Abstract: Techniques are described for managing access of executing programs to non-local block data storage. In some situations, a block data storage service uses multiple server storage systems to reliably store network-accessible block data storage volumes that may be used by programs executing on other physical computing systems. A group of multiple server block data storage systems that store block data volumes may in some situations be co-located at a data center, and programs that use volumes stored there may execute on other physical computing systems at that data center. If a program using a volume becomes unavailable, another program (e.g., another copy of the same program) may in some situations obtain access to and continue to use the same volume, such as in an automatic manner in some such situations.

Abstract: Virtual data stores may be sparsely provisioned by virtual data storage services in a manner that controls risk of implementation resource shortages. Relationships between requested data storage space size, data storage server capacity, allocated data storage space size and/or allocated data storage space utilization may be tracked on a per data store, per customer, per data storage server, and/or a per virtual data storage service basis. For each such basis, a set of constraints may be specified to control the relationships. The set of constraints may be enforced during implementation resource allocation, and by migration of data storage space portions to different implementation resources as part of a sparse provisioning load balancing. Sparse provisioning details may be made explicit to virtual data storage service customers to varying degrees including explicit, aggregate on a per customer basis, and aggregate on a per virtual data storage service basis.

Abstract: Techniques are described for managing access of executing programs to non-local block data storage. In some situations, a block data storage service uses multiple server storage systems to reliably store block data that may be accessed over one or more networks by programs executing on other physical computing systems. Users may create block data storage volumes that are each stored by at least two of the server block data storage systems, and may initiate use of such volumes by one or more executing programs, such as in a reliable manner by enabling an automatic switch to a second volume copy if a first volume copy becomes unavailable. A group of multiple server block data storage systems that store block data volumes may in some situations be co-located at a data center, and programs that use volumes stored there may execute on other physical computing systems at that data center.

Abstract: Techniques are described for managing access of executing programs to non-local block data storage. In some situations, a block data storage service uses multiple server storage systems to reliably store network-accessible block data storage volumes that may be used by programs executing on other physical computing systems. A group of multiple server block data storage systems that store block data volumes may in some situations be co-located at a data center, and programs that use volumes stored there may execute on other physical computing systems at that data center. If a program using a volume becomes unavailable, another program (e.g., another copy of the same program) may in some situations obtain access to and continue to use the same volume, such as in an automatic manner in some such situations.

Abstract: Techniques are described for managing access of executing programs to non-local block data storage. In some situations, a block data storage service uses multiple server storage systems to reliably store copies of network-accessible block data storage volumes that may be used by programs executing on other physical computing systems, and snapshot copies of some volumes may also be stored (e.g., on remote archival storage systems). A group of multiple server block data storage systems that store block data volumes may in some situations be co-located at a data center, and programs that use volumes stored there may execute on other computing systems at that data center, while the archival storage systems may be located outside the data center. The snapshot copies of volumes may be used in various ways, including to allow users to obtain their own copies of other users' volumes (e.g., for a fee).

Abstract: Techniques are described for managing access of executing programs to non-local block data storage. In some situations, a block data storage service uses multiple server storage systems to reliably store block data that may be accessed over one or more networks by programs executing on other physical computing systems. Users may create block data storage volumes that are each stored by at least two of the server block data storage systems, and may initiate use of such volumes by one or more executing programs, such as in a reliable manner by enabling an automatic switch to a second volume copy if a first volume copy becomes unavailable. A group of multiple server block data storage systems that store block data volumes may in some situations be co-located at a data center, and programs that use volumes stored there may execute on other physical computing systems at that data center.

Abstract: Techniques are described for managing access of executing programs to non-local block data storage. In some situations, a block data storage service uses multiple server storage systems to reliably store copies of network-accessible block data storage volumes that may be used by programs executing on other physical computing systems, and snapshot copies of some volumes may also be stored (e.g., on remote archival storage systems). A group of multiple server block data storage systems that store block data volumes may in some situations be co-located at a data center, and programs that use volumes stored there may execute on other computing systems at that data center, while the archival storage systems may be located outside the data center. The snapshot copies of volumes may be used in various ways, including to allow users to obtain their own copies of other users' volumes (e.g., for a fee).

