Abstract: Methods, systems, and computer-readable storage media for adaptive application server request balancing. An example method includes receiving, from a load balancer, an application request for a first application at a first application server. In response to determining that a complexity value for the application request is greater than a complexity value threshold and that an occupancy value for the first application server is greater than an occupancy value threshold, the application request is provided to a global task queue that is accessible by the first application server and other application servers. A notification is received from a second application server of a completion of the application request by the second application server. A completion result of the completion of the application request by the second application server is retrieved from a global results queue and the completion result is provided to the first application in response to the application request.

Abstract: System computing resources are dynamically managed by a resource management layer together with resource server pool. A group monitor collects data of server operation (e.g., CPU usage, memory consumption, queue size) in a particular group (e.g., customer-facing servers, job servers). The group monitor: calculates a weighted score for each server, sorts the scores of each server, maintains a sequence of scores, and periodically reports the score list to a resource manager. When an incoming request is directed to a particular server group, the group monitor redirects the request to a lowest-scoring server, and recalculates/sorts the score list. The resource manager monitors and throttles the servers in each group. Where servers in a group are experiencing high workload, the manager adds to the group server(s) from the resource pool. Conversely, where server group members are experiencing a low workload, the manager removes the lowest scoring server(s) to the resource pool.

Abstract: System computing resources are dynamically managed by a resource management layer together with resource server pool. A group monitor collects data of server operation (e.g., CPU usage, memory consumption, queue size) in a particular group (e.g., customer-facing servers, job servers). The group monitor: calculates a weighted score for each server, sorts the scores of each server, maintains a sequence of scores, and periodically reports the score list to a resource manager. When an incoming request is directed to a particular server group, the group monitor redirects the request to a lowest-scoring server, and recalculates/sorts the score list. The resource manager monitors and throttles the servers in each group. Where servers in a group are experiencing high workload, the manager adds to the group server(s) from the resource pool. Conversely, where server group members are experiencing a low workload, the manager removes the lowest scoring server(s) to the resource pool.

Abstract: A cloud computing system receives a plurality of requests originating from a plurality of tenants. Thereafter, a load balancer forming part of the cloud computing system dispatches each request to one of a plurality of groups of servers based on a group mapping table configured to optimize a cache hit ratio. Each group of servers includes a plurality of servers dispatching each request to one of the plurality of servers within each group of servers. The cloud computing system provides responses to the requests to the respective tenants as generated by the respective servers within the respective groups of servers. The group mapping table can be generated by monitoring historical request statistics for each of the tenants, monitoring current resource consumption by the plurality of groups of servers when handling requests from the tenants, and associating each tenant with one of the groups of servers based on such monitoring.

Abstract: A system, a method, and a computer program product for detection and extraction of data are disclosed. A query containing a filtering parameter for extracting changed data from a plurality of resources is executed. Using the filtering parameter, first data in the plurality of resources is identified. Based on the identified first data, second data stored in the plurality of resources and associated with the identified first data is identified. The identified first data is contained in a first resource in the plurality of resources and the second data is contained in a second resource in the plurality of resources. Based on the filtering parameter, a determination is made whether at least one of the identified first data and the identified second data contain at least one change. At least one of the identified first data and the identified second data from the plurality of resources is retrieved.