DETAILED ACTION
The following is a Non-Final, First Office Action on the Merits in response to communications filed January 9, 2025. Currently, claims 1–20 are pending.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 7–9 and 17–19 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 7 and 17 recite “key words or phrases” in the element for “adding”. However, claims 1 and 11, from which claims 7 and 17 depend, previously recite “key words or phrases” in a previous step for “adding”. As a result, the scope of claims 7 and 17 is indefinite because it is unclear whether Applicant intends for the recitations of claims 7 and 17 to reference the previous recitations or intends to introduce second, different “key words or phrases”.
For purposes of examination, claims 7 and 17 are interpreted as reciting “adding the search term for the new detector that includes the key words or the phrases that describe the issue”.
In view of the above, claims 7 and 17 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claims 8–9 and 18–19, which depend from claims 7 and 17, inherit the deficiencies described above. As a result, claims 8–9 and 18–19 are similarly rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
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 1–5, 7–15, and 17–20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Specifically, claims 1–5, 7–15, and 17–20 are directed to an abstract idea without additional elements amounting to significantly more than the abstract idea.
With respect to Step 2A Prong One of the framework, claim 1 recites an abstract idea. Claim 1 includes elements for “identifying one or more issues for a customer workload running on a cloud service provider”; “analyze backend telemetry data for the customer workload and generate an insight for the one or more issues observed in the backend telemetry data to troubleshoot the one or more issues”; and “adding a search term for the detector that includes key words or phrases that describe the one or more issues”.
The limitations above recite an abstract idea. More particularly, the elements above recite certain methods of organizing human activity for commercial business relations because the elements describe a process for analyzing customer issues. Further, the elements recite mental processes because the elements embody observations or evaluations that can be practically performed in the mind or by a human using pen and paper. As a result, claim 1 recites an abstract idea under Step 2A Prong One.
Claim 11 includes substantially similar limitations to those included with respect to claim 1. As a result, claim 11 recites an abstract idea under Step 2A Prong One for the same reasons as stated above with respect to claim 1.
Claims 2–5, 7–10, 12–15, and 17–20 further describe the process for analyzing customer issues and further recite certain methods of organizing human activity and/or mental processes for the same reasons as stated above. As a result, claims 2–5, 7–10, 12–15, and 17–20 recite an abstract idea under Step 2A Prong One.
With respect to Step 2A Prong Two of the framework, claim 1 does not include additional elements that integrate the abstract idea into a practical application. Claim 1 includes additional elements that do not recite an abstract idea under Step 2A Prong One. The additional elements include a datastore, using a detector to automatically analyze backend telemetry data, and storing the detector and the search term in a datastore. When considered in view of the claim as a whole, the additional elements do not integrate the abstract idea into a practical application because the additional computer element is a generic computing component that is merely used as a tool to perform the recited abstract idea, and the remaining additional elements do no more than generally link the use of the recited abstract idea to a particular technological environment. As a result, claim 1 does not include any additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two.
As noted above, claim 11 includes substantially similar limitations to those included with respect to claim 1. Although claim 11 further includes a processor, memory, and instructions, the additional elements, when considered in view of the claim as a whole, do not integrate the abstract idea into a practical application because the additional computer elements are generic computing components that are merely used as a tool to perform the recited abstract idea. As a result, claim 11 does not include any additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two.
Claims 5, 7, 15, and 17 include additional elements that do not recite an abstract idea under Step 2A Prong One. The additional elements include running a natural language processing (NLP) search (claims 5 and 15) and an interface and a step for “creating” a new detector (claims 7 and 17). When considered in view of the claims as a whole, the additional elements do not integrate the abstract idea into a practical application because the additional elements do no more than generally link the use of the recited abstract idea to a particular technological environment. As a result, claims 5, 7, 15, and 17 do not include additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two.
Claims 2–4, 8–10, 12–14, and 18–20 do not include any additional elements beyond those included with respect to the claims from which claims 2–4, 8–10, 12–14, and 18–20 depend. As a result, claims 2–4, 8–10, 12–14, and 18–20 do not include any additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two for the same reasons as stated above.
