DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. Claims 1–18 are presented for examination in a continuation application filed on 05/07/2024.
This instant application No. 18/657,204 is a continuation of:
application No. 17 /854,695, filed on Jun. 30, 2022, now Pat. No. 12,008,408, which is a continuation of:
application No. 16/566,209, filed on Sep. 10, 2019, now Pat. No. 11,379,266.
Drawings
3. The drawings were received on 05/07/2024 (in the filings). These drawings are acceptable.
Double Patenting
4. The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO internet Web site contains terminal disclaimer forms which may be used. Please visit http://www.uspto.gov/forms/. The filing date of the application will determine what form should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
5. Claims 1–18 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1–24 of U.S. Patent No. 11,379,266 B2 (“’266 Patent”) and further in view of Dailianas et al., 2020/0314174 A1 (“Dailianas”), since the claims, if allowed, would improperly extend the “right to exclude” already granted in the patent.
Dailianas is cited and applied below, to reject each of the dependent claims under 103.
It would have been obvious to a person of ordinary skill in the art to combine the claims of the reference patent with the teachings of Dailianas to provide for the user input and/or confirmation of the evaluation before performing the migration
6. Although the claims at issue are not identical, they are not patentably distinct (nonobvious) from each other, because at least some of the subject matter claimed in the instant application is already fully disclosed in the issued ’266 patent.
For purposes of illustration, a table has been constructed below to compare the two independent method claims.
Instant Application No. 18/657,204
Issued ’266 Patent
1. A computer-implemented method for providing a cloud advisory service for a cloud computing service, comprising:
obtaining resource usage data for a set of database resources of a first set of one or more compute instances;
determining, based on the resource usage data, a first level of performance and cost;
determining a first compute instance of the first set of compute instances, wherein the first compute instance has a first instance type corresponding with a second instance type available in the cloud computing service different from the first instance type;
predicting, based on the resource usage data, a second level of performance and cost by replacing at least the first instance with the second instance type;
comparing the first level of performance and cost and second level of cost performance and cost; and
making, based on the comparing, a recommendation to migrate the set of one or more database resources to the second instance type having the second level of performance and cost.
14. A computer-implemented method for providing an instance advisory service for an Infrastructure as a Service (IaaS), comprising:
monitoring a resource utilization of a set of resources of one or more instances, the resource utilization corresponding to a first level of performance and cost;
determining, based on the resource utilization, whether there is an instance type for at least one of the one or more instances, with a resource profile, that will provide a second level of performance and cost that is closer to a default level of performance and cost than the first level of performance and cost;
causing an evaluation of the recommended instance type when the recommended instance type is different from a current instance type of the at least one of the one or more instances, the evaluation includes provisioning, as part of an experiment, one or more instances of the recommended instance type to service work associated with an application cluster; and
performing, based on the determining, one of making and not making a recommendation to replace the instance type of the at least one of the one or more instances.
7. Claims 1–18 are also further rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1–24 of each of U.S. Patent No. US 11,977,921 B2, US 11,977,920 B2, US 12,008,408 B2, US 12,008,407 B2, and US 12,321,784 B2, belonging to the SAME APPLICATION FAMILY, and each further in view of Dailianas et al., 2020/0314174 A1 (“Dailianas”), since the claims, if allowed, would improperly extend the “right to exclude” already granted in the patent.
Dailianas is cited and applied below, to reject each of the dependent claims under 103.
It would have been obvious to a person of ordinary skill in the art to combine the claims of each of the reference patent with the teachings of Dailianas to provide for the user input and/or confirmation of the evaluation before performing the migration.
8. Although the claims at issue are not identical, they are not patentably distinct (nonobvious) from each other, because at least some of the subject matter claimed in the instant application is already fully disclosed in these issued patents.
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.
9. Claims 1–18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
10. As to independent claim 1, the claim recites:
“determining, based on the resource usage data, a first level of performance and cost;
determining a first compute instance of the first set of compute instances, wherein the first compute instance has a first instance type corresponding with a second instance type available in the cloud computing service different from the first instance type;
predicting, based on the resource usage data, a second level of performance and cost by replacing at least the first instance with the second instance type;
comparing the first level of performance and cost and second level of cost performance and cost”
As to independent claims 7 and 13, they each recite similar language of commensurate scope as claim 7.
