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 .
This communication is responsive to the amendment filed on 11/11/2025.
Status of claims:
Claims 1, 12 and 20 are amended.
Claims 1-20 are pending for examination.
Response to Arguments
Applicant argued with respected the newly added and amended limitations have been considered in the new ground rejection below.
Claim Rejections - 35 USC § 112
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 1-20 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.
Claim 1, 12 and 20: recite the newly added limitation “calculating a frequency of receiving the homogenized data from each data center”, which the underlined features
render the claim indefinite. Applicant’s specification provides no guidance as how the step of calculating for a frequency of receiving is done. Applicant is required for clarification/correction is required.
- All dependent claims are rejected under the same rational as their based claims as above.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1, 12 and 20:Step 1: Statutory Category
The claims are directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter.
Step 2A, Prong One:
The limitations a “collecting…; calculating…; comparing…; determining…; generating…; generating…”, as drafted, is a process that, under its broadest reasonable interpretation, covers a mental process as a form of evaluation or judgement, but for the recitation of generic computer components. That is nothing in the claim element precludes the steps from practically being performed in a human mind. For example, the limitation “collecting…; calculating…; comparing…; determining…; generating…; generating…”, in the context of the claim encompasses one can manually or mentally with the aid of pen and paper determines the number of students.
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.
Step 2A, Prong Two: Integrated into a Practical Application
This judicial exception is not integrated into a practical application. The claim recites the additional elements “wherein….to receive…”, amount to data gathering steps which is considered to be insignificant extra-solution activity. (See MPEP 2106.05(g).
“process….to output…; transforming…,” represent(s) an extra solution activity because it is a mere nominal or tangential addition to the claim, a mere generic transmission and presenting of collected and analyzed data. (See MPEP 2106.05(g)).
“processor(s), non-transitory computer readable medium, non-transitory storage device” are recited at a high level of generality such that they amount to on more than mere instructions to apply the exception using a generic component. (see MPEP 2106.05(f)).
“machine learning model” is a mere implementation using a computer. It is at best generally linking the abstract idea to a particular field of use or technological environment of machine learning (see MPEP 2106.05(h).
Step 2B: Claim provides an Inventive Concept
The conclusions for the mere implementation using a computer, mere field of use, and using generic computer components (i.e. ML) as a tool are carried over and do not provide significantly more.
“wherein….to receive…”. These are identified as insignificant extra-solution activity above when re-evaluated this element is well-understood, routine, and conventional as evidenced by the court cases in MPEP 2106.05(d)(II), "i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); … OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network);" and thus remains insignificant extra-solution activity that does not provide significantly more.
“process….to output…; transforming…”. This is identified as insignificant extra-solution activity above when re-evaluated this element is well-understood, routine, and conventional as evidenced by the court cases in MPEP 2106.05(d)(II), "iv. Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334; i. … transmitting data over a network, …Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); … OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350,
1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)”.
“processor(s), non-transitory computer readable medium, non-transitory storage device”, amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrate by: relevant court decision: the followings are example of the court decisions demonstrating well-understood, routine and conventional activities, See e.g., MPEP 2106.05(d)(II) and MPEP 2106.05(f)(2): computer readable storage media comprising instructions to implement a method, e.g., see versata Dev. Group, Inc. v SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
The claims as a whole, does not amount to significantly more than the abstract
idea itself. This is because the claims do not affect an improvement to the functioning
of a computer itself; and the claims do not move beyond a general link of the use of an
abstract idea to a particular technological environment.
Accordingly, claims are directed to an abstract idea.
Claim 2 recites the additional element at a high level of generality such that they amount to on more than mere instructions to apply the exception using a generic component. (see MPEP 2106.05(f)).
Claims 3-6, recite the additional limitations. These additional elements do not integrate the integrate the judicial exception into a practical application and does not amount to significantly more.
Claims 7-8, recite the limitations, which are processes that, under its broadest reasonable interpretation, covers a mental process as a form of evaluation or judgement, but for the recitation of generic computer components. There is no additional elements recited so the claims do not provide a practical application and is not considered to be significantly.
Claims 9-10, recite the limitation “determining…”, which is a process that, under its broadest reasonable interpretation, covers a mental process as a form of evaluation or judgement, but for the recitation of generic computer components.
“providing…”. This additional element does not integrate the integrate the judicial exception into a practical application and does not amount to significantly more.
Claim 11, recites the limitation, which is a process that, under its broadest reasonable interpretation, covers a mental process as a form of evaluation or judgement, but for the recitation of generic computer components.
Claims 13-19 recite the same limitations as claims 2-11 above. Therefore, they are rejected under the same rational.
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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Nyerges et al., (US 2016/0234087), hereinafter “Nyerges”, in view of Mritunjai (US 11,652,755), hereinafter “Mritunjai”, and in further view of Patil et al., (US 10,511,545), hereinafter “Patil”.
