Abstract: In one embodiment, a computer-implemented method for object-granular policy assignment in an object storage environment includes: automatically assigning a plurality of objects stored within the object storage environment to one or more policies; and locating one or more of the objects among a plurality of policy rings within the object storage environment based on semantics of the one or more policies. A virtual namespace maps each object to at least one of the policy rings based on the one or more policies assigned to the object; and the virtual namespace is scalable with a number of the plurality of objects stored within the object storage environment. Corresponding systems and computer program products are also disclosed.

Abstract: One embodiment provides a quality of service (QoS) monitoring framework for dynamically binding one or more customer applications to one or more microservices in a dynamic service environment, collecting compliance data and contextual data from the dynamic service environment and one or more hosting environments, and modifying a monitoring infrastructure for the one or more customer applications based on the compliance data and the contextual data.

Abstract: In one general embodiment, a computer-implemented method includes analyzing a plurality of data management factors within an object-based storage system, including tracking which of a plurality of proxy servers within the object-based storage system currently holds a lock; determining a data management policy for predetermined data within the object-based storage system, based on the analyzing, including identifying a current location of the lock within one of the plurality of proxy servers within the object-based storage system; and sharing the data management policy for the predetermined data, including the current location of the lock within the object-based storage system, with a load balancer associated with the object-based storage system.

Abstract: A method and system for creating a new restore container. A count that is determined for each unique infrastructure container of existing unique infrastructure containers is a number of instances in which a particular container type that is unique for each unique infrastructure container has been utilized. In response to both determining that the count for one unique infrastructure container is equal to or greater than a specified threshold and determining that a popular infrastructure container does not exist within a central repository that stores the existing unique infrastructure containers, the new restore container is created within the central repository by determining a most similar container of the existing restore containers whose software stack content matches, in part, software content in a first software stack of the popular infrastructure container more closely than does software content in the software stack of any other existing restore container.

Abstract: In one general embodiment, a computer-implemented method includes analyzing a plurality of data management factors within an object-based storage system, including tracking which of a plurality of proxy servers within the object-based storage system currently holds a lock; determining a data management policy for predetermined data within the object-based storage system, based on the analyzing, including identifying a current location of the lock within one of the plurality of proxy servers within the object-based storage system; and sharing the data management policy for the predetermined data, including the current location of the lock within the object-based storage system, with a load balancer associated with the object-based storage system.

Abstract: Embodiments relate to a pool of persistent storage volumes. Capacity of the volumes is managed to ensure continued operation and function of the volumes with respect to their corresponding storage pool capacity threshold(s). One or more space savings techniques are selectively performed on a copy of a selected volume. Such techniques include measurement of capacity change and measurement of workload performance change. These measurements are leveraged to produce a subset of space reduction actions for execution. A space reduction action in the form of compression or thinning takes place on-demand on a corresponding volume.

Abstract: A method and associated systems for backing up a target computer application that comprises identifying and backing up databases and other information repositories upon which the target application depends. The target application is identified and related to a backup requirement that specifies a minimum application-backup frequency. The application's “dependencies” are automatically identified from sources that include configuration files, where each dependency identifies one or more databases or other information repositories that store information upon which the application directly or indirectly depends. If any of these databases or repositories is associated with a backup frequency less than the application's minimum backup frequency, the database or repository is flagged. Each flagged entity's backup schedule is then revised so that the flagged entity's backup frequency is equal to or greater than the application's minimum backup frequency.

Abstract: In one general embodiment, a computer program product for sharing a data management policy with a load balancer comprises a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se. Additionally, the program instructions are executable by a processor to cause the processor to perform a method comprising analyzing, by the processor, a plurality of data management factors within an object-based storage system, determining, by the processor, a data management policy for predetermined data within the object-based storage system, based on the analyzing, and sharing, by the processor, the data management policy for the predetermined data with a load balancer associated with the object-based storage system.

Abstract: One embodiment provides a method, including: generating, for each of a plurality of storage volumes, an actual used storage capacity model and identifying a potential storage capacity savings using the actual used capacity model, wherein each of the plurality of storage volumes has been identified as a candidate for migration to a thin provisioned volume; generating, for each of the plurality of storage volumes, an input/output profile model and identifying a potential change in performance of an application accessing the storage volume using the input/output profile model; generating, for each of the plurality of storage volumes, a growth profile and identifying a potential change in capacity using the growth profile; and determining, using an optimization algorithm, a subset of the plurality of storage volumes to be migrated to thin provisioned volumes based upon the volume capacity model, the performance model, and the volume growth profile.

Abstract: The embodiments described herein relate to dynamically managing metric data of a network environment with respect to a data storage system. A data retention policy is analyzed, which includes extracting one or more metric definitions from the retention policy. A relevance of a set of metric data is identified based on the analysis. The set of metric data includes an aggregation of one or more metric observations. A storage location in a data storage system for the set of metric values is selected based on the identified relevance. The data storage system includes a cache storage location and a persistent storage location. The set of metric data is retained in the selected storage location. As the retention policy is modified, select data may be re-classified and moved within the storage system based on the re-classification.