These limitations, as currently drafted and within their respective claim, represent processes that, under a broadest reasonable interpretation, covers performance in the mind (including observation, evaluation, judgment, opinion, etc.) but for the recitation of generic computer components.
That is, other than reciting the use of
“non-transitory computer-readable memory (NTCRM) comprising instructions stored thereon” (claim 7), and
“memory circuitry to store program code of a resource analyzer, a resource configuration determiner, and a resource type recommender; and processor circuitry connected to the memory circuitry” (claim 13),
to perform these steps, nothing in the claim element precludes the step from practically being performed in the mind or using pencil and paper (see MPEP 2106.04(a)(2) – Examples of Concepts The Courts Have Identified As Abstract Ideas, discussing abstract ideas or concepts relating to organizing or analyzing information in a way that can be performed mentally or is analogous to human mental work).
For example, but for the use of generic computers,
the performance of these steps in the context of the claims reasonably encompasses the user mentally and/or manually performing these steps.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application (under Prong Two of Step 2A)
(I) Generic Computing Device
For instance, claim 7 recite the additional element of:
“non-transitory computer-readable memory (NTCRM) comprising instructions stored thereon,” and
claim 13 recites a ““memory circuitry to store program code of a resource analyzer, a resource configuration determiner, and a resource type recommender; and processor circuitry connected to the memory circuitry,”
that perform these steps.
These computer components, functionalities, and/or services are all recited at a high-level of generality (i.e., as a generic computing device performing a generic computer function of processing and outputting data) such that it amounts no more than mere instructions to apply the exception using a generic computer components such as processors, basic processor instructions and/or software components or programs.
Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
(II) Data Collection
As presented, the claims also include the additional element of:
(a) “obtaining resource usage data for a set of database resources of a first set of one or more compute instances.”
However, merely obtaining or receiving data or input for processing (or other uses) simply does not “integrate” the abstract idea into a practical application which improves the functioning of a computer or other technology or technological field.
Moreover, the courts have also held that limitations which merely adds insignificant extra-solution activity to the judicial exception does not integrate a judicial exception into a practical application.
As discussed below and set forth in MPEP § 2106.05(g), the mere collection and receiving of information for processing essentially amounts to data gathering and storing (using processors, basic processor instructions and/or software components or programs) and therefore is consider an “insignificant extra-solution activity.”
Accordingly, the additional elements of the claims, viewed individually and as an ordered combination, added nothing to the implementation of a mental process on an unspecified, “generic” computer and therefore failed to transform the abstract idea nature of the claims into a patent-eligible application.
(III) Data Output
Additionally, as presented, the claims also includes the additional elements of:
(b) “making, based on the comparing, a recommendation to migrate the set of one or more database resources to the second instance type having the second level of performance and cost.”
However, merely presenting or outputting the information from one computing device to another simply does not “integrate” the abstract idea into a practical application which improves the functioning of a computer or other technology or technological field, absent a further step or activity that executes or performs tasks or controls, and thereby effecting a change or improvement to the functioning of the computer or the technological field or environment.
Moreover, the courts have also held that limitations which merely adds insignificant extra-solution activity to the judicial exception does not integrate a judicial exception into a practical application.
As discussed below and set forth in MPEP § 2106.05(g), the mere outputting of data or information is consider an “insignificant extra-solution activity.”
Accordingly, the additional elements of the claims, viewed individually and as an ordered combination, added nothing to the implementation of a mental process on an unspecified, “generic” computer and therefore failed to transform the abstract idea nature of the claims into a patent-eligible application.
(IV) Particular Technological Environment or Field Of Use
As shown above, the claims also include the elements of:
(1) “resource usage data for a set of database resources of a first set of one or more compute instances,”
(2) “a first level of performance and cost,”
(3) “a first compute instance of the first set of compute instances, wherein the first compute instance has a first instance type corresponding with a second instance type available in the cloud computing service different from the first instance type,” and
(3) “a second level of performance and cost.”
These exemplary elements however merely describes the general technical or computing environment (within which the claimed steps or processes operate) and restrict the processed information or data to a particular type or category (without imposing any functional claim limitations, activities, or steps).
Limitations that generally link the use of the judicial exception to a particular technological environment or field of use, neither meaningfully limit the claim nor transform (the abstract idea nature of) the claim to a particular useful application to improve the functioning of a computer or any other technology.
