Abstract: Ensuring resiliency to storage device failures in a storage system, including: determining a number of storage device failures within a particular write group that are to be tolerated by the storage system; for a plurality of datasets stored within the storage system, writing each dataset to at least a predetermined number of storage devices within the particular write group, wherein the predetermined number of storage devices is greater than the number of storage device failures within the particular write group that are to be tolerated by the storage system; and responsive to recovering from a system interruption: determining a number of readable storage devices that contain a copy of the dataset; and if the number of readable storage devices that contain a copy of the dataset is not greater than the number of failures that are to be tolerated, writing the dataset to one or more additional storage devices.

Abstract: Migrating workloads to a preferred environment, including: predicting, for each of a plurality of environments, a performance load on each of a plurality of environments that would result from placing one or more of a plurality of workloads on the environment; determining a preferred environment for each of the plurality of workloads by determining a placement of each of the plurality of workloads that results in a best fit for the plurality of workloads; and deploying each of the plurality of workloads in the corresponding preferred environment.

Abstract: Workload placement based on carbon emissions, including: calculating, for each execution environment of a plurality of execution environments, a carbon emission cost associated with a workload; selecting, based on each carbon emission cost for the plurality of execution environments, a target execution environment; and executing the workload on the target execution environment.

Abstract: Workload placement based on carbon emissions, including: calculating, for each execution environment of a plurality of execution environments, a carbon emission cost associated with a workload; selecting, based on each carbon emission cost for the plurality of execution environments, a target execution environment; and executing the workload on the target execution environment.

Abstract: Migrating workloads among execution environments including storage systems includes: selecting a target execution environment for supporting a workload and migrating the workload to the target execution environment utilizing active disaster recovery. Migrating the workload can include: assigning storage resources of the workload to a first pod; linking for replication, the first pod to a second pod of the target execution environment; and replicating the storage resources of the workload to the second pod of the target execution environment.

Abstract: Utilizing volume-level policies in a storage system, including: identifying, for each of a plurality of volumes, one or more characteristics associated with usage of the volume; associating, using the one or more characteristics associated with the usage of the volume, one or more storage system policies with the volume; and configuring, using the one or more storage system policies that are associated with the volume, the storage system.

Abstract: Recommending changes to a storage system, including: identifying, using predicted characteristics of one or more workloads executing on the storage system, one or more configuration changes to the storage system that would improve the operation of the storage system; selecting, from the one or more configuration changes to the storage system that would improve the operation of the storage system, a preferred configuration change; and recommending the preferred configuration change.

Abstract: Content including information describing an issue with a storage system is received. The content is analyzed by a generative artificial intelligence (AI) model to identify the issue described by the content. A solution for the issue is determined based on at least one of information associated with the storage system or information associated with one or more other storage systems. A response including a description of the solution for the issue is generated.

Abstract: A method for managing an application's resource stack is disclosed. The method includes identifying, by a storage system, a root cause of an anomaly predicted at the external component that affects a performance of the storage system based on a relationship between metrics of the storage system and metrics of a component external to the storage system; and reconfiguring the external component based on the identified root cause.

Abstract: Ensuring resiliency to storage device failures in a storage system, including: determining a number of storage device failures within a particular write group that are to be tolerated by the storage system; for a plurality of datasets stored within the storage system, writing each dataset to at least a predetermined number of storage devices within the particular write group, wherein the predetermined number of storage devices is greater than the number of storage device failures within the particular write group that are to be tolerated by the storage system; and responsive to recovering from a system interruption: determining a number of readable storage devices that contain a copy of the dataset; and if the number of readable storage devices that contain a copy of the dataset is not greater than the number of failures that are to be tolerated, writing the dataset to one or more additional storage devices.

Abstract: Staging data on a storage element integrating fast durable storage and bulk durable storage, including: receiving, at a storage element integrating fast durable storage and bulk durable storage, a data storage operation from a host computer; storing data corresponding to the data storage operation within fast durable storage in accordance with a first data resiliency technique; and responsive to detecting a condition for transferring data between fast durable storage and bulk durable storage, transferring the data from fast durable storage to bulk durable storage in accordance with a second data resiliency technique.

