DETAILED ACTION
This action is in response to an amendment filed on February 5, 2026 for the application of Bramble for a “Techniques to provide self-healing data pipelines in a cloud computing environment” filed on November 9, 2023, which is a continuation of U.S. Application No. 18113873, filed on February 24, 2023, now U.S. Patent No. 11815994, which is a continuation of U.S. Application No. 17331846, filed on May 27, 2021, now U.S. Patent No. 11625294. 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, 3, 5-9, 11, 13-17, 19-20, 22, and 24-25 are pending in the application.
Claims 1, 9, 17, and 25 have been amended.
Claims 1, 3, 5-9, 11, 13-17, 19-20, 22, and 24-25 are rejected under 35 USC § 103.
Claims 1, 3, 5-9, 11, 13-17, 19-20, 22, and 24-25 are rejected on the ground of nonstatutory double patenting.
Double Patenting
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 conflicting claims 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); 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 nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) 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 www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1, 3, 5-9, 11, 13-17, 19-20, 22, and 24-25 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 11815994. Although the claims at issue are not identical, they are not patentably distinct from each other because claims 1-20 of U.S. Patent No. 11815994 contain(s) every element of claim(s) 1, 3, 5-9, 11, 13-17, 19-20, 22, and 24-25 of the instant application and as such anticipate(s) claim(s) 1, 3, 5-9, 11, 13-17, 19-20, 22, and 24-25 of the instant application.
Claims 1, 3, 5-9, 11, 13-17, 19-20, 22, and 24-25 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 11625294. Although the claims at issue are not identical, they are not patentably distinct from each other because claims 1-20 of U.S. Patent No. 11625294 contain(s) every element of claim(s) 1, 3, 5-9, 11, 13-17, 19-20, 22, and 24-25 of the instant application and as such anticipate(s) claim(s) 1, 3, 5-9, 11, 13-17, 19-20, 22, and 24-25 of the instant application.
Claim Rejections - 35 USC § 101
In view of the applicant’s amendments, the previous rejection of claim has been withdrawn.
Claim Rejections - 35 USC § 103
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.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 6, 17 and 20, 22, and 25 are rejected under 35 U.S.C. 103 as being unpatentable over Dreyfuss et al. (U.S. PGPUB 20200183788) in view of Dukhovny et al. (U.S. Patent No. 11210160) and in further view of Brown et al. (U.S. PGPUB 20070118908).
As per claims 1 and 17, Dreyfuss discloses a computer system/method/a non-transitory computer readable medium ([0091]), comprising: one or more processors; and memory comprising instructions that when executed by the one or more processors, cause the one or more processors ([0090]) to:
detect a failure event in a data pipeline ([0062], “detecting failure(s) of a job, such as a data processing pipeline or process”);
responsive to detecting the first failure event, determine a plurality of different immediate remedial actions associated with the first failure event (Fig. 5B, elements 518 and 522) and ([0047] and [0069]-[0072]); and one fatal remedial action associated with the first failure event ([0048], “an instruction to migrate machines before re-executing; an exit code identifying the processor as being too busy to execute the component 204 may be associated with an instruction to retry at a later time, migrate to a different processor”);
Dreyfuss fails to explicitly disclose successively invoke each of the plurality of different immediate remedial actions.
Dukhovny of analogous art teaches:
after determining the plurality of different immediate remedial actions and the one fatal remedial action (col. 12, lines 12-17, “the remediation actions are presented according to score with the highest scoring remediation action presented at the top of a list. In various embodiments, additional information is also presented with each remediation action (e.g., probability of success, frequency of use for similar alerts, and/or estimated time to complete the remediation action).”), successively invoke each of the plurality of different immediate remedial actions in an attempt to resolve the first failure event until the first failure event is resolved or all of the plurality of different immediate remedial actions have been invoked (col. 6, lines 63-64, “attempting remediation actions successively in a specified order until remediation is successful”); and
when none of the plurality of different immediate remedial actions resolved the first failure event, invoke the one fatal remedial action in an attempt to resolve the first failure event (col. 10, line 52 through col. 11, line 35) and (Figs. 4-5).