With respect to Step 2B of the framework, claim 1 does not include additional elements amounting to significantly more than the abstract idea. As noted above, claim 1 includes additional elements that do not recite an abstract idea under Step 2A Prong One. The additional elements include a datastore, using a detector to automatically analyze backend telemetry data, and storing the detector and the search term in a datastore. The additional elements do not amount to significantly more than the recited abstract idea because the additional computer element is a generic computing component that is merely used as a tool to perform the recited abstract idea, and the remaining additional elements do no more than generally link the use of the recited abstract idea to a particular technological environment. Further, looking at the additional elements as an ordered combination adds nothing that is not already present when considering the additional elements individually. As a result, claim 1 does not include any additional elements that amount to significantly more than the recited abstract idea under Step 2B.
As noted above, claim 11 includes substantially similar limitations to those included with respect to claim 1. Although claim 11 further includes a processor, memory, and instructions, the additional elements do not amount to significantly more than the recited abstract idea because the additional computer elements are generic computing components that are merely used as a tool to perform the recited abstract idea. As a result, claim 11 does not include any additional elements that amount to significantly more than the recited abstract idea under Step 2B.
Claims 5, 7, 15, and 17 include additional elements that do not recite an abstract idea under Step 2A Prong One. The additional elements include running a natural language processing (NLP) search (claims 5 and 15) and an interface and a step for “creating” a new detector (claims 7 and 17). The additional elements do not amount to significantly more than the recited abstract idea because the additional elements do no more than generally link the use of the recited abstract idea to a particular technological environment. Further, looking at the additional elements as an ordered combination adds nothing that is not already present when considering the additional elements individually. As a result, claims 5, 7, 15, and 17 do not include additional elements that amount to significantly more than the recited abstract idea under Step 2B.
Claims 2–4, 8–10, 12–14, and 18–20 do not include any additional elements beyond those included with respect to the claims from which claims 2–4, 8–10, 12–14, and 18–20 depend. As a result, claims 2–4, 8–10, 12–14, and 18–20 do not include any additional elements that amount to significantly more than the recited abstract idea under Step 2B for the same reasons as stated above.
Therefore, the claims are directed to an abstract idea without additional elements amounting to significantly more than the abstract idea. Accordingly, claims 1–5, 7–15, and 17–20 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 102(a)(1)
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1–3 and 11–13 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by S NANAL et al. (U.S. 2020/0180148).
Claims 1 and 11: S NANAL discloses a method, comprising:
identifying one or more issues for a customer workload running on a cloud service provider (See paragraphs 21–22, in view of paragraph 44, wherein customer issues are identified with respect to cloud-hosted applications);
using a detector to automatically analyze backend telemetry data for the customer workload and generate an insight for the one or more issues observed in the backend telemetry data, wherein the detector is used to troubleshoot the one or more issues (See paragraphs 29–30, in view of paragraphs 23–24, wherein extracted telemetry data is analyzed to identify and deploy a troubleshooting solution; see also paragraphs 21–22);
adding a search term for the detector that includes key words or phrases that describe the one or more issues (See paragraphs 28–30, wherein the RPA system employs NLP to “select particular keywords indicative of the nature of the error”, wherein knowledge base includes feature keywords indicative of the issues, and wherein the knowledge base is updated based on analysis of executed corrective actions; see also paragraphs 31–32, wherein new solutions are recorded within the knowledge base); and
storing the detector and the search term in a datastore (See paragraphs 30–32, wherein updates to the RPA system, including new terms, are recorded within the knowledge base).
With respect to claim 11, S NANAL discloses a processor; memory in electronic communication with the processor; and instructions stored in the memory, the instructions being executable (See FIG. 9 and paragraph 54).
Claims 2 and 12: S NANAL discloses the method of claim 1, wherein the insight provides a recommended action to address the one or more issues (See paragraph 29, wherein the RPA system identifies a solution).
