Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Drawings
The drawings are objected to because Figures 4A, B, and C have label “Sever Node,” which should be “Server Node.” Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-3, 5, 9-11, 13, and 17-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fontoura (US 2019/0163517) and further in view of Breitgand (US 2014/0082612).
Regarding claim 1, Fontoura teaches: A method, comprising:
receiving deployment data for a customer subscription associated with a deployment of a first set of virtual machines on a node cluster of a cloud computing system (¶ 44, “At 210, the resource manager collects data for VM deployments in a cloud computing system”), the first set of virtual machine being implemented on a first set of server nodes of the node cluster (¶ 48, “Each cluster 34 includes a plurality of racks (shown in FIGS. 4-5), and each rack includes a plurality of nodes (shown in FIG. 5), which are also called servers, hosts, or machines throughout the present disclosure”) and configured to provide one or more services of a customer subscription (¶ 29, “A virtual machine deployment may be associated with a subscription. A subscription can generally refer to a set of identified resources or selected offerings (e.g., virtual machine deployment instance) from a cloud computing system”);
identifying, based on the deployment data, a trigger condition (¶ 27, “The confidence score and the confidence score threshold can be used to determine whether to generate or recommend deploying the predicted rightsized deployment configuration of the VM deployment,” the threshold corresponds to the trigger condition) associated with a predicted mismatch in utilization of available computing resources allocated for the first set of virtual machines in accordance with the customer subscription (¶ 27, “The predicted maximum resource utilization can be, for example, 10% CPU, 50% memory, 20% disk, and 5% network,” predicted resource usage well below 100% corresponds to mismatch in utilization);
generating a goal state of the customer subscription based on the deployment data (¶ 45, “At 220, based on the predicted resource utilization and the confidence score meeting the confidence score threshold, the predictive rightsizing controller generates a predicted rightsized deployment configuration for the VM deployment”), the goal state including a second set of virtual machines having rightsized specifications based on the deployment data (¶ 27, “a predicted rightsized deployment configuration (e.g., 5 A2s) for the VM deployment is determined”) and capable of providing the one or more services of the customer subscription (¶ 29, “A virtual machine deployment may be associated with a subscription”); and
providing the goal state to a server device on the node cluster (¶ 45, “At 224, communicate the predicted rightsized deployment configuration to an interface for the customer”).
Fontoura does not teach; however, Breitgand discloses: providing the goal state to the server device causes a transition from a current state of the customer subscription including the first set of virtual machines to the goal state of the customer subscription including the second set of virtual machines (¶ 36, “the module 300 is operative to execute a reconfiguration of the number and/or capacity of resource elements assigned to each virtual machine without any need for interruption of the virtual machine's operation”).
It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the invention, to have applied the known technique of providing the goal state to the server device causes a transition from a current state of the customer subscription including the first set of virtual machines to the goal state of the customer subscription including the second set of virtual machines, as taught by Breitgand, in the same way to the providing the goal state to a server device, as taught by Fontoura. Both inventions are in the field of right-sizing VM deployments, and combining them would have predictably resulted in “an ability to quickly provision (and de-provision) virtual machines (VMs),” as indicated by Breitgand (¶ 2).
Regarding claim 2, Fontoura teaches: The method of claim 1, further comprising generating a predicted utilization of computing resources on the node cluster of the cloud computing system based on the deployment data (¶ 44, “At 214, based on collected data, the prediction engine generates a predicted resource utilization for the virtual machine deployment”).
Regarding claim 3, Breitgand teaches: The method of claim 2, wherein identifying the trigger condition comprises determining that the first set of virtual machines utilizes a number of compute cores that is less than a maximum number of compute cores allocated for the first set of virtual machines (¶ 34, “a virtual machine 202 is configured to include four virtual processors, CPU 1, CPU 2, CPU 3, and CPU 4” and “In a first state, which in this embodiment is a light load state, two virtual processors, CPU 3 and CPU 4, are eclipsed and one virtual processor, CPU 2, is capped at about half of its maximum operating frequency” and ¶ 36, “The virtual machine resizing module 300 is operative to continuously (or at least periodically) monitor resource usage of one or more virtual machines, VM1, VM2, . . . , VMM-2, VMM-1, VMM, running on a cloud 302, in addition to monitoring resource availability on such cloud, and, in accordance with a set of rules defining tolerable upper and lower limits on resource usage”).
Regarding claim 5, Breitgand teaches: The method of claim 1, wherein identifying the trigger condition comprises estimating that the deployment of the first set of virtual machines will result in the predicted mismatch in utilization of available computing resources relative to a deployment on the second set of virtual machines based on the rightsized specifications of the second set of virtual machines (¶ 27, “Based on the predicted resource utilization, a predicted rightsized deployment configuration (e.g., 5 A2s) for the VM deployment is determined,” predicted rightsized deployment configuration corresponds to the rightsized specifications).
Claims 9-11, 13, and 17-19 recite commensurate subject matter as claims 1-3 and 5. Therefore, they are rejected for the same reasons.
Claim(s) 4 and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fontoura and Breitgand, as applied above, and further in view of David (US 2018/0373552).
Regarding claim 4, Fontoura and Breitgand do not teach; however, David discloses: receiving an indication that a new generation of hardware has been added to the node cluster of the cloud computing system (¶ 16, “Over time, the datacenter manager may replace and upgrade the compute and network hardware in datacenter 100 (i.e., processing units, CPUs, memory, routers, switches, etc.) as existing hardware fails or becomes obsolete or inefficient”), wherein identifying the trigger condition is based on the new generation of hardware being added to the node cluster of the cloud computing system (¶ 22, “As the datacenter is updated from one hardware generation to another, the service provider can define a resource constraint set or VM model for each hardware generation. For example, resource constraint set 207 for the physical server type A 201 hardware generation may define a percentage X of the CPU resources to be used when configuring a tenant's VMs 205”).
