DETAILED ACTION
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 .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract ide without significantly more.
Step 1: Claim 1 recites “a method comprising: partitioning a population of compute nodes of a cloud platform into maintenance domains” which is a method.
Claim 10 recites “one or more non-transitory computer-readable media storing instructions which, when executed by one or more computing devices, cause: partitioning a population of compute nodes of a cloud platform into maintenance domains” which is a manufacture.
Step 2A Prong 1:
Claims 1 and 10 recite “partitioning,” “determining,” “determining,” “selecting,” and “placing” which specifically recite “partitioning a population of compute nodes of a cloud platform into maintenance domains (MDs),” “for a target virtual machine, determining a compute-node on which to place the target virtual machine:,” “for the target virtual machine, determining, for each compute-node in a set of candidate compute nodes, a placement context score based on a plurality of metrics; wherein each metric of the plurality of metrics corresponds to a goal; wherein the plurality of metrics includes at least one MD-aware metric,” and “performing a second set of autoscaling actions using a second autoscaler in the network-based data system, the performing the second set of autoscaling actions,” “selecting a particular compute-node for placement of the target virtual machine based on the placement context scores determined for the target virtual machine;,” and “placing the VM on the particular compute-node.” These limitations are processes that, under their broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitation of generic computer components. That is, other than reciting (from claims 1 and 10) “partitioning a population of compute nodes of a cloud platform into maintenance domains (MDs),” “wherein each compute node in the population of compute nodes belongs to exactly one of the MDs,” “wherein maintenance is performed for the cloud platform using rolling maintenance based on the MDs,” (form claim 10) “one or more non-transitory computer-readable media storing instructions which, when executed by one or more computing devices, cause” nothing in the claim element precludes the step from practically being performed in a human mind or with the aid of pen and paper. For example, “determining,” “determining,” and “determining” in the context of this/these claim(s) encompasses a user mentally, and with the aid of pen and paper writing the changes down on a sheet of paper and examine the list to identify the relevant ones (rationale).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas (concepts performed in the human mind including an observation, evaluation, judgment, and opinion).
Step 2A Prong 2:
This judicial exception is not integrated into a practical application. The claims recites the additional elements
(from claims 1 and 10) “wherein each compute node in the population of compute nodes belongs to exactly one of the MDs;,” “wherein maintenance is performed for the cloud platform using rolling maintenance based on the MDs;,” and (from claim 10) “one or more non-transitory computer-readable media storing instructions which, when executed by one or more computing devices, cause” these limitations are recited at a high-level of generality (i.e., as a generic network system and generic computing resources for said generic network system performing a generic computer network function(s)) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. (see MPEP 2106.05(f)).
The claims are directed to an abstract idea.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The limitations (from claims 1 and 10) “wherein each compute node in the population of compute nodes belongs to exactly one of the MDs;,” “wherein maintenance is performed for the cloud platform using rolling maintenance based on the MDs;,” and (from claim 10) “one or more non-transitory computer-readable media storing instructions which, when executed by one or more computing devices, cause” are recognized by the courts as well-understood, routine, and conventional activities when they are claimed in a merely generic manner.
As such, claims 1 and 10 are rejected under 35 U.S.C. 101.
