Sap Se

Dabin Feng

Xia Yu

Hui Li

Chen Feng

Wanshun Zhang

Zhen Zhang

Baolin He

Neng Gan

Methods, systems, and computer-readable storage media for receiving, from a first entity, a first call, the call being received by a middleware client of a second entity, storing a set of headers associated with a workflow in a request context holder of the middleware client, and determining that a second call is to be executed from the middleware client of the second entity for the workflow, and in response: reading, by a client of the middleware client, the set of headers associated with the workflow, including the headers in a request of the second call, determining an endpoint for the second call, and transmitting the second call for receipt at the endpoint.

Middleware for communication between microservices and monolithic application

Methods, systems, and computer-readable storage media for receiving a request through a web services API, the request comprising a query to query a database system, retrieving a set of weights that is specific to the web services, determining a factor score for each impact factor in a set of impact factors to provide a set of factor scores, providing a score total for the query based on the set of weights and the set of factor scores, returning a score response including the total score and at least one query suggestion, and receiving a modified request through the web services API, the modified request including the query modified to include at least a portion of the at least one query suggestion.

Protecting cloud systems using request scores

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.

Adaptive application server request balancing

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.

Dynamic management of system computing resources

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.

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Shanghai, China

Dabin Feng