Abstract: Techniques are described for managing communications between multiple intercommunicating computing nodes, such as multiple virtual machine nodes hosted on one or more physical computing machines or systems. In some situations, users may specify groups of computing nodes and optionally associated access policies for use in the managing of the communications for those groups, such as by specifying which source nodes are allowed to transmit data to particular destinations nodes. In addition, determinations of whether initiated data transmissions from source nodes to destination nodes are authorized may be dynamically negotiated for and recorded for later use in automatically authorizing future such data transmissions without negotiation. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.

Abstract: Techniques are described for managing communications between multiple intercommunicating computing nodes, such as multiple virtual machine nodes hosted on one or more physical computing machines or systems. In some situations, users may specify groups of computing nodes and optionally associated access policies for use in the managing of the communications for those groups, such as by specifying which source nodes are allowed to transmit data to particular destinations nodes. In addition, determinations of whether initiated data transmissions from source nodes to destination nodes are authorized may be dynamically negotiated for and recorded for later use in automatically authorizing future such data transmissions without negotiation. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.

Abstract: Techniques are described for managing communications between multiple intercommunicating computing nodes, such as multiple virtual machine nodes hosted on one or more physical computing machines or systems. In some situations, users may specify groups of computing nodes and optionally associated access policies for use in the managing of the communications for those groups, such as by specifying which source nodes are allowed to transmit data to particular destinations nodes. In addition, determinations of whether initiated data transmissions from source nodes to destination nodes are authorized may be dynamically negotiated for and recorded for later use in automatically authorizing future such data transmissions without negotiation. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.

Abstract: Input and output (I/O) operations performed by a data storage device are managed dynamically to balance aspects such as throughput and latency. Sequential read and write requests are sent to a data storage device whereby the corresponding operations are performed without time delay due to extra disk revolutions. In order to minimize latency, particularly for read operations, random read and write requests are held in a queue upstream of an I/O controller of the data storage device until the buffer of the data storage device is empty. The queued requests can be reordered when a higher priority request is received, improving the overall latency for specific requests. An I/O scheduler of a data server is still able to use any appropriate algorithm to order I/O requests, such as by prioritizing reads over writes as long as the writes do not back up in the I/O queue beyond a certain threshold.

Abstract: Input and output (I/O) operations performed by a data storage device are managed dynamically to balance aspects such as throughput and latency. Sequential read and write requests are sent to a data storage device whereby the corresponding operations are performed without time delay due to extra disk revolutions. In order to minimize latency, particularly for read operations, random read and write requests are held in a queue upstream of an I/O controller of the data storage device until the buffer of the data storage device is empty. The queued requests can be reordered when a higher priority request is received, improving the overall latency for specific requests. An I/O scheduler of a data server is still able to use any appropriate algorithm to order I/O requests, such as by prioritizing reads over writes as long as the writes do not back up in the I/O queue beyond a certain threshold.

Abstract: Techniques are described for managing the execution of programs on multiple computing systems, such as computing systems organized into multiple groups. A program execution service manages the program execution on behalf of multiple customers or other users, and selects appropriate computing systems to execute one or more instances of program, such as based in part on locations of one or more previously stored copies of the program from which copies of the program to execute may be acquired. For example, in some situations the selection of an appropriate computing system to execute an instance of a program is based in part on physical or logical proximity to other resources, such as stored copies of the program, executing copies of the program, and/or available computing systems.