It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the invention, to have applied the known technique of receiving an indication that a new generation of hardware has been added to the node cluster of the cloud computing system, wherein identifying the trigger condition is based on the new generation of hardware being added to the node cluster of the cloud computing system, as taught by David, in the same way to transitioning from a current state to a goal state, as taught by Fontoura and Breitgand. Both inventions are in the field of reconfiguring datacenter resources, and combining them would have predictably resulted in a system such that “performance can be normalized across different server hardware generations and the cloud service provider can deploy the same virtual machine on different hardware,” as indicated by David (¶ 5).
Claim 12 recites commensurate subject matter as claim 4. Therefore, it is rejected for the same reason.
Claim(s) 6, 7, 14, and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fontoura and Breitgand, as applied above, and further in view of Featonby (US 2020/0310853).
Regarding claim 6, Fontoura and Breitgand do not teach; however, Featonby discloses: the first set of virtual machines comprises virtual machines of a first virtual machine family associated with a first set of virtual machine specifications (¶ 54, “computing devices 112(1) may support one or more VM instances 114(1)-114(N) that are of a first VM instance type, and computing devices 112(2) may support one or more VM instances 116(1)-116(N) that are of a second VM instance type”), and wherein the second set of virtual machines comprises virtual machines of a second virtual machine family associated with a second set of virtual machine specifications (¶ 60, “the VM instance types 130 can include compute optimized types, memory optimized types, accelerated optimized types, storage optimized types, and/or network throughput optimized types. As a specific example, a VM instance type 130 that is compute optimized may be allocated use of 4 vCPUs of 3.0 GHz processors”).
It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the invention, to have applied the known technique of the first set of virtual machines comprises virtual machines of a first virtual machine family associated with a first set of virtual machine specifications, and wherein the second set of virtual machines comprises virtual machines of a second virtual machine family associated with a second set of virtual machine specifications, as taught by Featonby, in the same way to the first and second sets of virtual machines, as taught by Fontoura and Breitgand. Both inventions are in the field of cloud based virtual machines, and combining them would have predictably resulted in a method to “help prevent underutilization of computing resources of a service provider network, which reduces the amount of computing resources that are (i) allocated or reserved for VM instances,” as indicated by Featonby (¶ 46).
Regarding claim 7, Fontoura and Breitgand do not teach; however, Featonby discloses: identifying the second set of virtual machines from a plurality of pre-configured virtual machines available for deployment on the node cluster (¶ 59, “The optimization service 106 includes the optimization component 126 that is configured to determine one or more VM instance types 130 that are optimized to support the workload 136 on behalf of the user 105”).
It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the invention, to have applied the known technique of identifying the second set of virtual machines from a plurality of pre-configured virtual machines available for deployment on the node cluster, as taught by Featonby, in the same way to generating the goal state, as taught by Fontoura and Breitgand. Both inventions are in the field of cloud based virtual machines, and combining them would have predictably resulted in a method to “help prevent underutilization of computing resources of a service provider network, which reduces the amount of computing resources that are (i) allocated or reserved for VM instances,” as indicated by Featonby (¶ 46).
Claims 14 and 15 recite commensurate subject matter as claims 6 and 7. Therefore, they are rejected for the same reasons.
Claim(s) 8, 16, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fontoura, Breitgand, and Featonby, as applied above, and further in view of Budzinski (US 2015/0355927).
Regarding claim 8, Fontoura, Breitgand, and Featonby do not teach; however, Budzinski discloses: a subset of virtual machine types available for deployment on the node cluster (¶ 63, “Requests associated with the application may be routed among two or more sets of instances at 304, where each of the two or more sets of instances have a different, corresponding instance type of two or more instance types including the first instance type and one or more additional instance types”) based on a determined compatibility of the plurality of pre-configured virtual machines with the first set of virtual machines in hosting the one or more services of the customer subscription (¶ 63, “the metrics may be collected during a particular period of time. The metrics may be analyzed at 308 to identify an optimal instance type for the application”).
It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the invention, to have applied the known technique of a subset of virtual machine types available for deployment on the node cluster based on a determined compatibility of the plurality of pre-configured virtual machines with the first set of virtual machines in hosting the one or more services of the customer subscription, as taught by Budzinski, in the same way to the plurality of pre-configured virtual machines, as taught by Fontoura, Breitgand, and Featonby. Both inventions are in the field of cloud based virtual machines, and combining them would have predictably resulted in “identifying optimal instance types for virtual machines,” as indicated by Budzinski (¶ 1).
Claims 16 and 20 recite commensurate subject matter as claim 8. Therefore, they are rejected for the same reasons.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Poothia (US 2020/0042338) teaches “Based upon the needs of the virtual machine as identified from the current memory usage profiles, the memory resizing recommendation system 340 uses the historical memory usage profiles to predict the future memory usage profiles, and then determine a revised memory allocation based on the future memory usage profiles” (¶ 79), which relates to the disclosed predicting need and revising VM resource allocation based on collected usage data.
Dow (US 2016/0314011) teaches “Candidate paths are formed from the origin state 202 through a plurality of intermediate states 206 to the goal state 204. A state may be referred to as a parent state if it is a transition state that occurs after the origin state 202” (¶ 52), which relates to the disclosed generating a goal state of a VM deployment and transitioning from a current state to the goal state.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JACOB D DASCOMB whose telephone number is (571)272-9993. The examiner can normally be reached M-F 9:00-5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Pierre Vital can be reached at (571) 272-4215. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JACOB D DASCOMB/ Primary Examiner, Art Unit 2198
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