Under Step 2B of the 101 analysis:
The claims do not include additional elements, alone or in combination, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than generic computing components and field of use/technological environment which do not amount to significantly more than the abstract idea.
As claimed, the ““non-transitory computer-readable memory (NTCRM) comprising instructions stored thereon,” and “memory circuitry to store program code of a resource analyzer, a resource configuration determiner, and a resource type recommender; and processor circuitry connected to the memory circuitry,”
merely encompasses generic computing components (e.g. processors, container-based or virtualized computing environment) recited at a high-level of generality, executing one or more steps of the claims.
Moreover, the activity of “mere data gathering” have also been found by the courts to be “insignificant extra-solution activity” as set forth in MPEP 2106.05(g)(3) Insignificant Extra-Solution Activity, describing that in determining whether an additional element is insignificant extra-solution activity, one may factoring into consideration whether the limitation amounts to necessary data gathering and outputting, (i.e., all uses of the recited judicial exception require such data gathering or data output).
As recited, the step of”
(a) “obtaining resource usage data for a set of database resources of a first set of one or more compute instances”
are mere data gathering activities for additional processing (to obtaining or receiving inputs for processing).
Moreover, the activity of “outputting information” have also been found by the courts to be “insignificant extra-solution activity” as set forth in 2106.05(g)(3) Insignificant Extra-Solution Activity, describing that in determining whether an additional element is insignificant extra-solution activity, one may factoring into consideration whether the limitation amounts to necessary data gathering and outputting, (i.e., all uses of the recited judicial exception require such data gathering or data output).
As recited, the step of:
(b) “making, based on the comparing, a recommendation to migrate the set of one or more database resources to the second instance type having the second level of performance and cost”
are merely data output activities for additional processing.
Additionally, the computing activity of a) receiving or transmitting data over a network, and b) storing and retrieving information in memory (for distribution and dissemination, as an example), set forth in 2106.05(d)(II), setting forth that courts have recognized computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
As recited, the step of
(b) “making, based on the comparing, a recommendation to migrate the set of one or more database resources to the second instance type having the second level of performance and cost.”
merely involving the sending, distribution, and dissemination of data or output across computing devices.
Accordingly, the additional step(s) or element(s) of the claims, viewed individually and as an ordered combination, added nothing to the implementation of a mental process on an unspecified, “generic” computer and therefore failed to transform the abstract idea nature of the claims into a patent-eligible application.
11. As to dependent claims 2–6, 8–12, and 14–18, each of these claims either (1) recites additional step(s) that covers performance in the mind; or (2) merely restricts or links the process step, information or data to a particular type, technological environment, or field of use; (3) amounts to insignificant extra-solution activity to the judicial exception such as data input and output/transmission; or (4) recites a function which amounts to no more than a recitation of the words “apply it” (or an equivalent) and is no more than mere instructions to implement an abstract idea or other exception on a computer; and thus as a whole is also directed and confined to the same process set forth in claims 1, 7, and 13. Therefore, these claims do not individually or collectively add an inventive concept or additional element(s) amounting to significantly more than the abstract idea itself. These claims are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
For instance, dependent claim 2, reciting “collecting performance data for a workload from the set of database resources” merely amounts to insignificant extra-solution activity to the judicial exception such as data input and output/transmission.
Dependent claim 3, reciting “wherein the performance data comprises at least one selected from the group consisting of: CPU usage, memory usage, …” merely additionally restricts or links the process step, information or data to a particular type, technological environment, or field of use, using generic computer/networking components and computer programs.
Dependent claims 4–6, reciting various characteristics and manners in which performance data is collected, merely amounts to insignificant extra-solution activity to the judicial exception such as data input and output/transmission and additionally restricts or links the process step, information or data to a particular type, technological environment, or field of use, using generic computer/networking components and computer programs.
As to dependent claims 8–12 and 14–18, they are the corresponding system and computer program product claims correspond to at least one of claims 2–6. Therefore, these claims do not individually or collectively 1) integrated the abstract idea into a practical application, nor do they 2) include additional element(s) amounting to significantly more than the abstract idea itself.
Examiner’s Remarks
12. Examiner refers to and explicitly cites particular pages, sections, figures, paragraphs or columns and lines in the references as applied to Applicant’s claims to the extent practicable to streamline prosecution.