Abstract: Managing an application's resource stack, including: detecting, in dependence upon one or more storage system metrics, an occurrence of a storage system performance anomaly; and responsive to detecting the storage system performance anomaly, identifying, in dependence upon codified relationships between one or more storage system metrics and one or more elements in the application stack that are external to the storage system, a root cause of the storage system performance anomaly.

Abstract: Ensuring resiliency to storage device failures in a storage system, including: determining a number of storage device failures within a particular write group that are to be tolerated by the storage system; for a plurality of datasets stored within the storage system, writing each dataset to at least a predetermined number of storage devices within the particular write group, wherein the predetermined number of storage devices is greater than the number of storage device failures within the particular write group that are to be tolerated by the storage system; and responsive to recovering from a system interruption: determining a number of readable storage devices that contain a copy of the dataset; and if the number of readable storage devices that contain a copy of the dataset is not greater than the number of failures that are to be tolerated, writing the dataset to one or more additional storage devices.

Abstract: Staging data on a storage element integrating fast durable storage and bulk durable storage, including: receiving, at a storage element integrating fast durable storage and bulk durable storage, a data storage operation from a host computer; storing data corresponding to the data storage operation within fast durable storage in accordance with a first data resiliency technique; and responsive to detecting a condition for transferring data between fast durable storage and bulk durable storage, transferring the data from fast durable storage to bulk durable storage in accordance with a second data resiliency technique.

Abstract: Migrating workloads between a plurality of execution environments, including: identifying, in dependence upon on characteristics of a workload, one or more execution environments that can support the workload; determining, for each execution environment, costs associated with supporting the workload on the execution environment; selecting, in dependence upon the costs associated with supporting the workload on each the execution environments, a target execution environment for supporting the workload; and executing the workload on the target execution environment.

Abstract: Software lifecycle management for a storage system, including: generating, based on user input, a user-defined software lifecycle management policy for software on one or more storage systems; identifying, in dependence upon on a software configuration of the one or more storage systems, one or more candidate updates for the software; and generating, in dependence upon the user-defined software lifecycle management policy, lifecycle management data that identifies one or more conforming updates from among the one or more candidate updates.

Abstract: Ensuring resiliency to storage device failures in a storage system, including: determining a number of storage device failures within a particular write group that are to be tolerated by the storage system; for a plurality of datasets stored within the storage system, writing each dataset to at least a predetermined number of storage devices within the particular write group, wherein the predetermined number of storage devices is greater than the number of storage device failures within the particular write group that are to be tolerated by the storage system; and responsive to recovering from a system interruption: determining a number of readable storage devices that contain a copy of the dataset; and if the number of readable storage devices that contain a copy of the dataset is not greater than the number of failures that are to be tolerated, writing the dataset to one or more additional storage devices.

Abstract: Migrating workloads to a preferred environment, including: predicting, for each of a plurality of environments, a performance load on each of a plurality of environments that would result from placing one or more of a plurality of workloads on the environment; determining a preferred environment for each of the plurality of workloads by determining a placement of each of the plurality of workloads that results in a best fit for the plurality of workloads; and deploying each of the plurality of workloads in the corresponding preferred environment.

Abstract: Ensuring resiliency to storage device failures in a storage system, including: determining a number of storage device failures within a particular write group that are to be tolerated by the storage system; for a plurality of datasets stored within the storage system, writing each dataset to at least a predetermined number of storage devices within the particular write group, wherein the predetermined number of storage devices is greater than the number of storage device failures within the particular write group that are to be tolerated by the storage system; and responsive to recovering from a system interruption: determining a number of readable storage devices that contain a copy of the dataset; and if the number of readable storage devices that contain a copy of the dataset is not greater than the number of failures that are to be tolerated, writing the dataset to one or more additional storage devices.

Abstract: Migrating workloads among execution environments including storage systems includes: selecting a target execution environment for supporting a workload and migrating the workload to the target execution environment utilizing active disaster recovery. Migrating the workload can include: assigning storage resources of the workload to a first pod; linking for replication, the first pod to a second pod of the target execution environment; and replicating the storage resources of the workload to the second pod of the target execution environment.