Claims 3 and 13: S NANAL discloses the method of claim 1, wherein the insight provides interactive visuals and contextual information that provide a description summarizing the backend telemetry data explaining why the one or more issues are occurring in the customer workload (See paragraphs 51–52, wherein the RPA system displays summaries for issues and actions on a dashboard).
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 4–10 and 14–20 are rejected under 35 U.S.C. 103 as being unpatentable over S NANAL et al. (U.S. 2020/0180148) in view of Gross et al. (U.S. 2021/0263828).
Claims 4 and 14: As disclosed above, S NANAL discloses the elements of claim 1.
S NANAL discloses the method of claim 1, further comprising: receiving a problem from a customer for the customer workload (See paragraphs 21–22, in view of paragraph 44, wherein customer issues are identified with respect to cloud-hosted applications); and
receiving the insight from the detector based on analysis of the backend telemetry data for the customer workload, wherein the insight provides a recommended action to address the one or more issues (See paragraphs 29–30, in view of paragraphs 23–24, wherein extracted telemetry data is analyzed to identify and deploy a troubleshooting solution; see also paragraphs 21–22). S NANAL does not expressly disclose the remaining claim elements.
Gross discloses receiving a problem statement from a customer (See paragraph 49, wherein a customer use case is provided as an inquiry);
identifying a subset of detectors from the datastore to use with the problem statement (See paragraphs 47–49, wherein a model is selected from a library of models to address the customer use case); and
receiving the insight from the subset of detectors based on analysis of the backend telemetry data, wherein the insight provides a recommended action to address the one or more issues (See paragraphs 47–49, wherein the selected model recommends configuration adjustments in response to the identified problem).
S NANAL discloses a system directed to using an analytic RPA system to implement operational solutions. Gross discloses a system directed to recommending and implementing data center configuration solutions by analyzing operational data. Each reference discloses a system directed to implementing solutions based on operational analysis. The technique of using a subset of detectors to address a problem statement is applicable to the system of S NANAL as they each share characteristics and capabilities, namely, they are directed to implementing solutions based on operational analysis.
One of ordinary skill in the art would have recognized that applying the known technique of Gross would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Gross to the teachings of S NANAL would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate operational analysis and solution implementation into similar systems. Further, applying a subset of detectors to address a problem statement to S NANAL would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow more detailed analysis and more reliable results.
Claims 5 and 15: S NANAL discloses the method of claim 4, wherein identifying the subset of detectors further comprises:
running a natural language processing (NLP) search on the problem (See paragraph 28, wherein the data processor applies NLP on the received error messages);
identifying the one or more issues for the customer workload based on the NLP search (See paragraphs 28–30, wherein the RPA system employs NLP to “select particular keywords indicative of the nature of the error”, wherein knowledge base includes feature keywords indicative of the issues, and wherein the knowledge base is updated based on analysis of executed corrective actions; see also paragraphs 31–32, wherein new solutions are recorded within the knowledge base); and
comparing the one or more issues to the search term of the detector (See paragraphs 28–30, wherein the RPA system employs NLP to “select particular keywords indicative of the nature of the error”, wherein knowledge base includes feature keywords indicative of the issues, and wherein the knowledge base is updated based on analysis of executed corrective actions; see also paragraphs 31–32, wherein new solutions are recorded within the knowledge base). S NANAL does not expressly disclose the remaining claim elements.
Gross discloses a problem statement (See paragraph 49, wherein a customer use case is provided as an inquiry); and
adding the detector to the subset of detectors when a match occurs between the one or more issues and the term for the detector (See FIG. 7 and paragraphs 34 and 52, wherein a new model is selected upon reconfiguration of the data center based on new matching characteristics; see also FIG. 6 and paragraph 47, wherein detector models are added to the library in an ongoing process).
One of ordinary skill in the art would have recognized that applying the known technique of Gross would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 4.
