Abstract: Fragmented data on a storage device may be additionally stored in a cache. A cache weight for determining storage of a data unit can be determined. For example, a computing device can receive storage device characteristics from a storage device. A data unit comprising multiple fragments may be stored on the storage device. The computing device can receive data unit characteristics from the storage device. The computing device can determine a cache weight for the data unit. The computing device may output the cache weight for determining storage of the data unit in a cache.

Abstract: An example method may include receiving, in a virtualized execution environment, a data access request from a storage system, identifying, in view of a virtualized execution image associated with the virtualized execution environment, an application running in the virtualized execution environment, generating a cache classification that specifies whether data accessed by the application is suitable for cache compression, including, in the data access request, a tag indicating whether cached data is to be accessed in a compressed-memory cache, wherein the tag is determined in view of the cache classification, and sending, to a server of the storage system, the data access request. The application can be identified in view of metadata included in the virtualized execution image, where the metadata comprises one or more of an application name or an application version.

Abstract: Systems, methods, and apparatus are disclosed for management of data storage with stream based compressibility. In an example, an orchestrator including a storage controller managing one or more storage nodes executes on one or more processors. The orchestrator receives compression ratio measurements associated with attempts to compress data from a plurality of applications running on a plurality of service guests. The orchestrator receives a request for storing a first data stream from a first application running in a first service guest. Based on a compression ratio of previously stored data associated with the first application being less than a threshold, the orchestrator assigns a first compressibility setting to the first data stream. The first compressibility setting causes a storage node to store the first data stream without attempting to compress the first data stream.

Abstract: A container image is received, the container image including a container manifest referencing a first base operating system layer and an application layer. An execution compatibility is determined between the application layer and a second base operating system layer, different from the first operating system layer. An updated container image, an updated container manifest, or the updated container image and the updated container manifest is generated in which the first base operating system layer is replaced with the second base operating system layer.

Abstract: A system includes a memory, a processor in communication with the memory, and an operating system (“OS”) executing on the processor. The processor belongs to a processor socket. The OS is configured to pin a workload of a plurality of workloads to the processor belonging to the processor socket. Each respective processor belonging to the processor socket shares a common last-level cache (“LLC”). The OS is also configured to measure an LLC occupancy for the workload, reserve the LLC occupancy for the workload thereby isolating the workload from other respective workloads of the plurality of workloads sharing the processor socket, and maintain isolation by monitoring the LLC occupancy for the workload.

Abstract: An example method may include receiving, in a virtualized execution environment, a data access request from a storage system, identifying, in view of a virtualized execution image associated with the virtualized execution environment, an application running in the virtualized execution environment, generating a cache classification that specifies whether data accessed by the application is suitable for cache compression, including, in the data access request, a tag indicating whether cached data is to be accessed in a compressed-memory cache, wherein the tag is determined in view of the cache classification, and sending, to a server of the storage system, the data access request. The application can be identified in view of metadata included in the virtualized execution image, where the metadata comprises one or more of an application name or an application version.

Abstract: Systems and methods are provided for managing write requests for drives in a cloud storage system. For example, a system can receive a plurality of write requests for writing a first set of data to a first drive of a plurality of drives. The first drive may be powered off. The system can write the first set of data to a cache in response to receiving the plurality of write requests. The system can determine that a number of the plurality of write requests exceeds a predetermined write request threshold. The system can power on the first drive in response to determining that the number of the plurality of write requests exceeds the predetermined write request threshold. The system can write the first set of data stored in the cache to the first drive.

Abstract: Deduplication operations can be managed based on a likelihood of duplicability. For example, a computing device can generate, by a container of a storage system, an indication of duplicability corresponding to a likelihood of duplicability for the data unit in the storage system. The computing device can transmit the indication of duplicability to a storage node of the storage system for performing an operation based on the indication of duplicability.

Abstract: Deduplication operations can be managed based on a likelihood of duplicability. For example, a computing device can generate, by a container of a storage system, an indication of duplicability corresponding to a likelihood of duplicability for the data unit in the storage system. The computing device can transmit the indication of duplicability to a storage node of the storage system for performing an operation based on the indication of duplicability.

Abstract: Systems and methods are provided for managing write requests for drives in a cloud storage system. For example, a system can receive a plurality of write requests for writing a first set of data to a first drive of a plurality of drives. The first drive may be powered off. The system can write the first set of data to a cache in response to receiving the plurality of write requests. The system can determine that a number of the plurality of write requests exceeds a predetermined write request threshold. The system can power on the first drive in response to determining that the number of the plurality of write requests exceeds the predetermined write request threshold. The system can write the first set of data stored in the cache to the first drive.

