Abstract: An example method to manage a virtual machine deployment in a cloud environment includes generating a blueprint comprising a blueprint component corresponding to an application storage policy for all endpoints associated with an infrastructure source in the cloud environment, in response to a determination that the application storage policy comprises a first storage policy of a first endpoint among the endpoints, collecting the first storage policy to deploy the virtual machine on the first endpoint according to the first storage policy, or in response to a determination that the application storage policy does not comprise any storage policy of the first endpoint among the endpoints, creating a storage policy of the first endpoint and collecting the created storage policy to deploy the virtual machine on the first endpoint according to the created storage policy.

Abstract: A policy-driven method of migrating a virtual computing resource that is executing an application workload includes the steps of determining that at least one of multiple policies of the application has been violated by the virtual computing resource while executing the workload in a first virtual data center, and responsive to said determining, programmatically performing: (1) searching for a virtual data center to which the virtual computing resource can be migrated, (2) determining that the virtual computing resource will be able to comply with all of the policies of the application while executing the workload if the virtual computing resource is migrated to the second virtual data center, and (3) based on determining the ability to comply, migrating the virtual computing resource across clouds, namely from the first virtual data center to the second virtual data center.

Abstract: An example method to manage a virtual machine deployment in a cloud environment includes generating a blueprint comprising a blueprint component corresponding to an application storage policy for all endpoints associated with an infrastructure source in the cloud environment, in response to a determination that the application storage policy comprises a first storage policy of a first endpoint among the endpoints, collecting the first storage policy to deploy the virtual machine on the first endpoint according to the first storage policy, or in response to a determination that the application storage policy does not comprise any storage policy of the first endpoint among the endpoints, creating a storage policy of the first endpoint and collecting the created storage policy to deploy the virtual machine on the first endpoint according to the created storage policy.

Abstract: A policy-driven method of migrating a virtual computing resource that is executing an application workload includes the steps of determining that at least one of multiple policies of the application has been violated by the virtual computing resource while executing the workload in a first virtual data center, and responsive to said determining, programmatically performing: (1) searching for a virtual data center to which the virtual computing resource can be migrated, (2) determining that the virtual computing resource will be able to comply with all of the policies of the application while executing the workload if the virtual computing resource is migrated to the second virtual data center, and (3) based on determining the ability to comply, migrating the virtual computing resource across clouds, namely from the first virtual data center to the second virtual data center.

Abstract: A scheduler selects an I/O from a session of a pool and updates token buckets associated with resource limits and reserves for the session and the pool and statistics used in determining fair sharing. To select an I/O, the scheduler identifies sessions with a non-empty queue, identifies head I/Os in the queues, computes for the head I/O a deadline using session and pool reserve buckets and a release time using session and pool limit buckets, and selects a head I/O with an earliest deadline that is past the release time. If the deadline of the selected candidate head I/O is in the past, the scheduler transfers the selected head I/O to the tail of the storage device queue. Otherwise, the scheduler selects the pool with the least amount of I/O traffic according to a session fair share estimator.

Abstract: A scheduler selects an I/O from a session of a pool and updates token buckets associated with resource limits and reserves for the session and the pool and statistics used in determining fair sharing. To select an I/O, the scheduler identifies sessions with a non-empty queue, identifies head I/Os in the queues, computes for the head I/O a deadline using session and pool reserve buckets and a release time using session and pool limit buckets, and selects a head I/O with an earliest deadline that is past the release time. If the deadline of the selected candidate head I/O is in the past, the scheduler transfers the selected head I/O to the tail of the storage device queue. Otherwise, the scheduler selects the pool with the least amount of I/O traffic according to a session fair share estimator.