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 § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 1,4-10 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Regarding claim 1, the claim recites limitations
“corresponding to a time instance of the predicted abnormal accident”, and “reduces log-query volume and cross-cluster network traffic by restricting log retrieval to a predicted anomaly time window,”.
The originally filed disclosure describes that, when a predicted abnormal accident occurs, the predictor reports a data sequence to the root cause analyzer; the root cause analyzer acquires a feature score and requests a log score; the data processor performs a “log query” for the data collector and a log stream; and the data processor analyzes the returned log information to calculate the log score.(see specification page 3).
Original claims 4 and 5 similarly describe requesting a log score after acquiring the feature score and transmitting a log query to the data collector upon receipt of the log-score request.
However, the originally filed disclosure does not describe the data processor as selecting or retrieving logs corresponding to a particular time instance of the predicted abnormal accident or restricting log retrieval to a predicted anomaly time window. The disclosure also does not describe the disclosed log-query process as reducing log-query volume, reducing cross-cluster network traffic, lowering inter-cluster bandwidth consumption, or otherwise achieving the particular cloud-system performance improvement now recited in claim 1.
Although the originally filed disclosure describes a plurality of clusters, collection of metric and log data, and initiation of a log query after prediction of an abnormal accident, those disclosures do not reasonably convey possession of the presently claimed time window-ed log-retrieval mechanism and its associated effects. A log query initiated in response to an abnormal accident could retrieve an unrestricted log stream, logs covering any time interval, or all available logs. Therefore, restricting retrieval to a predicted anomaly time window and reducing log-query volume and cross-cluster network traffic are not necessarily inherent in the originally disclosed process.
Accordingly, the application as originally filed does not expressly, implicitly, or inherently support the claimed combination of:
querying logs corresponding to a time instance of the predicted abnormal accident;
restricting log retrieval to a predicted anomaly time window; and
therefore reducing log-query volume and cross-cluster network traffic.
Independent claims 8 and 9 recite similar limitations directed to querying logs at a specific time instance corresponding to the predicted abnormal accident and reducing log-query volume and cross-cluster network traffic by restricting log retrieval to a predicted anomaly time window. Claims 8 and 9 are rejected for the same reasons.
Claims 4–7 depend on claim 1 and therefore include the unsupported limitations of claim 1. Claim 10 depends on claim 9 and therefore includes the unsupported limitations of claim 9. Therefore, claims 4–7 and 10 are also rejected under 35 U.S.C. 112(a).
Response to Arguments
Applicant’s arguments, see Remarks, filed 04/16/2026, with respect to the rejections of claims 1,4-10 have been fully considered and are persuasive. The rejections of 2/17/2026 have been withdrawn.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20170123957 A1 - Gupta - automated root cause analysis of layered architecture. Focuses a lot on global timing stuff.
US 20220206886 A1 - Srivastava - root cause analysis of logs.
US 20220334904 A1 - Chesneau - automated incident detection and root cause analysis
US 20230229545 A1 - Yadav - log analysis and retention system
US 20240036963 A1 - Azeez - analyzes multiple types of metrics using machine learning models to detect anomalies.
US 20210026723 A1 - Nadger - Does data source discovery, determines root cause using statistical models. Missing recovery action.
US 20220138072 A1 - Liu - monitors disk arrays and collects extra logs when failures occur.
US 9891971 B1 - Kuhhirte - observes activity of IT operators in remedying root causes and generates/stores runbooks for root causes of error conditions.
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/MICHAEL XU/Examiner, Art Unit 2113
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