Abstract: In some implementations, a computing device may provide an indication of availability of a producer workload, located on a first virtual private cloud (VPC) or being a cloud application programming interface (API) on a first cloud, as a virtual private endpoint (VPE) to a consumer workload in a second VPC on a second cloud that is different from the first cloud. The computing device may receive, from the consumer workload and based at least in part on the indication of availability, a request for access to the producer workload. The computing device may establish, based at least in part on the request, the producer workload as the VPE in the second VPC via a link between the first cloud and the second cloud.

Abstract: A heterogeneous resource reservation (HRR) manager configured to classify historical application requests from a past time interval for a first workload to generate labeled historical application requests. The HRR manager further configured to generate a forecast based on the labeled historical application requests and for predicting future application requests for the first workload for a future time interval and calculate a joint plan based on the forecast. The joint plan including a set of virtual resources, a set of billing contracts, and a set of load balancer weights. The HRR manager further configured to implement the joint plan for a distributed computing workload during the future time interval.

Abstract: A heterogeneous resource reservation (HRR) manager configured to classify historical application requests from a past time interval for a first workload to generate labeled historical application requests. The HRR manager further configured to generate a forecast based on the labeled historical application requests and for predicting future application requests for the first workload for a future time interval and calculate a joint plan based on the forecast. The joint plan including a set of virtual resources, a set of billing contracts, and a set of load balancer weights. The HRR manager further configured to implement the joint plan for a distributed computing workload during the future time interval.

Abstract: Methods, computing systems and computer program products implement embodiments of the present invention that include defining, for a request processing system, a first homogeneous auto-scaling group including a first monitored resource, a first set of processing systems, a first minimum threshold, a first maximum threshold, and a first system configuration. Subsequent to defining the first homogeneous auto-scaling group, a second auto-scaling group is defined for the request processing system, the second auto-scaling group including a second monitored resource different from the first monitored resource, a second set of processing systems, a second minimum threshold, a second maximum threshold, and a second system configuration different from the first system configuration. In embodiments of the present invention, a load balancer for the request processing system manages the first and the second sets of processing systems as a single heterogeneous auto-scaling group.