Although the cited portions of the references are representative of the best teachings in the art and are applied to meet the specific limitations of the claims, other uncited but related teachings of the references may be equally applicable as well. It is respectfully requested that, in preparing responses to the rejections, the Applicant fully considers not only the cited portions of the references, but also the references in their entirety, as potentially teaching, suggesting or rendering obvious all or one or more aspects of the claimed invention.
Abbreviations
13. Where appropriate, the following abbreviations will be used when referencing Applicant’s submissions and specific teachings of the reference(s):
i. figure / figures: Fig. / Figs.
ii. column / columns: Col. / Cols.
iii. page / pages: p. / pp.
References Cited
14. (A) Dailianas et al., 2020/0314174 A1 (“Dailianas”).
(B) Borthakur et al., US 2015/0347183 A1 (“Borthakur”).
Notice re prior art available under both pre-AIA and AIA
15. 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 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.
Claim Rejections - 35 USC § 103
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 of this title, 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.
A.
16. Claims 1–18 are rejected under 35 U.S.C. 103 as being unpatentable over (A) Dailianas in view of (B) Borthakur.
See “References Cited” section, above, for full citations of references.
17. Regarding claim 1, (A) Dailianas teaches/suggests the invention substantially as claimed, including:
“A computer-implemented method for providing a cloud advisory service for a cloud computing service, comprising:
obtaining resource usage data for a set of database resources of a first set of one or more compute instances”
(¶ 8: management of resources and performance in cloud-based resource provisioning environments;
¶ 10: systems, apparatus and methods contemplated and disclosed herein can be used … to recommend and eventually migrate workloads among multiple providers;
¶ 160: recommend and eventually migrate workloads back and forth among multiple providers (private and/or public) in a cloud environment;
¶ 11: (a) determining, by a consumer manager running on a data processor in a computer system, a cost in currency units for running a computational workload on a first computational resource provider, the workload having a resource requirement corresponding to a quantity of one or more resources selected from CPUs, memory, databases, network bandwidth ….;
¶ 14: The cost of running the workload on the second provider may be based at least in part on the utilization of one or more resources of the first provider and/or a determined performance characteristic of the first or second provider;
¶ 17: workload has a resource requirement corresponding to a quantity of one or more resources selected from CPUs, memory, databases;
¶ 58: a containerized database server (shown as the application 136));
“determining, based on the resource usage data, a first level of performance and cost”
(¶ 14: The cost of running the workload on the second provider may be based at least in part on the utilization of one or more resources of the first provider and/or a determined performance characteristic of the first or second provider;
¶ 29: The cost of moving can be part of the comparison between two or more alternatives ( e.g., keeping a resource, such as memory, in an existing infrastructure-which may involve physically expanding the resource to accommodate increased utilization-or moving the resource to an external cloud provider);
“determining a first compute instance of the first set of compute instances, wherein the first compute instance has a first instance type corresponding with a second instance type available in the cloud computing service different from the first instance type”
(¶ 14: The cost of running the workload on the second provider may be based at least in part on the utilization of one or more resources of the first provider and/or a determined performance characteristic of the first or second provider;
¶ 29: The cost of moving can be part of the comparison between two or more alternatives ( e.g., keeping a resource, such as memory, in an existing infrastructure-which may involve physically expanding the resource to accommodate increased utilization-or moving the resource to an external cloud provider;
¶ 170: decisions can be based on a trade-off-between price offered by a CSP and its historical and/or anticipated performance metrics. For example, when deciding between deployment with competing first and second CSPs, the systems, apparatus and methods can be used to weigh the benefits and tradeoffs between selecting a first CSP having superior performance and commensurately higher price of a resource (e.g., CPU) versus a second CSP having inferior performance and a lower price for the resource);
“predicting, based on the resource usage data, a second level of performance and cost by replacing at least the first instance with the second instance type”
(¶ 170: decisions can be based on a trade-off-between price offered by a CSP and its historical and/or anticipated performance metrics. For example, when deciding between deployment with competing first and second CSPs, the systems, apparatus and methods can be used to weigh the benefits and tradeoffs between selecting a first CSP having superior performance and commensurately higher price of a resource (e.g., CPU) versus a second CSP having inferior performance and a lower price for the resource;
¶ 111: in one approach, the cost of running a workload on a resource provider begins with the nominal price charged by the provider, but is adjusted upward if the resource provider delivers performance below a quality metric (e.g., average performance) or downward if the resource provider delivers performance above the quality metric. In another approach, the performance metric is considered separately from cost but the resource budget is adjusted upward if performance is to be considered a factor in the procurement decision. In this way, performance can be weighted separately as a decision-making factor and the larger budget will permit selection of a higher-cost but better-performing resource provider;
