Abstract: Data volumes hosted for customers in a multi-tenant environment can be moved advantageously throughout the environment to improve performance and reduce cost. A data volume can serve I/O for a virtual machine instance, and it can be advantageous for the virtual machine and the data volume to be in the same network locality, or share at least some of the same network state and interconnection. Since there is limited capacity in a network locality, data volumes not attached to virtual machines can be moved to other locations in the environment. This can include moving data volumes to other local network topologies or snapshotting data volumes and writing the snapshots to another storage service. If the data volume is again needed for I/O, the data volume can moved, allocated, or reattached as necessary.

Abstract: A distributed system may implement analyzing resource placement fragmentation for capacity planning. Capacity planning may determine when, where, and how much capacity to implement for a distributed system that hosts resources. Placement constraints for resources may, over time, create fragmentation or stranded capacity which is available yet unusable to host new resources. Analyzing capacity fragmentation across a distributed system may allow a determination of available capacity that is actually available to host additional resources. In some embodiments, future resource placements may be estimated in order to perform capacity fragmentation analysis to determine available capacity.

Abstract: A request to create a volume to store data is received. A block within the storage node is selected, dependent at least in part on metadata indicating regions of available storage space in a storage node, to associate with a volume. Information is generated that includes an address to the block. A second computer system is determined to lacks the address to the block. The second computer system is enabled, by providing at least a portion of the information to the second computer system, to perform an operation to the block.

Abstract: Data volumes hosted for customers in a multi-tenant environment can be moved advantageously throughout the environment to improve performance and reduce cost. A data volume can serve I/O for a virtual machine instance, and it can be advantageous for the virtual machine and the data volume to be in the same network locality, or share at least some of the same network state and interconnection. Since there is limited capacity in a network locality, data volumes not attached to virtual machines can be moved to other locations in the environment. This can include moving data volumes to other local network topologies or snapshotting data volumes and writing the snapshots to another storage service. If the data volume is again needed for I/O, the data volume can moved, allocated, or reattached as necessary.

Abstract: A distributed system may implement analyzing resource placement fragmentation for capacity planning Capacity planning may determine when, where, and how much capacity to implement for a distributed system that hosts resources. Placement constraints for resources may, over time, create fragmentation or stranded capacity which is available yet unusable to host new resources. Analyzing capacity fragmentation across a distributed system may allow a determination of available capacity that is actually available to host additional resources. In some embodiments, future resource placements may be estimated in order to perform capacity fragmentation analysis to determine available capacity.

Abstract: A first location in one or more storage nodes is determined, with the first location being associated with a first block of a plurality of blocks associated with a storage volume. First information that maps the first block to the first location is generated. At least a portion of data is obtained from the first block at the first location. A second location in the one or more storage nodes is determined, with the second location being associated with a second block. Second information that maps the second block to the second location is included in the first information. A second computer system, different from the first computer system, is enabled, by providing at least a portion of the first information, to perform an operation to the storage volume.

Abstract: A distributed system may deploy infrastructure units according to resource hosting constraints. Additional infrastructure units, or infrastructure units to be redeployed, may be identified for deployment. State information describing the deployment of infrastructure units currently deployed amongst different infrastructure localities of a distributed system may be evaluated for different possible deployments according to resource hosting constraints. Possible deployments that optimize or increase resource hosting capacity in the distributed system within the resource hosting constraints may be determined. Deployment at those infrastructure localities of the determined possible deployments may be directed.

Abstract: A distributed system may implement dynamic resource creation for connecting resources. Resource creation requests may be received for resources which are accessed by other resources hosted in a distributed system. An intention for the creation request is stored to perform the creation request. At a subsequent time, a request to connect another resource to the resource of the creation request is received. An infrastructure locality for the other resource may then be identified and utilized to determine a placement location for the resource. The resource may then be created at the placement location according to the stored intention. The resource may then be connected with the other resource for access.

Abstract: A system and method for providing sets of partition placements, the system and method including determining a first set of placements for a first set of partitions first set of partitions of a volume based at least in part on a set of constraints, and placing the first set of partitions based at least in part on the first set of placements. The system and method further includes determining a second set of placements for a second set of partitions of the volume based at least in part on the first set of placements and the set of constraints, the second set of partitions being a replica of the first set of partitions, and placing the second set of partitions based at least in part on the second set of placements.

Abstract: A system and method for providing sets of partition placements, the system and method including, receiving at least one placement request for a set of partitions of a volume. Based at least in part on counts of pairs of partitions hosted by pairs of computing devices, the system and method further includes determining how suitable the pairs of computing devices are for placement of partitions of the set of partitions, generating a set of placements based at least in part on the determination, and providing the set of placements in response to the at least one placement request.

Abstract: A remirror buffer can be used in failover situations so as to backup storage volumes in a service provider. The remirror buffer is dynamically resized to meet current usage metrics captured from a data center. A risk boundary can be defined through which resource hosts are grouped together so as to determine the usage metrics. The risk boundary can be based on a topology of the data center, such as a room/rack/sharing of power supplies, or other characteristics of the resource hosts.

Abstract: A distributed system may implement opportunistic resource migration to optimize resource placement. Resources may be placed amongst different resource hosts of a distributed system. An evaluation of the current placement may be performed according placement criteria that improve placement of the resources at the distributed system. Based on the evaluation, the prospective migration of resources that exceed an improvement threshold may be identified as candidate resources to migrate. Migration for the candidate resources may be opportunistically performed. In some embodiments, a priority may be assigned to the candidate resources according to which the candidate resources are selected for performing migration.