Claim 1, Nyerges discloses a method for managing various data centers comprising:
- collecting, by one or more processors, heterogeneous telemetry data from a plurality of data centers (par. [0007] and [0008], collecting heterogenous telemetry data);
- transforming, by the one or more processors, the heterogenous telemetry data into homogenized data using a mapping that converts various formats of the heterogenous telemetry data into a homogenized format (par. [0008], transforming the collected telemetry data and par. [0034], generates telemetry data (e.g., “chunks” or fragments of information typically used in multimedia formats) during this exchange. Such telemetry data is monitored by SDCDN 105. For example, SDCDN 105 monitors telemetry data including, … As discussed above, SDCDN 105 represents one or more telemetry frameworks or modules which are preferably incorporated within application servers in content and/or data transfer networks and manages/monitors telemetry data generated by client devices.).
However, Nyerges does not explicitly disclose “monitoring, by the one or more processors, a parameter for assessing data center health across the plurality of data centers using the homogenized data”.
On the other hand, Mritunjai discloses monitoring, by the one or more processors, a parameter for assessing data center health across the plurality of data centers using the homogenized data (col.5, lines 23-33, generating metrics, e.g., average values of dimensions of data, maximum values, minimum values, other statistical measures), wherein the monitoring comprises:
calculating a frequency of receiving the homogenized data from each data
center (col.2, lines 21-39, monitoring service collects monitoring and operational data in the form of logs, metrics; and col. 6 lines 41-55 and col. 7 lines 41-56, determining that a recent (or average) latency of response from the monitoring service meets or exceeds a threshold (e.g., when a moving window average—such as a truncated mean that ignores the top and bottom 1% of values—of the observed latency of operation rises a threshold percentage or exceeds a threshold); col. 9 line 9 to col. 10 lines 20, generating histogram type data by, over a particular time aperture, constructing “buckets” of values where each bucket has an associated range and the value indicates, e.g., a number of data points that fall within the range); which is similar to the Applicant’s specification, par. [0025] and [0037, homogenized data of that log matching data );
comparing the respective frequencies to a threshold frequency range (col.2,
lines 21-39, monitoring service collects monitoring and operational data in the form of logs, metrics, and events, providing users with a unified view of operational health, applications, and services that run in the data centers); and
determining that the homogenized data from each data center is being received within the threshold frequency range based on the comparison (col.2, lines 21-39, monitoring service collects monitoring and operational data in the form of logs, metrics; and col. 6 lines 41-55 and col. 7 lines 41-56, determining that a recent (or average) latency of response from the monitoring service meets or exceeds a threshold (e.g., when a moving window average—such as a truncated mean that ignores the top and bottom 1% of values—of the observed latency of operation rises a threshold percentage or exceeds a threshold); col. 9 line 9 to col. 10 lines 20, generating histogram type data by, over a particular time aperture, constructing “buckets” of values where each bucket has an associated range and the value indicates, e.g., a number of data points that fall within the range);
- generating a metric for each data center based on the parameter (col.5, lines 23-33, generating metrics, e.g., average values of dimensions of data, maximum values, minimum values, other statistical measures).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified the combined system of Nyerges to include the features of Mritunjai in order to improve the functioning of the computing systems, thereby automatically detecting an anomaly using telemetry data.
Neither Nyerges nor Mritunjai discloses “generating, by the one or more processors, a prediction for data center health across the plurality of data centers using a machine learning model based on the respective metrics, wherein the machine learning model is configured to receive the respective metrics and process the respective metrics to output the prediction for data center health”.
Patil discloses generating, by the one or more processors, a prediction for data center health across the plurality of data centers using a machine learning model based on the respective metrics, wherein the machine learning model is configured to receive the respective metrics and process the respective metrics to output the prediction for data center health (col. 11 lines 60-67, generating the prediction including a regression function, or a machine learning model/function, such as a logistic regression-based classification model, a tree-based model; abstract and col.2, lines 7-44, historical telemetry data can be used to generate predictions for various classes of data at various aggregates of a system that implements an online service of a system by determining a prediction error by comparing the values of the aggregated metrics to a prediction, detecting an anomaly based at least in part on the prediction error, and transmitting an alert message of the anomaly to a receiving entity).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of cited references to include the features as disclosed by Patil to improve the functioning of the computing systems that implement the online service, and the online service itself is improved by increasing the reliability of the systems utilized for providing services.
Claim 2, the combination of Nyerges, Mritunjai, and Patil discloses the invention as claimed. In addition, Nyerges discloses displaying, by the one or more processors, the metrics in real-time via a user interface (par. [0047], each application server includes the telemetry framework, which collects telemetry data for corresponding client devices and aggregates, in real-time, the telemetry data using a distribution tree).
Claim 3, the combination of Nyerges, Mritunjai, and Patil discloses the invention as claimed. In addition, Nyerges discloses the heterogenous telemetry data is collected from a plurality of data sources associated with the plurality of data centers (par. [0007]-[0009], heterogeneous telemetry data, and translate telemetry data collected by devices having different operating systems).