¶ 223: The pricing can further extend to differentiate between service providers based on performance as well as cost. This adds a TRADEOFF BETWEEN PRICE AND PERFORMANCE. For example, if SP 1 has better CPU performance than SP N the price of CPU on a SP 1 may be effectively cheaper, resulting in workloads consuming a significant portion of CPU preferring to run on a SP 1 even though the cost of running on a SPN is cheaper. Stated differently, superior performance of a cloud provider can render a nominally more expensive resource as a more cost effective option. For example, if a first provider has superior CPU performance compared to a second provider, it is possible that usage of the first provider, even at a higher nominal cost for CPU usage, results in overall cost savings compared to usage of the second provider, with a lower nominal cost (but also lower performance) for CPU usage);
“comparing the first level of performance and cost and second level of cost performance and cost”
(¶ 170, ¶ 111, and ¶ 223, teaching making a decision to move/migrate workloads based on cost and performance, as applied above).
“making … a recommendation to migrate the set of one or more database resources to the second instance type having the second level of performance and cost”
(¶ 10: systems, apparatus and methods contemplated and disclosed herein can be used … to recommend and eventually migrate workloads among multiple providers;
¶ 160: recommend and eventually migrate workloads back and forth among multiple providers (private and/or public) in a cloud environment).
Dailianas does not teach that the recommendation is performed “based on the comparing.”
(B) Borthakur, however teaches or suggests:
“making, based on the comparing, a recommendation to migrate …”
(¶ 46: The workload may then use those estimated costs to compare the resource costs associated with operating the workload in a computing resource service provider environment to the resource costs associated with operating the workload in a customer datacenter
environment 614 … Finally, based at least in part on the actual and/or estimated ROI, the workload analysis service may determine if the migration is advantageous 616 and, if not, may not recommend migration 618. If the migration is advantageous 616, the workload analysis service may perform one or more operations to recommend migration 620).
See additionally, Borthakur, teaching database servers and database storage systems in resource service providers
(¶ 33: “computing resource service provider may provide access to one or more host machines as well as provide access to computer services such as virtual machine (VM) instances, automatic scaling groups, file-based database storage systems;
¶ 59: In embodiments utilizing a web server, the web server can run any of a variety of server or mid-tier applications, including Hypertext Transfer Protocol ("HTTP") servers … Apache servers and business application servers. The server(s) also may be capable of executing programs or scripts in response to requests from user devices, such as by executing one or more web applications …. The server(s) may also include database servers).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of (B) Borthakur with those of (A) Dailianas to recommend workload migration after performing a cost-performance trade-off analysis. The motivation or advantage to do so is to provide for the user input and/or confirmation of the evaluation before performing the migration.
The Examiner notes that (B) Borthakur broadly and similarly teaches the invention as claimed, and thus may be generally combined with (A) Dailianas’s teachings.
(see Borthakur’s abstract: Techniques for identifying a candidate workload which may be a suitable candidate for migration from a first location to a second location are described herein. A set of suitability measurements associated with a computer system resource operating in the first location is received, the set of suitability measurements including, for example, resource usage values for one or more resources associated with the workload. Based at least in part on one or more statistical calculations on the set of suitability measurements exceeding one or more thresholds, recommendations are made about whether to migrate the workload from the first location to the second location).
18. Regarding claim 2, Dailianas and Borthakur teach/suggest:
“collecting performance data for a workload from the set of database resources”
(Dailianas, ¶ 128: monitors storage or network I/O usage by one or more containers, such as by collecting data from one or more of the container system;
¶ 129: periodically estimates both the average storage I/O capacity used and the average available I/O capacity, and updates the respective attributes of the storage I/O objects;
see ¶ 58: a containerized database server;
Borthakur, ¶ 21: computer system entities may utilize computer system resources including, but not limited to, CPUs, memory, disk I/O, disk storage, application resources, other hardware resources, virtual hardware resources and other such computer system resources;
¶ 22: resource usage may be sampled and/or otherwise periodically monitored. Other resource usage measurements may also be gathered for resources including, but not limited to, memory usage, total memory load, storage requirements, storage bandwidth requirements, network usage, network bandwidth requirements, application usage, system usage, hardware usage and/or other such resources;
see ¶ 33: file-based database storage systems; ¶ 59: database servers).
