Hitachi, Ltd.

Soichi Takashige

Jun Mizuno

Keisuke Hatasaki

Hideki Takano

Nobuhiro Maki

Hideo Saito

Yuichi Taguchi

Masakuni Agetsuma

Takashi Tameshige

Hiroshi Nasu

Azusa Jin

Provided is an application development support system and method that support studies on applying serverless while optimizing application resource usage amount and maintaining API response performance in developing an application with microservices. In the application development support system, a container runtime platform applies serverless to a certain container to form an event-driven container. The application development support system executes an API processing time prediction process by calculating a predicted value of API processing time in the event-driven container and a predicted value of API processing time in all of the containers based on the predicted value and a sequence of API calls among the plurality of containers; calculating a usage amount of resources used by the plurality of containers per unit period; and outputting a calculated result of each of the API processing time prediction processing and the resource usage amount calculation processing.

Application development support system and application development support method

Provided is a data management method capable of deleting intermediate data at an appropriate timing. The data management method in a data analysis system that performs analysis by combining a plurality of input data based on an analysis execution request from a computer includes: a first step, in which a request analysis unit analyzes the analysis execution request from the computer to identify a task, identifies intermediate data generated after execution of each identified task, and generates constraint information that determines whether to delete the identified intermediate data; a second step, in which a task management unit determines whether to delete the intermediate data based on the constraint information for each identified task; and a third step, in which a task execution unit executes the identified task and deletes the intermediate data of the task based on a determination result of the second step.

Data management method and data analysis system

Status information including remaining battery power is collected from a management target device. Subsequent operations of the device are identified from an operation schedule management collection. Battery consumptions corresponding to subsequent operations of the device are estimated from KPI management collection that includes information representing relationships between battery consumptions and operations with respect to each of a plurality of devices. The battery life of the device is predicted based on the estimated battery consumptions and the remaining battery power represented by the collected status information. A circuit schedule of a maintenance engineer is determined based on the predicted battery life, the schedule including necessity of dispatch of the maintenance engineer to the device.

Energy saving device management method and energy saving device management system

The present invention ensures improving responsiveness in a P2P type distributed database system that includes a plurality of node computers capable of storing management target data in storage devices. The storage devices include a first type storage device having a high input/output performance and a second type storage device having a low input/output performance. There is provided the storage devices that store KeySpace management tables including response count information indicative of a count of the node computers from which the identical management target data are to be read. The identical management target data are required to respond to a read request of the management target data. The node computers by a count indicated by the response count information and capable of storing the management target data in the first type storage devices among the plurality of node computers are determined as storage destinations when a CPU receives a write request of new management target data. The determined node computers are caused to store the management target data.

Distributed database system, distributed database management method, and distributed database management program

The present invention proposes an information processing system and a volume allocation method making it feasible to reduce overall system operation cost. A replication group to carry out replication is comprised of one or multiple nodes. A storage node classifies respective storage devices mounted thereon into plural storage hierarchies according to the drive type of each of the storage devices for management of the storage devices. A controller node allocates, to each node of the nodes constituting the replication group, a volume for which a storage device of a storage hierarchy suitable for a type of middleware that the node uses and a node type of the node acting in the replication group provides a storage area.

Information processing system and volume allocation method

Standby computers are dynamically divided into groups according to the difference between the software thereof and the software required of a business system. When a computer is made available, the standby computers divided into groups by software structure are searched and an appropriate one is extracted to quickly complete the construction of the software environment. An active computer, if to be transferred to standby mode, is associated with the group having the same software structure as the business system with which the active computer has thus far operated. The active/standby states of the computers are monitored, and the standby computers are changed thereby to widen the possible range of application to other business systems, removing copy operation of disk images from the active computer to the standby computers.

Growing community of inventors

Tokyo, Japan

Soichi Takashige