Abstract: In various implementations, methods and systems resource balancing in a distributed computing environment are provided. A client defined resource metric is received that represents a resource of nodes of the cloud computing platform. A placement plan for job instances of service applications is generated. The placement plan includes one or more movements that are executable to achieve a target placement of the job instances on the nodes. It is determined that the placement plan complies with placement rules. Each placement rule dictates whether a given job instance of the job instances is suitable for placement on a given node of the nodes. The placement plan is executed based on determining that the target placement of the job instances improves balance of resources across the nodes of the cloud computing platform based on the resource represented by the client defined resource metric.

Abstract: In various implementations, methods and systems resource balancing in a distributed computing environment are provided. A client defined resource metric is received that represents a resource of nodes of the cloud computing platform. A placement plan for job instances of service applications is generated. The placement plan includes one or more movements that are executable to achieve a target placement of the job instances on the nodes. It is determined that the placement plan complies with placement rules. Each placement rule dictates whether a given job instance of the job instances is suitable for placement on a given node of the nodes. The placement plan is executed based on determining that the target placement of the job instances improves balance of resources across the nodes of the cloud computing platform based on the resource represented by the client defined resource metric.

Abstract: A resource balancer for a cluster of nodes in a cloud computing system includes a load calculation module that receives load reports for respective load metrics associated with the nodes, wherein the load reports are indicative of respective loads on a plurality of resources provided by the nodes, calculates, based on the received load reports, an expected distribution of loads across the nodes for each load metric, and calculates, based on the expected distribution of loads, probabilities that each of the load metrics will exceed a respective predetermined capacity for each node. A load balancing module selectively balances, based on the calculated probabilities, the loads on the resources provided by the nodes.

Abstract: A resource balancer for a cluster of nodes in a cloud computing system includes a load calculation module that receives load reports for respective load metrics associated with the nodes, wherein the load reports are indicative of respective loads on a plurality of resources provided by the nodes, calculates, based on the received load reports, an expected distribution of loads across the nodes for each load metric, and calculates, based on the expected distribution of loads, probabilities that each of the load metrics will exceed a respective predetermined capacity for each node. A load balancing module selectively balances, based on the calculated probabilities, the loads on the resources provided by the nodes.

Abstract: In various implementations, methods and systems resource balancing in a distributed computing environment are provided. A client defined resource metric is received that represents a resource of nodes of the cloud computing platform. A placement plan for job instances of service applications is generated. The placement plan includes one or more movements that are executable to achieve a target placement of the job instances on the nodes. It is determined that the placement plan complies with placement rules. Each placement rule dictates whether a given job instance of the job instances is suitable for placement on a given node of the nodes. The placement plan is executed based on determining that the target placement of the job instances improves balance of resources across the nodes of the cloud computing platform based on the resource represented by the client defined resource metric.

Abstract: A chlorinated rubber composition which is resistant to various fluids such as transmission fluids comprises a blend of a chlorinated polyethylene elastomer, an ethylene acrylic elastomer and/or polyacrylic rubbers, and optionally a chlorosulfonated polyethylene. The rubber composition has many uses such as a tube and generally contains various additives such as fillers, plasticizers, vulcanizing agents, and the like. A heat resistant rubber composition comprises a blend of a chlorinated polyethylene elastomer, an ethylene-acrylic elastomer and/or polyacrylic rubbers, an ethylene-octene copolymer, and an ethylene-propylene-diene terpolymer, and the same can be used as a cover or jacket as on the above chlorinated rubber tube.