19. Regarding claim 3, Dailianas and Borthakur teach/suggest:
“wherein the performance data comprises at least one selected from the group consisting of: CPU usage, memory usage, storage usage, and I/O (input/output) usage”
(Dailianas, ¶ 128 and ¶ 129;
Borthakur, ¶ 21 and ¶ 22, as applied in rejecting claim 2 above).
20. Regarding claim 4, Dailianas and Borthakur teach/suggest:
“wherein the performance data is collected at predetermined time intervals”
(Dailianas, ¶ 128 and ¶ 129;
Borthakur, ¶ 21 and ¶ 22, as applied in rejecting claim 2 above.
See also Dailianas, ¶ 11, (b) selecting to run the workload on the first computational resource provider; (c) determining, after a predetermined period of time has passed since the selection or after the cost for running the workload has increased by at least a predetermined amount, a cost for running the workload on a second computational resource provider).
21. Regarding claim 5, Dailianas and Borthakur teach/suggest:
“wherein the performance data is collected for a predetermined amount of time to determine the workload”
(Dailianas, ¶ 128: monitors storage or network I/O usage by one or more containers, such as by collecting data from one or more of the container system;
¶ 129: periodically estimates both the average storage I/O capacity used and the average available I/O capacity, and updates the respective attributes of the storage I/O objects;
¶ 11, (b) selecting to run the workload on the first computational resource provider; (c) determining, after a predetermined period of time has passed since the selection or after the cost for running the workload has increased by at least a predetermined amount, a cost for running the workload on a second computational resource provider;
Borthakur, ¶ 21: computer system entities may utilize computer system resources including, but not limited to, CPUs, memory, disk I/O, disk storage, application resources, other hardware resources, virtual hardware resources and other such computer system resources;
¶ 22: resource usage may be sampled and/or otherwise periodically monitored. Other resource usage measurements may also be gathered for resources including, but not limited to, memory usage, total memory load, storage requirements, storage bandwidth requirements, network usage, network bandwidth requirements, application usage, system usage, hardware usage and/or other such resources;
¶ 23: resource usage measurements may be recorded over the course of the execution of an entity, application, computer system or workload or may be recorded over a sampling period).
22. Regarding claim 6, Dailianas and Borthakur teach/suggest:
“wherein the performance data is aggregated to determine the workload”
(Dailianas, ¶ 128: The economically based scheduling process described above may be used effectively to de-correlate peaks of competing, bursty I/O flows. …. The aggregate demand average of 1 Gbps consumes only 25% of the HBA capacity;
Borthakur, ¶ 23: The resource usage measurements may be analyzed individually and/or in aggregate to determine whether at least a part of a selected resource, entity, application, computer system or workload may be a good candidate for migration from a customer datacenter environment to a computing resource service provider environment;
¶ 25: metrics may be aggregated or combined such as, for example, by aggregating metrics across multiple related processes that together constitute a workload).
23. Regarding claims 7–12, they are the corresponding computer program product claims reciting similar limitations of commensurate scope as the method of claims 1–6, respectively. Therefore, they are rejected on the same basis as claims 1–6 above.
24. Regarding claims 13–18, they are the corresponding system claims reciting similar limitations of commensurate scope as the method of claims 1–6, respectively. Therefore, they are rejected on the same basis as claims 1–6 above, including the following rationale:
Dailianas teaches/suggests:
“memory circuitry to store program code of a resource analyzer, a resource configuration determiner, and a resource type recommender; and processor circuitry connected to the memory circuitry, wherein: the processor circuitry is to operate [various program modules or codes]”
(¶¶ 225 to 231: Embodiments of the subject matter and the functional operations described in this specification can be implemented in digital electronic circuitry, or in computer
Software …. The processes and logic flows described in this specification can be performed by one or more programmable processors executing one or more computer programs).
Conclusion
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/BENJAMIN C WU/Primary Examiner, Art Unit 2195
October 25, 2025