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 .
Claims 1-20 are presented for examination.
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, 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.
Claims 1-5, 7-8, 10-15, 17-18, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Iyoob et al. U.S. Patent Application Publication Number 2015/0341240 A1 (hereinafter Iyoob), and further in view of Sharma et al. U.S. Patent Application Publication Number 2022/0035680 A1 (hereinafter Sharma).
As per claims 1, 11, Iyoob discloses a computer-implemented method for optimizing cloud computing configurations based on cloud maturity scores, comprising:
receiving generated (see calculate the readiness index 618, or cloud maturity scores as claimed, based on cost savings, application performance, and network performance on page 15 section [0117]) cloud maturity scores (see readiness index 618, or cloud maturity scores as claimed, for determining readiness to migrate to a target deployment model such as a cloud based network on page 15 section [0117]) related to one or more hyperscaler instances (to be taught by Sharma);
identifying, based on the one or more cloud maturity scores (see readiness index identifies target deployment model on page 15 section [0117]), one or more optimization recommendations (see identifying recommended deployment infrastructure options such as physical hardware, visualized hardware, private IaaS, public IaaS-enterprise, PaaS cloud, and SaaS cloud on page 15 section [0119]) for adjusting cloud configurations of one or more hyperscaler instances (to be taught by Sharma);
implementing the one or more optimization recommendations to adjust the cloud configurations (see selected one of the recommended cloud service provider options and enabling cloud resource procurement from the service providers on page 19 section [0140]); and
generating one or more updated cloud maturity scores (see modifying existing cloud services on page 5 section [0053] by doing cloud readiness assessment for readiness index on page 15 section [0117]).
Iyoob do not disclose expressly the use of hyperscaler instances in cloud computing.
Sharma teaches the use of hyperscaler instances in cloud computing (see hyperscaler instance are benchmarked and stored in HyperScalers benchmark repository on page 7 section [0070]).
Iyoob and Sharma are analogous art because they are from the same field of endeavor, cloud migration recommendation systems. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to use hyperscaler instances in cloud computing. The motivation for doing so would have been to identify and keep track of hyperscaler instances in repositories for management purposes (see page 7 section [0070] in Sharma). Therefore, it would have been obvious to combine Iyoob and Sharma for the benefit of using hyperscaler instances to obtain the invention as specified in claims 1, 11.
As per claims 2, 12, Iyoob and Sharma disclose the method of claim 1, wherein the optimization recommendations are directed to reducing costs associated with the cloud computing configuration (see calculating based on cost TCO and ROI on page 6 section [0056] and see readiness is calculated based on TCO savings on cost on page 15 section [0117] in Iyoob). The motivation to combine is same as above.
As per claims 3, 13, Iyoob and Sharma disclose the method of claim 1, wherein the optimization recommendations are based on a customer profile (see Customer Relationship Management for customer profile on page 17 section [0132] and see customer profile needs such as demand profile and workflow profile to determine the cloud strategy recommendation on page 15 section [0116] in Iyoob). The motivation to combine is same as above.
As per claims 4, 14, Iyoob and Sharma disclose the method of claim 1, further comprising receiving user-selected recommendations and automatically implementing adjustments to the one or both of the hyperscaler instances and cloud configurations (see auto-provisioning of deployment instances on page 14 section [0111] and see auto-scaling and provisioning of cloud services on page 5 section [0052] in Iyoob). The motivation to combine is same as above.
As per claims 5, 15, Iyoob and Sharma disclose the method of claim 1, wherein the optimization recommendations are industry-specific optimization recommendations (see Enterprise Resource Planning, or Industry-specific optimization as claimed, on for optimizing for cloud deployment on page 17 section [0132] in Iyoob). The motivation to combine is same as above.
As per claims 7, 17, Iyoob and Sharma disclose the method of claim 5, wherein industry-specific criteria for optimization comprise at least one of compliance requirements, performance benchmarks, and cost efficiency metrics specific to an industry segment (see cost TCO on page 6 section [0056] and see TCO savings, application performance, and network performance to determine readiness index on page 15 section [0117] in Iyoob). The motivation to combine is same as above.
As per claims 8, 18, Iyoob and Sharma disclose the method of claim 1, further comprising dynamically updating recommendations based on feedback related to the implemented optimization recommendations applied to one or both of the hyperscaler instances and cloud configurations (see recommendations could be changed or replaced with user-selected responses on page 18 section [0133] in Iyoob). The motivation to combine is same as above.
As per claim 10, Iyoob and Sharma disclose the method of claim 1, further comprising displaying the optimization recommendations via a graphical user interface on a client computing device (see recommendation packages in user interface on page 13 section [0104] and see user interface displaying optimization recommendations on Figure 8A in Iyoob). The motivation to combine is same as above.
As per claim 20, Iyoob and Sharma disclose the computing system of claim 11, wherein the one or more hyperscaler instances include one or more of one of (i) a Microsoft Azure instance, (ii) an Amazon Web Services instance, or (iii) a Google Cloud Platform instance (see Amazon Web Service instances on page 5 section [0052] in Iyoob). The motivation to combine is same as above.
Allowable Subject Matter
Claims 6, 9, 16, 19 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALAN S CHOU whose telephone number is (571)272-5779. The examiner can normally be reached Monday-Friday 9:00-5:00 EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chris L Parry can be reached at (571)272-8328. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ALAN S CHOU/Primary Examiner, Art Unit 2451
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