Claims 6 and 16: S NANAL discloses the method of claim 4, further comprising: sharing the insight with the customer (See paragraphs 51–52, wherein the RPA system displays summaries for issues and actions on a dashboard); and
performing the recommended action provided by the detector to fix the problem for the customer workload (See paragraphs 29–30, in view of paragraphs 23–24, wherein extracted telemetry data is analyzed to identify and deploy a troubleshooting solution; see also paragraphs 21–22). S NANAL does not expressly disclose the remaining claim elements.
Gross discloses performing the recommended action provided by the subset of detectors to fix the problem statement for the customer workload (See paragraphs 47–49, in view of FIG. 7, wherein the recommended configuration is implemented in response to the customer case inquiry).
One of ordinary skill in the art would have recognized that applying the known technique of Gross would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 4.
Claims 7 and 17: S NANAL discloses the method of claim 1, further comprising: creating, using an interactive interface, a new detector bot for an issue in the customer workload (See paragraphs 31–32, wherein a user creates a new solution, thereby training a new bot for automated resolution of the customer problem);
adding the search term for the new detector bot that includes key words or phrases that describe the issue (See paragraphs 30–32, in view of paragraphs 28–29, wherein issues and solutions are stored in the knowledge base with respect to associated keywords, and wherein new solutions/bots implicitly include keyword associations); and
storing the new detector bot and the search term in the datastore (See paragraphs 30–32, in view of paragraphs 28–29, wherein issues and solutions are stored in the knowledge base with respect to associated keywords, and wherein new solutions/bots implicitly include keyword associations). S NANAL does not expressly disclose the remaining claim elements.
Gross discloses creating a new detector (See FIG. 6 and paragraph 47, wherein detector models are added to the library in an ongoing process).
One of ordinary skill in the art would have recognized that applying the known technique of Gross would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 4.
Claims 8 and 18: S NANAL discloses the method of claim 7, wherein creating the new detector further comprises: identifying the backend telemetry data necessary to troubleshoot the issue in the customer workload (See paragraph 35, wherein the data parser analyzing the unstructured data to generate the necessary data in structured form); and
associating the backend telemetry data with the new detector bot in the datastore (See paragraphs 30–32, in view of paragraphs 18 and 27–29, wherein issues and solutions are stored in the knowledge base with respect to associated features, and wherein new solutions/bots implicitly include feature associations). S NANAL does not expressly disclose the remaining claim elements.
Gross discloses a new detector (See FIG. 6 and paragraph 47, wherein new detector models are generated and trained).
One of ordinary skill in the art would have recognized that applying the known technique of Gross would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 4.
Claims 9 and 19: S NANAL discloses the method of claim 7, wherein the new detector bot is a custom detector bot tailored to the customer workload (See paragraphs 31–32, wherein new detector bots are customized for new customer issues). S NANAL does not expressly disclose the remaining claim elements.
Gross discloses a new detector (See FIG. 6 and paragraph 47, wherein new detector models are generated and trained).
One of ordinary skill in the art would have recognized that applying the known technique of Gross would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 4.
Claims 10 and 20: S NANAL discloses the method of claim 1, further comprising: placing the detector bot into a category in response to the key words or the phrases in the search term for the detector matching the category (See paragraph 30, wherein solution bots are mapped according to issues categories). S NANAL does not expressly disclose the remaining claim elements.
Gross discloses placing the detector into a category (See FIG. 6, wherein models are indexed using row and column categories).
One of ordinary skill in the art would have recognized that applying the known technique of Gross would have yielded predictable results and resulted in an improved system for the same reasons as stated above with respect to claim 4.
Conclusion
The following prior art is made of record and not relied upon but is considered pertinent to Applicant's disclosure:
Antonio et al. (U.S. 2019/0303232) discloses a system directed to automatically detecting and resolving issues using bot deployment.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM S BROCKINGTON III whose telephone number is (571)270-3400. The examiner can normally be reached M-F, 8am-5pm, EST.
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/WILLIAM S BROCKINGTON III/ Primary Examiner, Art Unit 3623