Abstract: Systems and methods are provided for managing prefetching operations for read requests for drives in a distributed storage system. For example, a system can determine that a first drive of a plurality of drives is powered on. Prior to receiving a read request for reading a first set of data from the first drive, the system can enable a prefetching operation for prefetching the first set of data from the first drive to be written to a cache. The system may power off the first drive. The system may receive a read request for reading the first set of data from the first drive of a plurality of drives. In response to receiving the read request, the system may read the first set of data from the cache.

Abstract: A container image can be used to determine a caching algorithm for a software application. For example, a storage system can receive a context tag indicating an input/output (IO) pattern associated with a software application of a container. The context tag can be determined based on a container image of the container. The storage system can determine a caching algorithm for the software application based on the context tag. The storage system can apply the caching algorithm to the software application.

Abstract: A technique for dynamic scaling of a distributed computing system is described. In one example of the present disclosure, a system can include a base node configured to provide an access point to a distributed computing system and for servicing a first portion of requests and to generate at least one compute node based on a first load of the base node. The system can also include the at least one compute node of the distributed computing system for servicing a second portion of requests. The at least one compute node can be configured to generate an additional compute node for servicing a subset of the second portion of requests based on a second load of the at least one compute node.

Abstract: Fragmented data on a storage device may be additionally stored in a cache. A cache weight for determining storage of a data unit can be determined. For example, a computing device can receive storage device characteristics from a storage device. A data unit comprising multiple fragments may be stored on the storage device. The computing device can receive data unit characteristics from the storage device. The computing device can determine a cache weight for the data unit. The computing device may output the cache weight for determining storage of the data unit in a cache.

Abstract: Aspects and features of the present disclosure can provide encryption to maintain data privacy while allowing deduplication of some client data by or cloud-based storage platforms. Data can be identified as public data and left unencrypted so that it can be deduplicated. Other data can be identified as personal data, which can be encrypted with a personal key, or as group data, which can be encrypted with a shared, group key. Identifying the data can include storing the data in storage regions within a closed environment. The storage regions can be established, at the client, in a storage platform, or both. Optionally, a storage platform can include multiple storage regions for multiple groups of users, wherein each group is assigned its own unique encryption key. Such data can thus automatically be subject to the same deduplication routines as unencrypted data.

Abstract: Data can be placed by an edge node in a computing environment using multiple criteria in a placement policy. For example, a processing device of an edge node can receive a write request for storing a data object. The processing device can select first and second criteria from a placement policy based on a tag for the data object. The processing device can determine a set of remote components that fulfill the first criterion. The processing device can then identify, from the set, a destination component that fulfills the second criterion. The processing device can transmit the data object to the destination component.

Abstract: Containers can be managed for cryptanalysis attack protection. For example, a computing system can receive, from a container, a description specifying a first hardware requirement for the container. The computing system can restrict access to hardware based on the first hardware requirement for the container. The computing system can perform, for a data object requested by the container, an encryption operation and a decryption operation using the hardware. A result of the encryption operation can be inaccessible to the container prior to the decryption operation.

Abstract: Containers can be managed for cryptanalysis attack protection. For example, a computing system can receive, from a container, a description specifying a first hardware requirement for the container. The computing system can restrict access to hardware based on the first hardware requirement for the container. The computing system can perform, for a data object requested by the container, an encryption operation and a decryption operation using the hardware. A result of the encryption operation can be inaccessible to the container prior to the decryption operation.

Abstract: Deduplication operations can be managed based on a likelihood of duplicability. For example, a computing device can generate, by a container of a storage system, an indication of duplicability corresponding to a likelihood of duplicability for the data unit in the storage system. The computing device can transmit the indication of duplicability to a storage node of the storage system for performing an operation based on the indication of duplicability.

Abstract: Data can be placed by an edge node in a computing environment using multiple criteria in a placement policy. For example, a processing device of an edge node can receive a write request for storing a data object. The processing device can select first and second criteria from a placement policy based on a tag for the data object. The processing device can determine a set of remote components that fulfill the first criterion. The processing device can then identify, from the set, a destination component that fulfills the second criterion. The processing device can transmit the data object to the destination component.