Abstract: A system and method are provided for directing a workload between distributed computing environments. Performance and use data from each of a plurality of computer clusters is monitored on a periodic or continuous basis. The plurality of computers can include a first subset being in a first region and a second subset being in a second region. Each region has known performance characteristics, zone of performance and zone of reliability which is used in distributing a workload or job. A job is received at the system, wherein the system determines a routing for the job to a distributed computing environment, wherein the routing is in response to the obtained performance and use data, and the region encompassing the given computer cluster.

Abstract: Systems and methods are provided for any party in a cloud ecosystem (cloud providers of such resources, the intermediate management software for such resources, and the end user of such resources) to detect and resolve faulty resources synchronously or asynchronously, before said faults adversely affect the users' workloads. The system requests a service or set of one or more resources within a cloud, automatically checking the infrastructure for various faults that would cause it to be non-functional, including pre-defined and user-defined checks, and resolving them before including the infrastructure in the working service cluster of resources. The system presents an API to the user that returns only functional, production-quality resources that are not in a faulty state. An API that tests and resolves bad infrastructure can be registered during the request or a preceding/subsequent API call, removing the need for the end-user to deal with various types of infrastructure faults.

Abstract: A system and method is provided to dynamically optimize the topography of a compute cluster in real time based on the runtime configuration, specified as metadata, of jobs in a queuing or scheduling environment. The system provisions or terminates multiple types of virtualized resources based on the profile of all applications of the jobs in a current queue based on their aggregate runtime configuration specified as requirements and rank expressions within associated metadata. The system will continually request and terminate compute resources as jobs enter and exit the queue, keeping the cluster as minimal as possible while still being optimized to complete all jobs in the queue, optimized for cost, runtime or other metric. End users can specify the runtime requirements of jobs, thereby preventing the user from having to know about the physical profile of the compute cluster to specifically architect their jobs.

Abstract: Systems and methods are provided for any party in a cloud ecosystem (cloud providers of such resources, the intermediate management software for such resources, and the end user of such resources) to detect and resolve faulty resources synchronously or asynchronously, before said faults adversely affect the users' workloads. The system requests a service or set of one or more resources within a cloud, automatically checking the infrastructure for various faults that would cause it to be non-functional, including pre-defined and user-defined checks, and resolving them before including the infrastructure in the working service cluster of resources. The system presents an API to the user that returns only functional, production-quality resources that are not in a faulty state. An API that tests and resolves bad infrastructure can be registered during the request or a preceding/subsequent API call, removing the need for the end-user to deal with various types of infrastructure faults.

Abstract: Systems and methods are provided for any party in a cloud ecosystem (cloud providers of such resources, the intermediate management software for such resources, and the end user of such resources) to detect and resolve faulty resources synchronously or asynchronously, before said faults adversely affect the users' workloads. The system requests a service or set of one or more resources within a cloud, automatically checking the infrastructure for various faults that would cause it to be non-functional, including pre-defined and user-defined checks, and resolving them before including the infrastructure in the working service cluster of resources. The system presents an API to the user that returns only functional, production-quality resources that are not in a faulty state. An API that tests and resolves bad infrastructure can be registered during the request or a preceding/subsequent API call, removing the need for the end-user to deal with various types of infrastructure faults.

Abstract: A system and method are provided for directing a workload between distributed computing environments. Performance and use data from each of a plurality of computer clusters is monitored on a periodic or continuous basis. The plurality of computers can include a first subset being in a first region and a second subset being in a second region. Each region has known performance characteristics, zone of performance and zone of reliability which is used in distributing a workload or job. A job is received at the system, wherein the system determines a routing for the job to a distributed computing environment, wherein the routing is in response to the obtained performance and use data, and the region encompassing the given computer cluster.

Abstract: A system and method is provided to dynamically optimize the topography of a compute cluster in real time based on the runtime configuration, specified as metadata, of jobs in a queuing or scheduling environment. The system provisions or terminates multiple types of virtualized resources based on the profile of all applications of the jobs in a current queue based on their aggregate runtime configuration specified as requirements and rank expressions within associated metadata. The system will continually request and terminate compute resources as jobs enter and exit the queue, keeping the cluster as minimal as possible while still being optimized to complete all jobs in the queue, optimized for cost, runtime or other metric. End users can specify the runtime requirements of jobs, thereby preventing the user from having to know about the physical profile of the compute cluster to specifically architect their jobs.

Abstract: Systems and methods are provided for any party in a cloud ecosystem (cloud providers of such resources, the intermediate management software for such resources, and the end user of such resources) to detect and resolve faulty resources synchronously or asynchronously, before said faults adversely affect the users' workloads. The system requests a service or set of one or more resources within a cloud, automatically checking the infrastructure for various faults that would cause it to be non-functional, including pre-defined and user-defined checks, and resolving them before including the infrastructure in the working service cluster of resources. The system presents an API to the user that returns only functional, production-quality resources that are not in a faulty state. An API that tests and resolves bad infrastructure can be registered during the request or a preceding/subsequent API call, removing the need for the end-user to deal with various types of infrastructure faults.