All of the claimed elements were known in Dreyfuss and Dukhovny and could have been combined by known methods with no change in their respective functions. It therefore would have been obvious to a person of ordinary skill in the art before the time of effective filing language to combine their failure recovery methods. One would be motivated to make this combination for the purpose of providing an improved failure recovery (Dukhovny, col. 2, lines 21-33).
Dreyfuss in view of Dukhovny fails to explicitly disclose cycling available subnets.
Brown of analogous art teaches wherein actions includes cycling available subnets ([0052], “This process cycles until all addresses in the subnet have been considered.”).
All of the claimed elements were known in Dreyfuss and Brown and could have been combined by known methods with no change in their respective functions. It therefore would have been obvious to a person of ordinary skill in the art before the time of effective filing language to combine their methods. One would be motivated to make this combination for the purpose of providing an improved corrective actions (Brown, [0053]).
As per claim 6, Dreyfuss discloses the instructions further cause the one or more processors to determine the first of the plurality of different immediate remedial actions based a resource cost associated therewith ([0074], “For example, the re-execution instructions (or a default set of re-execution instructions) may migrate execution of the second component to a different machine upon re-execution, if a different machine is available, the execution management component may wait to cause the second component to re-execute until a temperature and/or memory/processor usage declines below a threshold, etc.”) and ([0076], “For example, this may comprise providing output(s) to the second component from upstream components and/or sequencing execution of the second component relative to other component(s) (e.g., to prevent resource overload”).
As per claims 22 and 25, Dreyfuss discloses the one fatal remedial action includes transferring processing of the data pipeline from a first location to a second location or contacting a system administrator ([0047]-[0048]).
Claims 3, 5, 7-8, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Dreyfuss et al. (U.S. PGPUB 20200183788) in view of Dukhovny et al. (U.S. Patent No. 11210160) and Brown et al. (U.S. PGPUB 20070118908) and in further view of Madawat et al. (U.S. PGPUB 20210342214).
As per claims 3 and 19, Dreyfuss fails to explicitly disclose a table comprising mappings of failure events to remedial actions.
Madawat of analogous art teaches a data store storing a table (Fig. 4, element 402) comprising mappings of failure events to remedial actions ([0052], “Knowledgebase 308 is a repository containing identification of previously failed workflow actions, corrective actions (e.g., fixes) for failed actions that were provided by a disaster recovery administrator, and artificial intelligence-generated corrective action recommendations with assigned weightage values corresponding to failed actions. In this example, knowledgebase 308 includes action library 328, correlation mapping 330, and weightage store 332”), wherein each of the remedial actions is classified into either an immediate action or a fatal action ([0076], “corrective actions 602 may include any number and type of corrective actions”).
All of the claimed elements were known in Dreyfuss and Madawat and could have been combined by known methods with no change in their respective functions. It therefore would have been obvious to a person of ordinary skill in the art before the time of effective filing language to combine their failure recovery methods. One would be motivated to make this combination for the purpose of providing a quick failure recovery (Madawat, [0003]-[0004]).
As per claims 5 and 20, Madawat discloses the instructions further cause the one or more processors to perform a lookup in the table to determine a first of the plurality of different immediate remedial actions to invoke based on the mappings ([0057], “Disaster recovery workflow 404 includes actions A1, A2, . . . An”) between the failure events and the remedial actions ([0052], “Knowledgebase 308 is a repository containing identification of previously failed workflow actions, corrective actions (e.g., fixes) for failed actions that were provided by a disaster recovery administrator, and artificial intelligence-generated corrective action recommendations with assigned weightage values corresponding to failed actions. In this example, knowledgebase 308 includes action library 328, correlation mapping 330, and weightage store 332”).
As per claim 7, Madawat discloses the instructions further cause the one or more processors to: train a model with historical data comprising a plurality of historical failure events and a plurality of historical remedial actions ([0053], “Cognitive engine 310 is an artificial intelligence-based component that utilizes, for example, machine learning, natural language processing, and the like to learn different workflow action failures and how to correct them”); and utilize the model to generate the mappings between the failure events and the remedial actions ([0053]-[0056], “Cognitive engine 310 is an artificial intelligence-based component that utilizes, for example, machine learning, natural language processing, and the like to learn different workflow action failures and how to correct them. In this example, cognitive engine 310 includes correlation engine 334 and weightage engine 336. Correlation engine 334 generates and updates correlation mapping 330 by identifying and correlating potential corrective actions to failed actions using information retrieved by data collector 304 and information stored in knowledgebase 308.”).
