Abstract: Example implementations described herein involve systems and methods that can include, responsive to a request to deploy an application using a storage of a storage system, managing a storage configuration for the application; managing data information and storage configuration information associated with a copy relationship between data used by the application and the storage configuration for the storage system; extracting and evaluating possible configuration patterns from the data information and the storage configuration information; and providing ones of the possible configuration patterns that satisfy specified requirements for the application.

Abstract: Provided is a resource allocation determination method for a VM/container, volume, and the like created as a new VM/container or volume without exceeding an upper limit of a computer resource of a node in an HCI environment. In order to determine allocation of at least one of a virtual machine, a container, and a volume in a system of the HCI environment, a use state of a computer resource shared by a virtual machine and a storage controller operating on each node is managed, and an allocation destination node of the new virtual machine, container, or volume is determined based on the use state without exceeding an upper limit of a computer resource of the allocation destination node.

Abstract: Example implementation described herein are directed to a mechanism to provision data volume which requires remote data copy between separated clusters, especially for the container platform. For a request to create a volume made to the clusters, example implementations can involve creating a first volume in a first cluster; obtaining volume information of a corresponding second volume from a second cluster; configuring the first volume and the corresponding second volume in the second cluster to have a remote copy relationship based on the obtained volume information; and setting access from the container to the first volume and the corresponding second volume based on the remote copy relationship.

Abstract: Example implementations described herein involve systems and methods which automatically determine volumes to be replicated for disaster recovery based on the execution priority of an application which uses the volumes. Such example implementations can involve systems and methods involving creating a volume in a first storage system for each of one or more containers newly launched on one or more servers managing a container orchestrator; and establishing replication of the volume for the each of the newly launched one or more containers to a second storage system in order from highest container priority to lowest container priority.

Abstract: Example implementations described herein involve systems and methods which automatically determine volumes to be replicated for disaster recovery based on the execution priority of an application which uses the volumes. Such example implementations can involve systems and methods involving creating a volume in a first storage system for each of one or more containers newly launched on one or more servers managing a container orchestrator; and establishing replication of the volume for the each of the newly launched one or more containers to a second storage system in order from highest container priority to lowest container priority.

Abstract: Example implementations described herein are directed to searching ML models to facilitate IO load prediction. Even if there is no existing ML model applicable to the underlying container, example implementations described herein obtain the ML model for the nearest container. Through such example implementations, the underlying systems can reduce the total ML models maintained for the prediction of IO load and can enhance ML models with enough learning data for each ML model.

Abstract: Example implementation described herein are directed to a mechanism to provision data volume which requires remote data copy between separated clusters, especially for the container platform. For a request to create a volume made to the clusters, example implementations can involve creating a first volume in a first cluster; obtaining volume information of a corresponding second volume from a second cluster; configuring the first volume and the corresponding second volume in the second cluster to have a remote copy relationship based on the obtained volume information; and setting access from the container to the first volume and the corresponding second volume based on the remote copy relationship.

Abstract: Example implementations described herein are directed to backup and restore of a public cloud and data center for disaster recovery. In a backup process of the disaster recovery, the VM root device information (a public cloud) and storage system volume information (a data center) in a main site are transferred to the disaster recovery tool. In a restoration process, the DR Tool specifies the storage system volume for backup to attach the VM in a backup site with the above information.

Abstract: Provided is a resource allocation determination method for a VM/container, volume, and the like created as a new VM/container or volume without exceeding an upper limit of a computer resource of a node in an HCI environment. In order to determine allocation of at least one of a virtual machine, a container, and a volume in a system of the HCI environment, a use state of a computer resource shared by a virtual machine and a storage controller operating on each node is managed, and an allocation destination node of the new virtual machine, container, or volume is determined based on the use state without exceeding an upper limit of a computer resource of the allocation destination node.

Abstract: Embodiments described herein are directed to volume creation such that the volume is created in the storage system that is closest to the group of servers that the container is likely to be launched. Through such embodiments, the volume can be created or migrated in anticipation to a launch or a relaunch of a container.

Abstract: Example implementations described herein are directed to searching ML models to facilitate IO load prediction. Even if there is no existing ML model applicable to the underlying container, example implementations described herein obtain the ML model for the nearest container. Through such example implementations, the underlying systems can reduce the total ML models maintained for the prediction of IO load and can enhance ML models with enough learning data for each ML model.

