential impact of the change, or after the change has been made. The search makes the prediction by evaluating semantics of conditions that specify when and/or and how an event will be detected at run-time.

Abstract: A search facility is used to predict the impact of change on events detected in application logic, where the change may involve a computing resource used by or referenced by the application logic and/or by event detection logic. The search may be performed prior to making a change, in order to judge potential impact of the change, or after the change has been made. The search makes the prediction by evaluating semantics of conditions that specify when and/or and how an event will be detected at run-time.

Abstract: A search facility is used to predict the impact of change on events detected in application logic, where the change may involve a computing resource used by or referenced by the application logic and/or by event detection logic. The search may be performed prior to making a change, in order to judge potential impact of the change, or after the change has been made. The search makes the prediction by evaluating semantics of conditions that specify when and/or and how an event will be detected at run-time.

Abstract: A search facility is used to predict the impact of change on events detected in application logic, where the change may involve a computing resource used by or referenced by the application logic and/or by event detection logic. The search may be performed prior to making a change, in order to judge potential impact of the change, or after the change has been made. The search makes the prediction by evaluating semantics of conditions that specify when and/or and how an event will be detected at run-time.

Abstract: A search facility is used to predict the impact of change on events detected in application logic, where the change may involve a computing resource used by or referenced by the application logic and/or by event detection logic. The search may be performed prior to making a change, in order to judge potential impact of the change, or after the change has been made. The search makes the prediction by evaluating semantics of conditions that specify when and/or and how an event will be detected at run-time.

Abstract: System-managed duplexing of coupling facility structures. A plurality of instances of coupling facility structures are maintained in a plurality of coupling facilities. Duplexing processing associated with the plurality of instances is managed by one or more operating systems, making many of the steps associated with duplexing transparent to the exploiters of the coupling facility structures. System-managed duplexing provides high availability for coupling facility structure data via a robust recovery mechanism (i.e., duplexing failover).

Abstract: Heuristics are employed to dynamically determine whether a given request is to be driven synchronously or asynchronously. The average synchronous service time associated with previously processed requests is monitored and used, in real-time, along with other information, to determine whether the given request is to be driven synchronously or asynchronously.

Abstract: System-managed duplexing of coupling facility structures. A plurality of instances of coupling facility structures are maintained in a plurality of coupling facilities. Duplexing processing associated with the plurality of instances is managed by one or more operating systems, making many of the steps associated with duplexing transparent to the exploiters of the coupling facility structures. System-managed duplexing provides high availability for coupling facility structure data via a robust recovery mechanism (i.e., duplexing failover).

Abstract: System-managed duplexing of coupling facility structures. A plurality of instances of coupling facility structures are maintained in a plurality of coupling facilities. Duplexing processing associated with the plurality of instances is managed by one or more operating systems, making many of the steps associated with duplexing transparent to the exploiters of the coupling facility structures. System-managed duplexing provides high availability for coupling facility structure data via a robust recovery mechanism (i.e., duplexing failover).

Abstract: System-managed duplexing of coupling facility structures. A plurality of instances of coupling facility structures are maintained in a plurality of coupling facilities. Duplexing processing associated with the plurality of instances is managed by one or more operating systems, making many of the steps associated with duplexing transparent to the exploiters of the coupling facility structures. System-managed duplexing provides high availability for coupling facility structure data via a robust recovery mechanism (i.e., duplexing failover).

Abstract: Heuristics are employed to dynamically determine whether a given request is to be driven synchronously or asynchronously. The average synchronous service time associated with previously processed requests is monitored and used, in real-time, along with other information, to determine whether the given request is to be driven synchronously or asynchronously.