Abstract: In one general embodiment, a computer program product for sharing a data management policy with a load balancer comprises a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se. Additionally, the program instructions are executable by a processor to cause the processor to perform a method comprising analyzing, by the processor, a plurality of data management factors within an object-based storage system, determining, by the processor, a data management policy for predetermined data within the object-based storage system, based on the analyzing, and sharing, by the processor, the data management policy for the predetermined data with a load balancer associated with the object-based storage system.

Abstract: The embodiments described herein relate to dynamically optimizing a mapping from applications to shared service providers via one or more monitoring modules. A software layer positioned between a set of requestor applications and a set of shared service providers is configured. The layer is populated with a collection of one or more monitoring modules, with each monitoring module configured to monitor application resource usage. In response to receiving a monitoring request from the set of requestor applications, a mapping of the received request to the collection of xlets is dynamically optimized.

Abstract: Embodiments relate to a pool of persistent storage volumes. Capacity of the volumes is managed to ensure continued operation and function of the volumes with respect to their corresponding storage pool capacity threshold(s). One or more space savings techniques are selectively performed on a copy of a selected volume. Such techniques include measurement of capacity change and measurement of workload performance change. These measurements are leveraged to produce a subset of space reduction actions for execution. A space reduction action in the form of compression or thinning takes place on-demand on a corresponding volume.

Abstract: Embodiments relate to a pool of persistent storage volumes. Capacity of the volumes is managed to ensure continued operation and function of the volumes with respect to their corresponding storage pool capacity threshold(s). A background process groups the volumes within each pool into one or more clusters based on a similarity or commonality characteristic. The background process selectively performs one or more space savings techniques of a copy of a selected volume, measures impact data associated with the techniques, and maintains the data. At such time as the threshold level is approached for a storage pool, one or more space reduction actions take place on constituent volumes in view of the background process and the associated groups. The reduction action includes implementation of a space saving technique, such as compression and/or thinning, of one or more volumes in one or more clusters in an associated storage pool.

Abstract: In one general embodiment, a computer program product for sharing a data management policy with a load balancer comprises a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se. Additionally, the program instructions are executable by a processor to cause the processor to perform a method comprising analyzing, by the processor, a plurality of data management factors within an object-based storage system, determining, by the processor, a data management policy for predetermined data within the object-based storage system, based on the analyzing, and sharing, by the processor, the data management policy for the predetermined data with a load balancer associated with the object-based storage system.

Abstract: An approach for managing replicated data is presented. A current usage of resources in a system and a threshold usage of the resources are determined. Based on inter-replica correlation(s) and inter-data correlation(s) specified by a unified replication metadata model, a proper subset of replicas included in a plurality of replicas is indexed by (i) if the current usage is less than the threshold usage, determining an expected additional resource usage due to performing an indexing task online and based on the expected additional resource usage, determining a resource affinity score for performing the indexing task online, or (ii) if the current usage is greater than or equal to the threshold usage, determining an expected resource usage due to performing the indexing task offline and based on the expected resource usage, determining a resource affinity score for performing the indexing task offline.

Abstract: One embodiment provides a quality of service (QoS) monitoring framework for dynamically binding one or more customer applications to one or more microservices in a dynamic service environment, collecting compliance data and contextual data from the dynamic service environment and one or more hosting environments, and modifying a monitoring infrastructure for the one or more customer applications based on the compliance data and the contextual data.

Abstract: In one general embodiment, a computer-implemented method includes creating multiple pools of micro services. Each of the pools includes a specific configuration set and resource properties. Also, the computer-implemented method includes receiving incoming workloads. Moreover, the computer-implemented method includes, for each of the incoming workloads, dynamically mapping the incoming workload, based on characteristics of the incoming workload, to an access path traversing a combination of a subset of the pools of micro services.

Abstract: In one embodiment, a computer-implemented method for object-granular policy assignment in an object storage environment includes: automatically assigning a plurality of objects stored within the object storage environment to one or more policies; and locating one or more of the objects among a plurality of policy rings within the object storage environment based on semantics of the one or more policies. A virtual namespace maps each object to at least one of the policy rings based on the one or more policies assigned to the object; and the virtual namespace is scalable with a number of the plurality of objects stored within the object storage environment. Corresponding systems and computer program products are also disclosed.

Abstract: In one embodiment, a computer-implemented method for object-granular policy assignment in an object storage environment includes: automatically assigning a plurality of objects stored within the object storage environment to one or more policies; and locating one or more of the objects among a plurality of policy rings within the object storage environment based on semantics of the one or more policies. A virtual namespace maps each object to at least one of the policy rings based on the one or more policies assigned to the object; and the virtual namespace is scalable with a number of the plurality of objects stored within the object storage environment. Corresponding systems and computer program products are also disclosed.