As per claim 8, Madawat discloses the instructions further cause the one or more processors to: update the model with result data associated with the plurality of different immediate remedial actions and the one fatal remedial action ([0057], “Disaster recovery workflow 404 includes actions A1, A2, . . . An”) and logged in data log ([0058]-[0061]); and periodically update the mappings between the failure events and the remedial actions based on the model being updated ([0053]-[0056], “Cognitive engine 310 is an artificial intelligence-based component that utilizes, for example, machine learning, natural language processing, and the like to learn different workflow action failures and how to correct them. In this example, cognitive engine 310 includes correlation engine 334 and weightage engine 336. Correlation engine 334 generates and updates correlation mapping 330 by identifying and correlating potential corrective actions to failed actions using information retrieved by data collector 304 and information stored in knowledgebase 308.”).
Claims 9, 14, and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Dreyfuss et al. (U.S. PGPUB 20200183788) in view of Dukhovny et al. (U.S. Patent No. 11210160) and in further view of McArdle (U.S. PGPUB 20050256858).
As per claim 9, Dreyfuss discloses a computer-implemented method, comprising:
detecting a failure event in a data pipeline ([0062], “detecting failure(s) of a job, such as a data processing pipeline or process”);
responsive to detecting the first failure event, determining a plurality of different immediate remedial actions associated with the first failure event (Fig. 5B, elements 518 and 522) and ([0047] and [0069]-[0072]); and one fatal remedial action associated with the first failure event ([0048], “an instruction to migrate machines before re-executing; an exit code identifying the processor as being too busy to execute the component 204 may be associated with an instruction to retry at a later time, migrate to a different processor”);
Dreyfuss fails to explicitly disclose successively invoke each of the plurality of different immediate remedial actions.
Dukhovny of analogous art teaches:
after determining the plurality of different immediate remedial actions and the one fatal remedial action (col. 12, lines 12-17, “the remediation actions are presented according to score with the highest scoring remediation action presented at the top of a list. In various embodiments, additional information is also presented with each remediation action (e.g., probability of success, frequency of use for similar alerts, and/or estimated time to complete the remediation action).”), successively invoking each of the plurality of different immediate remedial actions in an attempt to resolve the first failure event until the first failure event is resolved or all of the plurality of different immediate remedial actions have been invoked (col. 6, lines 63-64, “attempting remediation actions successively in a specified order until remediation is successful”); and
when none of the plurality of different immediate remedial actions resolved the first failure event, invoking the one fatal remedial action in an attempt to resolve the first failure event (col. 10, line 52 through col. 11, line 35) and (Figs. 4-5).
All of the claimed elements were known in Dreyfuss and Dukhovny and could have been combined by known methods with no change in their respective functions. It therefore would have been obvious to a person of ordinary skill in the art before the time of effective filing language to combine their failure recovery methods. One would be motivated to make this combination for the purpose of providing an improved failure recovery (Dukhovny, col. 2, lines 21-33).
Dreyfuss in view of Dukhovny fails to explicitly disclose extracting failing data from a dataset and resubmitting the dataset without the failing data.
McArdle of analogous art teaches wherein the plurality of different immediate remedial actions includes extracting failing data from a dataset and resubmitting the dataset without the failing data ([0059], “deleting "mytable" and thereby removing or correcting for the error condition. Then, when command line 580 is re-executed”).
All of the claimed elements were known in Foster and McArdle and could have been combined by known methods with no change in their respective functions. It therefore would have been obvious to a person of ordinary skill in the art before the time of effective filing language to combine their methods. One would be motivated to make this combination for the purpose of providing an improved error recovery (McArdle, [0009]).
As per claim 14, Dreyfuss discloses the instructions further cause the one or more processors to determine the first of the plurality of different immediate remedial actions based a resource cost associated therewith ([0074], “For example, the re-execution instructions (or a default set of re-execution instructions) may migrate execution of the second component to a different machine upon re-execution, if a different machine is available, the execution management component may wait to cause the second component to re-execute until a temperature and/or memory/processor usage declines below a threshold, etc.”) and ([0076], “For example, this may comprise providing output(s) to the second component from upstream components and/or sequencing execution of the second component relative to other component(s) (e.g., to prevent resource overload”).
