Abstract: In accordance with an embodiment, described herein are systems and methods for automatic block storage volume tuning by simulating usage characteristics for data/block volumes. The block storage performance associated with usage by a cloud instance of a block volume can be simulated, and the manner in which data is stored or cached, for example within a combination of SSD/NVMe block storage and/or HDD object storage, can be automatically adjusted, for example to associate the block volume with a particular volume performance tier. The described approach allows the system to tune block volume performance in a dynamic manner, without further manual input from a user—the volume performance can be automatically increased when the user needs it, and otherwise reduced down to save costs (both for the user and the cloud provider). A user can enable tuning on a particular block volume, and thereafter automatically receive appropriate price/performance characteristics.

Abstract: In accordance with an embodiment, described herein are systems and methods for providing tiered data storage in cloud infrastructure environments. A data storage service (block store) is adapted to automatically adjust the manner by which the data for a data volume or block volume (data/block volume), associated with a cloud instance, can be stored to meet the requirements of a performance tier. For example, responsive to selection of a particular performance tier, the storage of the data/block volume can be allocated between a first type of data storage associated with a first performance characteristics; and a second type of data storage associated with a second performance characteristics. A graphical user interface enables configuring data/block volumes to use particular performance tiers, and/or to support automatic tuning.

Abstract: In accordance with an embodiment, described herein are systems and methods for automatic block storage volume tuning by simulating usage characteristics for data/block volumes. The block storage performance associated with usage by a cloud instance of a block volume can be simulated, and the manner in which data is stored or cached, for example within a combination of SSD/NVMe block storage and/or HDD object storage, can be automatically adjusted, for example to associate the block volume with a particular volume performance tier. The described approach allows the system to tune block volume performance in a dynamic manner, without further manual input from a user—the volume performance can be automatically increased when the user needs it, and otherwise reduced down to save costs (both for the user and the cloud provider). A user can enable tuning on a particular block volume, and thereafter automatically receive appropriate price/performance characteristics.

Abstract: In accordance with an embodiment, described herein are systems and methods for automatic block storage volume tuning by simulating usage characteristics for data/block volumes. The block storage performance associated with usage by a cloud instance of a block volume can be simulated, and the manner in which data is stored or cached, for example within a combination of SSD/NVMe block storage and/or HDD object storage, can be automatically adjusted, for example to associate the block volume with a particular volume performance tier. The described approach allows the system to tune block volume performance in a dynamic manner, without further manual input from a user—the volume performance can be automatically increased when the user needs it, and otherwise reduced down to save costs (both for the user and the cloud provider). A user can enable tuning on a particular block volume, and thereafter automatically receive appropriate price/performance characteristics.

Abstract: In accordance with an embodiment, described herein are systems and methods for automatic block storage volume tuning by simulating usage characteristics for data/block volumes. The block storage performance associated with usage by a cloud instance of a block volume can be simulated, and the manner in which data is stored or cached, for example within a combination of SSD/NVMe block storage and/or HDD object storage, can be automatically adjusted, for example to associate the block volume with a particular volume performance tier. The described approach allows the system to tune block volume performance in a dynamic manner, without further manual input from a user—the volume performance can be automatically increased when the user needs it, and otherwise reduced down to save costs (both for the user and the cloud provider). A user can enable tuning on a particular block volume, and thereafter automatically receive appropriate price/performance characteristics.

Abstract: In accordance with an embodiment, described herein are systems and methods for automatic block storage volume tuning by simulating usage characteristics for data/block volumes. The block storage performance associated with usage by a cloud instance of a block volume can be simulated, and the manner in which data is stored or cached, for example within a combination of SSD/NVMe block storage and/or HDD object storage, can be automatically adjusted, for example to associate the block volume with a particular volume performance tier. The described approach allows the system to tune block volume performance in a dynamic manner, without further manual input from a user—the volume performance can be automatically increased when the user needs it, and otherwise reduced down to save costs (both for the user and the cloud provider). A user can enable tuning on a particular block volume, and thereafter automatically receive appropriate price/performance characteristics.

Abstract: In accordance with an embodiment, described herein are systems and methods for providing tiered data storage in cloud infrastructure environments. A data storage service (block store) is adapted to automatically adjust the manner by which the data for a data volume or block volume (data/block volume), associated with a cloud instance, can be stored to meet the requirements of a performance tier. For example, responsive to selection of a particular performance tier, the storage of the data/block volume can be allocated between a first type of data storage associated with a first performance characteristics; and a second type of data storage associated with a second performance characteristics. A graphical user interface enables configuring data/block volumes to use particular performance tiers, and/or to support automatic tuning.

Abstract: Various embodiments are directed to generating video data using temporally offset image data samples having disparate exposure times. Synthetic samples are generated for each of the pixels at a particular time period by computing, for each synthetic sample, a combined intensity of the captured samples that fall within the time period. Synthetic samples from adjacent pixels are grouped and image data in different groups is compared to identify matching groups. Video frames are constructed by combining image data from the captured samples based upon the matched images.

Abstract: Various embodiments are directed to generating video data using temporally offset image data samples having disparate exposure times. Synthetic samples are generated for each of the pixels at a particular time period by computing, for each synthetic sample, a combined intensity of the captured samples that fall within the time period. Synthetic samples from adjacent pixels are grouped and image data in different groups is compared to identify matching groups. Video frames are constructed by combining image data from the captured samples based upon the matched images.