Abstract: Embodiments of the disclosure provide systems and methods for reducing the capacity used to provide High Availability (HA) and Disaster Recovery (DR) in a distributed computing environment. According to one embodiment, dynamic recovery of a cloud-based resource can comprise setting a current latency value to an initial latency value and handling received requests with the current latency value. Current resource utilization can be detected while requests are being processed and a determination can be made as to whether the detected current resource utilization exceeds a predetermined threshold amount of resource utilization. In response to determining the detected current resource utilization does not exceed the threshold, the current latency amount can be maintained at the initial latency value. In response to determining the detected current resource utilization exceeds the threshold, the current latency value can be adjusted and injected into handling of received client requests.

Abstract: Examples are disclosed for identifying duplicated media content in a plurality of media files. In some examples, according to a media file format, media content sequences may be located and duplicated media content sequences identified. For these examples, at least a portion of the identified duplicated media content sequences may then be deleted or not stored at a storage system. Other examples are described and claimed.

Abstract: Techniques for a data storage cluster and a method for maintaining and updating reliability data and reducing data communication between nodes, are disclosed herein. Each data object is written to a single data zone on a data node within the data storage cluster. Each data object includes one or more data chunks, and the data chunks of a data object are written to a data node in an append-only log format. When parity is determined for a reliability group including the data zone, there is no need to transmit data from other data nodes where the rest of data zones of the reliability group reside. Thus, inter-node data communication for determining reliability data is reduced.

Abstract: Techniques for a data storage cluster and a method for maintaining and updating reliability data and reducing data communication between nodes, are disclosed herein. Each data object is written to a single data zone on a data node within the data storage cluster. Each data object includes one or more data chunks, and the data chunks of a data object are written to a data node in an append-only log format. When parity is determined for a reliability group including the data zone, there is no need to transmit data from other data nodes where the rest of data zones of the reliability group reside. Thus, inter-node data communication for determining reliability data is reduced.

Abstract: Examples are disclosed for identifying duplicated media content in a plurality of media files. In some examples, according to a media file format, media content sequences may be located and duplicated media content sequences identified. For these examples, at least a portion of the identified duplicated media content sequences may then be deleted or not stored at a storage system. Other examples are described and claimed.

Abstract: Techniques for a data storage cluster and a method for maintaining and updating reliability data and reducing data communication between nodes, are disclosed herein. Each data object is written to a single data zone on a data node within the data storage cluster. Each data object includes one or more data chunks, and the data chunks of a data object are written to a data node in an append-only log format. When parity is determined for a reliability group including the data zone, there is no need to transmit data from other data nodes where the rest of data zones of the reliability group reside. Thus, inter-node data communication for determining reliability data is reduced.

Abstract: A storage system provides highly flexible data layouts that can be tailored based on reliability considerations. The system allocates reliability values to logical containers at an upper logical level of the system based, for example, on objectives established by reliability SLOs. Based on the reliability value, the system identifies a specific parity group from a lower physical storage level of the system for storing data corresponding to the logical container. After selecting a parity group, the system allocates the data to physical storage blocks within the parity group. In embodiments, the system attaches the reliability value information to the parity group and the physical storage units storing the data. In this manner, the underlying physical layer has a semantic understanding of reliability considerations related to the data stored at the logical level.

Abstract: A storage system provides highly flexible data layouts that can be tailored based on reliability considerations. The system allocates reliability values to logical containers at an upper logical level of the system based, for example, on objectives established by reliability SLOs. Based on the reliability value, the system identifies a specific parity group from a lower physical storage level of the system for storing data corresponding to the logical container. After selecting a parity group, the system allocates the data to physical storage blocks within the parity group. In embodiments, the system attaches the reliability value information to the parity group and the physical storage units storing the data. In this manner, the underlying physical layer has a semantic understanding of reliability considerations related to the data stored at the logical level.