Claim 4, the combination of Nyerges, Mritunjai, and Patil discloses the invention as claimed. In addition, Nyerges discloses the heterogenous telemetry data comprises telemetry data in a plurality of data formats (par. [0006]-[0009], each client device generates a different type or format of telemetry data).
Claim 5, the combination of Nyerges, Mritunjai, and Patil discloses the invention as claimed. In addition, Mritunjai discloses the homogenized data comprises telemetry data converted to a data object format comprising the parameters (col.2, lines 27-39, obtain a unified view of operational health, collects monitoring and operational data in the form of logs, metrics, and events, providing users with a unified view of their resources, applications, and services that run in the data centers).
Claim 6, the combination of Nyerges, Mritunjai, and Patil discloses the invention as claimed. In addition, Mritunjai discloses storing, by the one or more processors, the homogenized data in logs segregated by each data center of the plurality of data centers (col.2, lines 27-39, obtain a unified view of operational health, collects monitoring and operational data in the form of logs, metrics, and events, providing users with a unified view of their resources, applications, and services that run in the data centers).
Claim 7, the combination of Nyerges, Mritunjai, and Patil discloses the invention as claimed. In addition, Mritunjai discloses determining, by the one or more processors, that the homogenized data of a log of a data center is being received within the threshold frequency range (col.2, lines 27-39, obtain a unified view of operational health, collects monitoring and operational data in the form of logs, metrics, and events, providing users with a unified view of their resources, applications, and services that run in the data centers).
Claim 8, the combination of Nyerges, Mritunjai, and Patil discloses the invention as claimed. In addition, Nyerges discloses comparing the metrics to one or more configurable thresholds (par. [0007] and [0050], recording a measurement for each tracked variable from a beginning of the log or from a last measurement and comparing a current measurement against the recorded measurement to determine a delta or changed state by performing calculations of changed states from measurements of tracked variables of telemetry data within the particular application server where it resides, wherein each telemetry framework additionally stores the results of such calculations, along with the entire log of telemetry data for variables, at which log points and what variables were measured, and all the measurements, for later comparisons).
Claim 9, the combination of Nyerges, Mritunjai, and Patil discloses the invention as claimed. In addition, Nyerges discloses determining, by the one or more processors, at least one metric of the metrics has exceeded a threshold (abstract, par. [0030]-[0031], determines a change in a value for the telemetry data, and stores the change in the value for the telemetry data keyed to the one or more parameters in a database); and
- providing, by the one or more processors, a notification to a client device in response to the at least one metric exceeding the threshold (par. [0042], automatically collect telemetry data from client devices connected to an application server at specific time intervals and update or request a modification to the telemetry data it collects, wherein a group notification is sent to all or a specific subgroup of devices connected to a corresponding application server in order to change the telemetry data collected).
Claim 10, the combination of Nyerges, Mritunjai, and Patil discloses the invention as claimed. In addition, Nyerges discloses determining, by the one or more processors, at least one metric of the metrics has exceeded a threshold (abstract, par. [0030]-[0031], determines a change in a value for the telemetry data, and stores the change in the value for the telemetry data keyed to the one or more parameters in a database); and
- providing, by the one or more processors, instructions to a computing device associated with a data center of the plurality of data centers to automatically perform a corrective measure in response to the at least one metric exceeding the threshold (par. [0042], automatically collect telemetry data from client devices connected to an application server at specific time intervals and update or request a modification to the telemetry data it collects, wherein a group notification is sent to all or a specific subgroup of devices connected to a corresponding application server in order to change the telemetry data collected).
Claim 11, the combination of Nyerges, Mritunjai, and Patil discloses the invention as claimed. In addition, Patil discloses generating the prediction is further based on historical data of the metrics (abstract and col.2, lines 7-44, historical telemetry data can be used to generate predictions for various classes of data at various aggregates of a system that implements an online service of a system by determining a prediction error by comparing the values of the aggregated metrics to a prediction, detecting an anomaly based at least in part on the prediction error, and transmitting an alert message of the anomaly to a receiving entity).
Claims 12-19, are system claims corresponding the method of claims 1-2 and 4-10. Therefore, claims 12-19 are rejected under the same rationale as claims 1-2 and 4-10 above.
Claim 20, is a non-transitory computer readable medium claim corresponding the method of claim 1. Therefore, claim 20 is rejected under the same rationale as claim 1 above.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Loan T. Nguyen whose telephone number is (571) 270-3103. The examiner can normally be reached on Monday from 10:00 am - 6:00 pm, Thursday-Friday from 10:00 am - 2:00 pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Aleksandr Kerzhner can be reached on (571) 270-1760. The fax phone number for the organization where this application or proceeding is assigned is 571-270-4103. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
5/10/2026
/LOAN T NGUYEN/Examiner, Art Unit 2165
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