As per claim 24, Dreyfuss discloses the one fatal remedial action includes transferring processing of the data pipeline from a first location to a second location or contacting a system administrator ([0047]-[0048]).
Claims 11, 13, and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Dreyfuss et al. (U.S. PGPUB 20200183788) in view of Dukhovny et al. (U.S. Patent No. 11210160) and McArdle (U.S. PGPUB 20050256858) and in further view of Madawat et al. (U.S. PGPUB 20210342214).
As per claim 11, Dreyfuss fails to explicitly disclose a table comprising mappings of failure events to remedial actions.
Madawat of analogous art teaches a data store storing a table (Fig. 4, element 402) comprising mappings of failure events to remedial actions ([0052], “Knowledgebase 308 is a repository containing identification of previously failed workflow actions, corrective actions (e.g., fixes) for failed actions that were provided by a disaster recovery administrator, and artificial intelligence-generated corrective action recommendations with assigned weightage values corresponding to failed actions. In this example, knowledgebase 308 includes action library 328, correlation mapping 330, and weightage store 332”), wherein each of the remedial actions is classified into either an immediate action or a fatal action ([0076], “corrective actions 602 may include any number and type of corrective actions”).
All of the claimed elements were known in Dreyfuss and Madawat and could have been combined by known methods with no change in their respective functions. It therefore would have been obvious to a person of ordinary skill in the art before the time of effective filing language to combine their failure recovery methods. One would be motivated to make this combination for the purpose of providing a quick failure recovery (Madawat, [0003]-[0004]).
As per claim 13, Madawat discloses the instructions further cause the one or more processors to perform a lookup in the table to determine a first of the plurality of different immediate remedial actions to invoke based on the mappings ([0057], “Disaster recovery workflow 404 includes actions A1, A2, . . . An”) between the failure events and the remedial actions ([0052], “Knowledgebase 308 is a repository containing identification of previously failed workflow actions, corrective actions (e.g., fixes) for failed actions that were provided by a disaster recovery administrator, and artificial intelligence-generated corrective action recommendations with assigned weightage values corresponding to failed actions. In this example, knowledgebase 308 includes action library 328, correlation mapping 330, and weightage store 332”).
As per claim 15, Madawat discloses the instructions further cause the one or more processors to: train a model with historical data comprising a plurality of historical failure events and a plurality of historical remedial actions ([0053], “Cognitive engine 310 is an artificial intelligence-based component that utilizes, for example, machine learning, natural language processing, and the like to learn different workflow action failures and how to correct them”); and utilize the model to generate the mappings between the failure events and the remedial actions ([0053]-[0056], “Cognitive engine 310 is an artificial intelligence-based component that utilizes, for example, machine learning, natural language processing, and the like to learn different workflow action failures and how to correct them. In this example, cognitive engine 310 includes correlation engine 334 and weightage engine 336. Correlation engine 334 generates and updates correlation mapping 330 by identifying and correlating potential corrective actions to failed actions using information retrieved by data collector 304 and information stored in knowledgebase 308.”).
As per claim 16, Madawat discloses the instructions further cause the one or more processors to: update the model with result data associated with the plurality of different immediate remedial actions and the one fatal remedial action ([0057], “Disaster recovery workflow 404 includes actions A1, A2, . . . An”) and logged in data log ([0058]-[0061]); and periodically update the mappings between the failure events and the remedial actions based on the model being updated ([0053]-[0056], “Cognitive engine 310 is an artificial intelligence-based component that utilizes, for example, machine learning, natural language processing, and the like to learn different workflow action failures and how to correct them. In this example, cognitive engine 310 includes correlation engine 334 and weightage engine 336. Correlation engine 334 generates and updates correlation mapping 330 by identifying and correlating potential corrective actions to failed actions using information retrieved by data collector 304 and information stored in knowledgebase 308.”).
Claims 1, 3, 5-6, 17, 19-20, 22, and 25 are rejected under 35 U.S.C. 103 as being unpatentable over Foster (U.S. PGPUB 20160026518) in view of Dukhovny et al. (U.S. Patent No. 11210160) and in further view of Brown et al. (U.S. PGPUB 20070118908).