Abstract: Techniques are described for managing access of executing programs to non-local block data storage. In some situations, a block data storage service uses multiple server storage systems to reliably store network-accessible block data storage volumes that may be used by programs executing on other physical computing systems. A group of multiple server block data storage systems that store block data volumes may in some situations be co-located at a data center, and programs that use volumes stored there may execute on other physical computing systems at that data center. If a program using a volume becomes unavailable, another program (e.g., another copy of the same program) may in some situations obtain access to and continue to use the same volume, such as in an automatic manner in some such situations.

Abstract: Techniques are described for managing access of executing programs to non-local block data storage. In some situations, a block data storage service uses multiple server storage systems to reliably store block data that may be accessed over one or more networks by programs executing on other physical computing systems. Users may create block data storage volumes that are each stored by at least two of the server block data storage systems, and may initiate use of such volumes by one or more executing programs, such as in a reliable manner by enabling an automatic switch to a second volume copy if a first volume copy becomes unavailable. A group of multiple server block data storage systems that store block data volumes may in some situations be co-located at a data center, and programs that use volumes stored there may execute on other physical computing systems at that data center.

Abstract: Customers of a shared-resource environment can provision resources in a fine-grained manner that meets specific performance requirements. A customer can provision a data volume with a committed rate of Input/Output Operations Per Second (IOPS) and pay only for that commitment (plus any overage), and the amount of storage requested. The customer will then at any time be able to complete at least the committed rate of IOPS. If the customer generates submissions at a rate that exceeds the committed rate, the resource can still process at the higher rate when the system is not under pressure. Even under pressure, the system will deliver at least the committed rate. Multiple customers can be provisioned on the same resource, and more than one customer can have a committed rate on that resource. Customers without committed or guaranteed rates can utilize the uncommitted portion, or committed portions that are not being used.

Abstract: Commitments against various resources can be dynamically adjusted for customers in a shared-resource environment. A customer can provision a data volume with a committed rate of Input/Output Operations Per Second (IOPS) and pay only for that commitment (plus any overage), for example, as well as the amount of storage requested. The customer can subsequently adjust the committed rate of IOPS by submitting an appropriate request, or the rate can be adjusted automatically based on any of a number of criteria. Data volumes for the customer can be migrated, split, or combined in order to provide the adjusted rate. The interaction of the customer with the data volume does not need to change, independent of adjustments in rate or changes in the data volume, other than the rate at which requests are processed.

Abstract: Techniques are described for managing access of executing programs to non-local block data storage. In some situations, a block data storage service uses multiple server storage systems to reliably store network-accessible block data storage volumes that may be used by programs executing on other physical computing systems. A group of multiple server block data storage systems that store block data volumes may in some situations be co-located at a data center, and programs that use volumes stored there may execute on other physical computing systems at that data center. If a program using a volume becomes unavailable, another program (e.g., another copy of the same program) may in some situations obtain access to and continue to use the same volume, such as in an automatic manner in some such situations.

Abstract: Techniques are described for managing access of executing programs to non-local block data storage. In some situations, a block data storage service uses multiple server storage systems to reliably store block data that may be accessed over one or more networks by programs executing on other physical computing systems. Users may create block data storage volumes that are each stored by at least two of the server block data storage systems, and may initiate use of such volumes by one or more executing programs, such as in a reliable manner by enabling an automatic switch to a second volume copy if a first volume copy becomes unavailable. A group of multiple server block data storage systems that store block data volumes may in some situations be co-located at a data center, and programs that use volumes stored there may execute on other physical computing systems at that data center.

Abstract: Techniques are described for managing execution of programs on multiple computing systems, such as based at least in part of user-specified constraints. For example, constraints related to execution of a program may be based on a desired relative location of a host computing system to execute a copy of the program with respect to an indicated target (e.g., computing systems executing other copies of the program or copies of another indicated program), on particular geographic locations, and/or on factors not based on location (e.g., cost of use of a particular computing system, capabilities available from a particular computing system, etc.). Some or all of the multiple computing systems may be part of a program execution service for executing multiple programs on behalf of multiple users, and each may provide multiple virtual machines that are each capable of executing one or more programs for one or more users.