TECHNOLOGIES FOR ALLOCATING RESOURCES ACROSS DATA CENTERS
Technologies for allocating resources across data centers include a compute device to obtain resource utilization data indicative of a utilization of resources for a managed node to execute a workload. The compute device is also to determine whether a set of resources presently available to the managed node in a data center in which the compute device is located satisfies the resource utilization data. Additionally, the compute device is to allocate, in response to a determination that the set of resources presently available to the managed node does not satisfy the resource utilization data, a supplemental set of resources to the managed node. The supplemental set of resources are located in an off-premises data center that is different from the data center in which the compute device is located. Other embodiments are also described and claimed.
1 . A server comprising:
a node, the node comprising resources, the resources including:
a compute resource to execute an application;
a data storage resource;
an accelerator resource; and
a memory resource; and
one or more non-transitory machine-readable storage media comprising a plurality of instructions stored thereon that, in response to being executed, cause the server to:
communicate with a remote server via a public cloud service to allocate a remote resource in the remote server to the node based on the resources available in the server; and
obtain address information from the remote server for use by the node to access the remote resource as if the remote resource was in the server.
2 . The server of claim 1 , wherein the server to select the remote resource as a function of availability and cost.
3 . The server of claim 1 , wherein the server to utilize an application programming interface to communicate with the remote server in a format specific to the remote server.
4 . The server of claim 1 , wherein the server to communicate with the remote resource using a non-volatile memory express over fabric (NVMe-oF) bus protocol.
5 . The server of claim 1 , wherein the server to communicate with the remote server via the public cloud service to deallocate the remote resource in the remote server to the node if the resources to be used in an execution of a workload by the node decrease below the resources available in the server.
6 . The server of claim 1 , wherein the remote resource is a remote accelerator resource.
7 . The server of claim 1 , wherein the remote resource is a remote storage resource.
8 . One or more non-transitory machine-readable storage media comprising a plurality of instructions stored thereon that, in response to being executed, cause a server to:
communicate with a remote server via a public cloud service to allocate a remote resource in the remote server to a node based on resources available in the server, the node comprising the resources, the resources including a compute resource to execute an application, a data storage resource, an accelerator resource, and a memory resource; and
obtain address information from the remote server for use by the node to access the remote resource as if the remote resource was in the server.
9 . The one or more non-transitory machine-readable storage media of claim 8 , wherein the server to select the remote resource as a function of availability and cost.
10 . The one or more non-transitory machine-readable storage media of claim 8 , wherein the server to utilize an application programming interface to communicate with the remote server in a format specific to the remote server.
11 . The one or more non-transitory machine-readable storage media of claim 8 , wherein the server to communicate with the remote resource using a non-volatile memory express over fabric (NVMe-oF) bus protocol.
12 . The one or more non-transitory machine-readable storage media of claim 8 , wherein the server to communicate with the remote server via the public cloud service to deallocate the remote resource in the remote server to the node if the resources to be used in an execution of a workload by the node decrease below the resources available in the server.
13 . The one or more non-transitory machine-readable storage media of claim 8 , wherein the remote resource is a remote accelerator resource.
14 . The one or more non-transitory machine-readable storage media of claim 8 , wherein the remote resource is a remote storage resource.
15 . A method comprising:
communicating, by a server, with a remote server via a public cloud service to allocate a remote resource in the remote server to a node based on resources available in the server, the node comprising the resources, the resources including a compute resource to execute an application, a data storage resource, an accelerator resource and a memory resource; and
obtaining, by the server, address information from the remote server for use by the node to access the remote resource as if the remote resource was in the server.
16 . The method of claim 15 , wherein the server to select the remote resource as a function of availability and cost.
17 . The method of claim 15 , wherein the server to utilize an application programming interface to communicate with the remote server in a format specific to the remote server.
18 . The method of claim 15 , wherein the server to communicate with the remote resource using a non-volatile memory express over fabric (NVMe-oF) bus protocol.
19 . The method of claim 15 , wherein the server to communicate with the remote server via the public cloud service to deallocate the remote resource in the remote server to the node if the resources to be used in an execution of a workload by the node decrease below the resources available in the server.
20 . The method of claim 15 , wherein the remote resource is a remote accelerator resource.
21 . The method of claim 15 , wherein the remote resource is a remote storage resource.