G06F2209/5014

FLEXIBLE SHARING IN SHARED COMPUTER ENVIRONMENTS

A sharable resource of a first user's environment is identified. The sharable resource is configured as sharable in a shared computer environment. A matching resource that is sufficiently similar to the sharable resource is located. The matching resource is used by pre-existing users of the shared computer environment. Agreement from the pre-existing users for the first user to access the matching resource is obtained. The first user is then provided access to the matching resource.

Resource reservation management device, resource reservation management method, and resource reservation management program

[Problem] Available resources are efficiently used even in a case in which continuous available resources cannot be secured on a cloud. [Solution] A resource reservation management apparatus 10 includes: a storage unit that stores a resource capacity and resource reservation information of a computing machine; a reservation notification unit 11 that receives, from a user terminal, reservation request information including an operating requested time period, an operating time, and a requested specification as a reservation of a master lease; a scheduling unit 12 that creates slave leases by splitting the operating time of the master lease in accordance with times corresponding to available resources indicated in the resource reservation information and sets the slave leases in the resource reservation information; a reservation management unit that detects occurrence of predetermined events including stop, shift, restart, and deletion of the created instances by referring to the resource reservation information; and an instance management unit 15 that transmits instruction information in accordance with an instance creation instruction and the detected predetermined events to the computing machine 15.

Managing containers on a data storage system

Mechanisms and techniques are employed for managing the allocation and load balancing of storage system resources for the containerized, distributed execution of applications on a storage system. A control component executing on a processing component of the storage system may control reserving the necessary resources on one or more processing components to implement an application, and control a container management module to create, deploy and/or modify one or more containers on one or more processing components of the storage system. The one or more containers then may be executed to implement the application. Multiple processing components of the storage system may have a resource management module executing thereon. The control component may exchange communications with the one or more resource management modules of each processing component to determine the resources available within the processing component; e.g., to determine whether the processing component can satisfy the resource requirements of the application.

Cost-savings using ephemeral hosts in infrastructure as a service environments based on health score

Various examples are disclosed for placing virtual machine (VM) workloads in a computing environment. Ephemeral workloads can be placed onto reserved instances or reserved hosts in a cloud-based VM environment. If a request to place a guaranteed workload is received, ephemeral workloads can be evacuated to make way for the guaranteed workload.

Recommendation and deployment engine and method for machine learning based processes in hybrid cloud environments

Methods and systems are provided for the deployment of machine learning based processes to public clouds. For example, a method for deploying a machine learning based process may include developing and training the machine learning based process to perform an activity, performing at least one of identifying and receiving an identification of a set of one or more public clouds that comply with a set of regulatory criteria used to regulate the activity, selecting a first public cloud of the set of one or more public clouds that complies with the set of regulatory criteria used to regulate the activity, and deploying the machine learning based process to the first public cloud of the set of one or more public clouds.

Differential overbooking in a cloud computing environment

Techniques for differential overbooking on a cloud database. These techniques may include determining a reservation amount of a multi-tenant resource for a first service of a based upon an overbooking characteristic of the first service, and determining that a total usage value of the multi-tenant resource by a plurality of services is greater than a threshold value. In addition, the techniques may include determining a service usage value of the multi-tenant resource by the first service, determining a first overage value of the first service based on the service usage value and the reservation amount, and performing a resource reclamation process over the multi-tenant resource based on the first overage value of the first service.

MANAGING CONTAINERS ON A DATA STORAGE SYSTEM

Mechanisms and techniques are employed for managing the allocation and load balancing of storage system resources for the containerized, distributed execution of applications on a storage system. A control component executing on a processing component of the storage system may control reserving the necessary resources on one or more processing components to implement an application, and control a container management module to create, deploy and/or modify one or more containers on one or more processing components of the storage system. The one or more containers then may be executed to implement the application. Multiple processing components of the storage system may have a resource management module executing thereon. The control component may exchange communications with the one or more resource management modules of each processing component to determine the resources available within the processing component; e.g., to determine whether the processing component can satisfy the resource requirements of the application.

Predictive virtual machine launch-based capacity management

A host computer inventory system within a provider network detects patterns of launch requests on an individual user account basis. For a customer that cyclically submits similar launch requests, the inventory system may allocate slots in specific host computers consistent with the detected launch pattern so that future attempts to launch the virtual machines will be honored using the pre-allocated hosts.

RESOURCE MANAGEMENT DEVICE, RESOURCE MANAGEMENT METHOD AND PROGRAM
20220357996 · 2022-11-10 ·

A resource management device (100) includes: a virtualized resource reservation unit (114) that receives a reservation request for a virtualized resource, and allocates and reserves the virtualized resource included in the reservation request; and a virtualized resource state management unit (115) that, when reservation performed for the reservation request fails, releases reservations of virtualized resources already reserved (existing reservations), allocates and reserves the virtualized resource included in the reservation request, and performs re-reservation for the existing reservations by allocating virtualized resources to the existing reservations. When the virtualized resource state management unit (115) fails in the re-reservation even for one or some of the existing reservations, reservation information is unchanged in a state stored when the virtualized resource reservation unit (114) fails in the reservation performed for the reservation request.

Processing future-dated resource reservation requests

Computer systems and methods for managing resources are described. In an aspect, a method includes: providing, to a client device associated with an authenticated entity, an intraday transfer interface, the intraday transfer interface including a selectable option to issue a future-dated borrowed resource reservation request to set aside an amount of borrowed resources; receiving, from the client device, a signal representing the future-dated borrowed resource reservation request, the future-dated borrowed resource reservation request associated with an amount of borrowed resources to set aside and a date of release of such borrowed resources; detecting a trigger condition, the trigger condition including an end-of-day reconciliation of resource tracking data and, in response to detecting the trigger condition, evaluating the future-dated borrowed resource reservation request based on a current amount of borrowed resources; and when the evaluation of the future-dated borrowed resource reservation request indicates that the future-dated borrowed resource reservation request cannot be implemented, generating an error by sending an error message to a computing device and rejecting the future-dated borrowed resource reservation request.