As per claims 1 and 17, Foster discloses a computer system/method/a non-transitory computer readable medium, comprising: one or more processors; and memory comprising instructions that when executed by the one or more processors ([0037]), cause the one or more processors to:
detect a first failure event in a data pipeline ([0025], “an enclosure 110 may be experiencing some type of error condition”);
responsive to detecting the first failure event, determine a plurality of different immediate remedial actions associated with the first failure event ([0044], “The recovery action may first attempt to recover by rebooting the enclosure and all of the components therein.” and “The next recovery may be to install the latest version of the firmware. Again, the latest version may be retrieved from the firmware repository.”); and one fatal remedial action associated with the first failure event ([0044] and [0046]);
Foster fails to explicitly disclose successively invoke each of the plurality of different immediate remedial actions.
Dukhovny of analogous art teaches:
after determining the plurality of different immediate remedial actions and the one fatal remedial action (col. 12, lines 12-17, “the remediation actions are presented according to score with the highest scoring remediation action presented at the top of a list. In various embodiments, additional information is also presented with each remediation action (e.g., probability of success, frequency of use for similar alerts, and/or estimated time to complete the remediation action).”), successively invoke each of the plurality of different immediate remedial actions in an attempt to resolve the first failure event until the first failure event is resolved or all of the plurality of different immediate remedial actions have been invoked (col. 6, lines 63-64, “attempting remediation actions successively in a specified order until remediation is successful”); and
when none of the plurality of different immediate remedial actions resolved the first failure event, invoke the one fatal remedial action in an attempt to resolve the first failure event (col. 10, line 52 through col. 11, line 35) and (Figs. 4-5).
All of the claimed elements were known in Foster and Dukhovny and could have been combined by known methods with no change in their respective functions. It therefore would have been obvious to a person of ordinary skill in the art before the time of effective filing language to combine their failure recovery methods. One would be motivated to make this combination for the purpose of providing an improved failure recovery (Dukhovny, col. 2, lines 21-33).
Foster in view of Dukhovny fails to explicitly disclose cycling available subnets.
Brown of analogous art teaches wherein actions includes cycling available subnets ([0052], “This process cycles until all addresses in the subnet have been considered.”).
All of the claimed elements were known in Foster and Brown and could have been combined by known methods with no change in their respective functions. It therefore would have been obvious to a person of ordinary skill in the art before the time of effective filing language to combine their methods. One would be motivated to make this combination for the purpose of providing an improved corrective actions (Brown, [0053]).
As per claims 3, 5, and 19-20, please refer to ([0022]-[0030], “recovery program repository”).
As per claim 6, please refer to ([0042]-[0045]).
As per claims 22 and 25, please refer to ([0044] and [0046]).
Claims 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Foster (U.S. PGPUB 20160026518) in view of Dukhovny et al. (U.S. Patent No. 11210160) and Brown et al. (U.S. PGPUB 20070118908) and in further view of Madawat et al. (U.S. PGPUB 20210342214).
As per claims 7-8, please refer to (Madawat [0053]-[0056], “Cognitive engine 310 is an artificial intelligence-based component that utilizes, for example, machine learning, natural language processing, and the like to learn different workflow action failures and how to correct them. In this example, cognitive engine 310 includes correlation engine 334 and weightage engine 336. Correlation engine 334 generates and updates correlation mapping 330 by identifying and correlating potential corrective actions to failed actions using information retrieved by data collector 304 and information stored in knowledgebase 308.”).
All of the claimed elements were known in Foster and Madawat and could have been combined by known methods with no change in their respective functions. It therefore would have been obvious to a person of ordinary skill in the art before the time of effective filing language to combine their failure recovery methods. One would be motivated to make this combination for the purpose of providing a quick failure recovery (Madawat, [0003]-[0004]).
Claims 9, 11, 13-14, and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Foster (U.S. PGPUB 20160026518) in view of Dukhovny et al. (U.S. Patent No. 11210160) and in further view of McArdle (U.S. PGPUB 20050256858).