Abstract: Example implementations described herein are directed to Input/Output (I/O) path reservation with out of band management. In example implementations, for failure of a storage orchestrator to delete the path between the container and the first volume, the example implementations described herein are directed to deleting a path between the first volume and a quorum volume; and establishing an I/O path between the new container and the second volume.

Abstract: Each file storage apparatus of a plurality of file storage apparatuses stores a file system, and associates and stores paths of elements in the file system and archive destinations of the elements in an archive storage apparatus. When the file system is operated, each file storage apparatus transmits archive data of an element as an operation target, and operation information including operation details to the archive storage apparatus. The archive storage apparatus receives the archive data and the operation information, stores the archive data, and stores consistency information including the operation information and archive versions indicating a reception order of the operation information.

Abstract: Provided is a resource allocation determination method for a VM/container, volume, and the like created as a new VM/container or volume without exceeding an upper limit of a computer resource of a node in an HCI environment. In order to determine allocation of at least one of a virtual machine, a container, and a volume in a system of the HCI environment, a use state of a computer resource shared by a virtual machine and a storage controller operating on each node is managed, and an allocation destination node of the new virtual machine, container, or volume is determined based on the use state without exceeding an upper limit of a computer resource of the allocation destination node.

Abstract: Provided is a resource allocation determination method for a VM/container, volume, and the like created as a new VM/container or volume without exceeding an upper limit of a computer resource of a node in an HCl environment. In order to determine allocation of at least one of a virtual machine, a container, and a volume in a system of the HCl environment, a use state of a computer resource shared by a virtual machine and a storage controller operating on each node is managed, and an allocation destination node of the new virtual machine, container, or volume is determined based on the use state without exceeding an upper limit of a computer resource of the allocation destination node.

Abstract: A highly accurate data migration pattern is decided on the bases of usages of a plurality of kinds of resources and by taking influence of execution of data migration on each resource into consideration. In a distributed storage system, a monitor acquires a per-period usage of each of the plurality of kinds of the resources per data, a performance simulator estimates a per-period usage of each resource on a migration destination node when the data is migrated by using the acquired per-data resource usage and calculates an estimate of a latency from the estimated usage of each resource and an optimizer decides a migration pattern of the data on the basis of the estimate of the latency.

Abstract: A highly accurate data migration pattern is decided on the bases of usages of a plurality of kinds of resources and by taking influence of execution of data migration on each resource into consideration. In a distributed storage system, a monitor acquires a per-period usage of each of the plurality of kinds of the resources per data, a performance simulator estimates a per-period usage of each resource on a migration destination node when the data is migrated by using the acquired per-data resource usage and calculates an estimate of a latency from the estimated usage of each resource and an optimizer decides a migration pattern of the data on the basis of the estimate of the latency.

Abstract: When a second storage device in a second site receives an update notification regarding a first element updated according to a write request from a first host, from a first storage device in a first site, for a second element specified on the basis of the update notification, the second storage device manages data of the first element corresponding to the second element as latest data. The first storage device provides a first volume capable of including a plurality of first elements. The second storage device provides a second volume capable of including a plurality of second elements corresponding to the plurality of first elements. When the second storage device receives a read request from a second host, the second storage device determines whether or not data of the first element corresponding to a read source second element (second element specified from the read request) is the latest data.

Abstract: According to one embodiment, a storage system includes a representative node and a plurality of general nodes including a plurality of resources. Each of the general nodes stores resource status information indicating respective statuses of the plurality of resources in a first storage unit thereof. The representative node stores resource status information collected from the plurality of general nodes in a second storage unit thereof, decides whether to acquire the resource status information from the first storage unit of the general node or to acquire the resource status information from the second storage unit based on a received request, and transmits the resource status information acquired from a decided acquisition destination to an issuing source of the request.

Abstract: A file server apparatus includes a second file system volume including cache data of a first file system volume stored in a shared file storage apparatus. The file server apparatus determines the operation type indicated by an access request to the first file system volume from a client. When the operation type is directory operation, the file server sends an instruction of directory operation to the shared file storage apparatus, and then transmits a completion response to the client. When the operation type is file operation, the file server apparatus executes a file operation in the second file system volume, transmits a completion response to the client, and then transmits a file operation instruction to the shared file storage apparatus.