Claims 2-9, and 11-18 depend from claims 1 and 10 and do not add additional elements that would overcome the rejection of claims 1 or 10 and are rejected for at least this reason and the analysis below:
2. The method of Claim 1 wherein the at least one MD-aware metric includes a metric associated with a goal of increasing availability, during rolling maintenance, of virtual machines that belong a target virtual machine cluster, wherein the target virtual machine cluster is a virtual machine cluster to which the target virtual machine belongs (insignificant extra solution activity - generic data processing)
3. The method of Claim 1 wherein the at least one MD-aware metric includes a metric associated with a goal of avoiding too-closely-timed maintenance events for virtual machines that belong a target virtual machine cluster, wherein the target virtual machine cluster is a virtual machine cluster to which the target virtual machine belongs (insignificant extra solution activity - generic data processing)
4. The method of Claim 1 wherein the at least one MD-aware metric includes a metric associated with a goal of evenly spreading virtual machines that are hosted by the cloud platform among the MDs (insignificant extra solution activity - generic data processing)
5. The method of Claim 1 further comprising determining the set of candidate nodes for the target virtual machine by filtering the population of compute nodes based on constraints (mental process – evaluation)
6. The method of Claim 5 wherein in constraints used to filter the population of compute nodes include a particular constraint that specifies a maintenance policy associated with a target virtual machine cluster, wherein the target virtual machine cluster is a virtual machine cluster to which the target virtual machine belongs (insignificant extra solution activity - generic data processing)
7. The method of Claim 6 further comprising receiving input, for a customer associated with the target virtual machine cluster, that indicates the maintenance policy to associate with the target virtual machine cluster (insignificant extra solution activity - generic data gathering)
8. The method of Claim 7 wherein the input indicates one of:
a first maintenance policy that indicates all virtual machines in the target virtual machine cluster are to be placed in a single MD; (insignificant extra solution activity - generic data processing)
a second maintenance policy that indicates all virtual machines in the target virtual machine cluster are to be split between two MDs; or (insignificant extra solution activity - generic data processing)
a third maintenance policy that indicates all virtual machines in the target virtual machine cluster are to be spread among as many MDs as possible (insignificant extra solution activity - generic data processing)
9. The method of Claim 1 wherein the plurality of metrics includes one or more non-MD- aware metrics, wherein the one or more non-MD-aware metrics include at least one of: a metric relating to maximizing resource utilization, a metric relating to maximizing spread among compute-nodes, and metric relating to minimizing fragmentation (insignificant extra solution activity - generic data processing)
11. The one or more non-transitory computer-readable media of Claim 10 wherein the at least one MD-aware metric includes a metric associated with a goal of increasing availability, during rolling maintenance, of virtual machines that belong a target virtual machine cluster, wherein the target virtual machine cluster is a virtual machine cluster to which the target virtual machine belongs (insignificant extra solution activity - generic data processing)
12. The one or more non-transitory computer-readable media of Claim 10 wherein the at least one MD-aware metric includes a metric associated with a goal of avoiding too-closely-timed maintenance events for virtual machines that belong a target virtual machine cluster, wherein the target virtual machine cluster is a virtual machine cluster to which the target virtual machine belongs (insignificant extra solution activity - generic data processing)
13. The one or more non-transitory computer-readable media of Claim 10 wherein the at least one MD-aware metric includes a metric associated with a goal of evenly spreading virtual machines that are hosted by the cloud platform among the MDs (insignificant extra solution activity - generic data processing)
14. The one or more non-transitory computer-readable media of Claim 10 wherein the instructions include instructions for determining the set of candidate nodes for the target virtual machine by filtering the population of compute nodes based on constraints (mental process – evaluation)
15. The one or more non-transitory computer-readable media of Claim 14 wherein the constraints used to filter the population of compute nodes include a particular constraint that specifies a maintenance policy associated with a target virtual machine cluster, wherein the target virtual machine cluster is a virtual machine cluster to which the target virtual machine belongs (insignificant extra solution activity - generic data processing)
16. The one or more non-transitory computer-readable media of Claim 15 wherein the instructions include instructions for receiving input, for a customer associated with the target virtual machine cluster, that indicates the maintenance policy to associate with the target virtual machine cluster (insignificant extra solution activity - generic data gathering)
17. The one or more non-transitory computer-readable media of Claim 16 wherein the input indicates one of: a first maintenance policy that indicates all virtual machines in the target virtual machine cluster are to be placed in a single MD; a second maintenance policy that indicates all virtual machines in the target virtual machine cluster are to be split between two MDs; or a third maintenance policy that indicates all virtual machines in the target virtual machine cluster are to be spread among as many MDs as possible (insignificant extra solution activity - generic data processing)
18. The one or more non-transitory computer-readable media of Claim 10 wherein the plurality of metrics includes one or more non-MD-aware metrics, wherein the one or more non- MD-aware metrics include at least one of: a metric relating to maximizing resource utilization, a metric relating to maximizing spread among compute-nodes, and metric relating to minimizing fragmentation (insignificant extra solution activity - generic data processing).
Other References Cited Not Relied Upon
Sheng et al. (US 2020/0167182) discloses node maintenance manners that divide existing virtual networks into unstructured and structured virtual networks.
Antony et al (US 2017/0242764) discloses network portioned hosts placed into self-maintenance mode once VM network connections are lost.
Guo et al. (US 2019/0018716) discloses extra configurations on physical switches that may introduce maintenance complexity for many network partition cases.
Conclusion
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/CRAIG C DORAIS/Primary Examiner, Art Unit 2198
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