As per claim 9, Foster discloses a computer-implemented method, comprising:
detecting a first failure event in a data pipeline ([0025], “an enclosure 110 may be experiencing some type of error condition”);
responsive to detecting the first failure event, determining a plurality of different immediate remedial actions associated with the first failure event ([0044], “The recovery action may first attempt to recover by rebooting the enclosure and all of the components therein.” and “The next recovery may be to install the latest version of the firmware. Again, the latest version may be retrieved from the firmware repository.”); and one fatal remedial action associated with the first failure event ([0044] and [0046]);
Foster fails to explicitly disclose successively invoke each of the plurality of different immediate remedial actions.
Dukhovny of analogous art teaches:
after determining the plurality of different immediate remedial actions and the one fatal remedial action (col. 12, lines 12-17, “the remediation actions are presented according to score with the highest scoring remediation action presented at the top of a list. In various embodiments, additional information is also presented with each remediation action (e.g., probability of success, frequency of use for similar alerts, and/or estimated time to complete the remediation action).”), successively invoking each of the plurality of different immediate remedial actions in an attempt to resolve the first failure event until the first failure event is resolved or all of the plurality of different immediate remedial actions have been invoked (col. 6, lines 63-64, “attempting remediation actions successively in a specified order until remediation is successful”); and
when none of the plurality of different immediate remedial actions resolved the first failure event, invoking the one fatal remedial action in an attempt to resolve the first failure event (col. 10, line 52 through col. 11, line 35) and (Figs. 4-5).
All of the claimed elements were known in Foster and Dukhovny and could have been combined by known methods with no change in their respective functions. It therefore would have been obvious to a person of ordinary skill in the art before the time of effective filing language to combine their failure recovery methods. One would be motivated to make this combination for the purpose of providing an improved failure recovery (Dukhovny, col. 2, lines 21-33).
Foster in view of Dukhovny fails to explicitly disclose extracting failing data from a dataset and resubmitting the dataset without the failing data.
McArdle of analogous art teaches wherein the plurality of different immediate remedial actions includes extracting failing data from a dataset and resubmitting the dataset without the failing data ([0059], “deleting "mytable" and thereby removing or correcting for the error condition. Then, when command line 580 is re-executed”).
All of the claimed elements were known in Foster and McArdle and could have been combined by known methods with no change in their respective functions. It therefore would have been obvious to a person of ordinary skill in the art before the time of effective filing language to combine their methods. One would be motivated to make this combination for the purpose of providing an improved error recovery (McArdle, [0009]).
As per claims 11 and 13, please refer to ([0022]-[0030], “recovery program repository”).
As per claim 14, please refer to ([0042]-[0045]).
As per claim 24, please refer to ([0044] and [0046]).
Claims 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Foster (U.S. PGPUB 20160026518) in view of Dukhovny et al. (U.S. Patent No. 11210160) and McArdle (U.S. PGPUB 20050256858) and in further view of Madawat et al. (U.S. PGPUB 20210342214).
As per claims 15-16, please refer to (Madawat [0053]-[0056], “Cognitive engine 310 is an artificial intelligence-based component that utilizes, for example, machine learning, natural language processing, and the like to learn different workflow action failures and how to correct them. In this example, cognitive engine 310 includes correlation engine 334 and weightage engine 336. Correlation engine 334 generates and updates correlation mapping 330 by identifying and correlating potential corrective actions to failed actions using information retrieved by data collector 304 and information stored in knowledgebase 308.”).
All of the claimed elements were known in Foster and Madawat and could have been combined by known methods with no change in their respective functions. It therefore would have been obvious to a person of ordinary skill in the art before the time of effective filing language to combine their failure recovery methods. One would be motivated to make this combination for the purpose of providing a quick failure recovery (Madawat, [0003]-[0004]).
Response to Arguments
Applicant’s amendments filed on February 5, 2026 necessitated a new ground(s) of rejection in this Office action. Accordingly, Applicant’s arguments have been fully considered but are moot in view of the new ground(s) of 35 U.S.C. 103 rejection, as set forth in this office action.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See included PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Elmira Mehrmanesh whose telephone number is (571)272-5531. The examiner can normally be reached on M-F from 10-6.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bryce Bonzo, can be reached at telephone number (571) 272-3655. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Elmira Mehrmanesh/
Primary Examiner, Art Unit 2113
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