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 .
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.
The test for obviousness is not whether the features of a secondary reference may be bodily incorporated into the structure of the primary reference; nor is it that the claimed invention must be expressly suggested in any one or all of the references. Rather, the test is what the combined teachings of the references would have suggested to those of ordinary skill in the art. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981).
Claims 1, 4, 7-8, 11, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Kozhaya et al (“Kozhaya”, US 20190347326) in view of Das et al (“Das”, US 20200004591).
Regarding Claim 1, Kozhaya teaches a method, comprising: determining, by a processor set, a service availability impact and a user tone associated with a service by analyzing one or more electronic communications using natural language processing (par 19; par 26; The service availability impact is the node phase, such as when a failure node occurs. The user tone is the sentiment determined based on the tone analyzer. The impact urgency score is the determined score of individual nodes based on a measured performance metric for a phase of a communication, a human sentiment, a transition, and an elapsed time at the node.);
determining, by the processor set, an impact urgency score based on the service availability impact and the user tone (par 19; par 26; The service availability impact is the node phase, such as when a failure node occurs. The user tone is the sentiment determined based on the tone analyzer. The impact urgency score is the determined score of individual nodes based on a measured performance metric for a phase of a communication, a human sentiment, a transition, and an elapsed time at the node.);
Kozhaya does not explicitly teach determining, by the processor set, a scale-by value based on the impact urgency score; and scaling, by the processor set and based on the scale-by value, a computing cluster running a workload that provides the service.
Das teaches determining, by the processor set, a scale-by value based on the impact urgency score (par 74; The impact urgency score is the importance of the software component, such as medium or high. The scale-by value is the predetermined amount resources are scaled up by.);
and scaling, by the processor set and based on the scale-by value, a computing cluster running a workload that provides the service (par 74; The impact urgency score is the importance of the software component, such as medium or high. The scale-by value is the predetermined amount resources are scaled up by.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of scale up functionality of Das because it allows for demand of services to be met without compromising on performance. Infrastructure can be dynamically scaled up and down based on demand (Das; par 74) so that resources are available when not needed and not wasted.
Regarding Claim 4, Kozhaya and Das teach the method of claim 1.
Kozhaya further teaches wherein the one or more electronic communications include communications selected from a group consisting of:
email;
telephone call;
help desk ticket;
online chat (par 16);
and social media message.
Regarding Claim 7, Kozhaya and Das teach the method of claim 1.
Kozhaya does not explicitly teach wherein the determining the scale-by value comprises: determining a priority score based on the impact urgency score;
and determining the scale-by value based on the priority score using a predefined relationship that equates respective priority scores to respective scale-by values.
Das teaches wherein the determining the scale-by value comprises: determining a priority score based on the impact urgency score (par 74; The impact urgency score is the importance of the software component, such as medium or high. The scale-by value is the predetermined amount resources are scaled up by.);
and determining the scale-by value based on the priority score using a predefined relationship that equates respective priority scores to respective scale-by values (par 74; The impact urgency score is the importance of the software component, such as medium or high. The scale-by value is the predetermined amount resources are scaled up by.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of scale up functionality of Das because it allows for demand of services to be met without compromising on performance. Infrastructure can be dynamically scaled up and down based on demand (Das; par 74) so that resources are available when not needed and not wasted.
Regarding Claim 8, Kozhaya and Das teach the method of claim 7.
Kozhaya does not explicitly teach further comprising adjusting one or more of the respective scale-by values in the predefined relationship based on feedback regarding the scaling the computing cluster.
Das teaches further comprising adjusting one or more of the respective scale-by values in the predefined relationship based on feedback regarding the scaling the computing cluster (par 74; The impact urgency score is the importance of the software component, such as medium or high. The scale-by value is the predetermined amount resources are scaled up by.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of scale up functionality of Das because it allows for demand of services to be met without compromising on performance. Infrastructure can be dynamically scaled up and down based on demand (Das; par 74) so that resources are available when not needed and not wasted.
Regarding Claim 11, Claim 11 is rejected with the same reasoning as Claim 1.
Regarding Claim 16, Claim 16 is rejected with the same reasoning as Claim 1.
Claims 2, 12, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Kozhaya and Das in view of Keen et al (“Keen”, US 20200106876).
Regarding Claim 2, Kozhaya and Das teach the method of claim 1.
Kozhaya does not explicitly teach wherein the impact urgency score is additionally based on an urgency value derived from a total number of the one or more electronic communications.
Keen teaches wherein the impact urgency score is additionally based on an urgency value derived from a total number of the one or more electronic communications (par 53-54; par 56-57).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kozhaya with the importance ratings of Keen because it allows for prioritizing communications with a larger amount of users involved, so that more users get better service.
Regarding Claim 12, Claim 12 is rejected with the same reasoning as Claim 2.
Regarding Claim 17, Claim 17 is rejected with the same reasoning as Claim 2.
Claims 3, 13, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Kozhaya and Das in view of Shanmugam et al (“Shanmugam”, US 20180268385).
Regarding Claim 3, Kozhaya and Das teach the method of claim 1.
Kozhaya further teaches wherein the analyzing one or more electronic communications comprises detecting a tone keyword in the one or more electronic communications (par 19; par 26; The service availability impact is the node phase, such as when a failure node occurs. The user tone is the sentiment determined based on the tone analyzer. The impact urgency score is the determined score of individual nodes based on a measured performance metric for a phase of a communication, a human sentiment, a transition, and an elapsed time at the node. The tone keyword is the word that was used to detect the human sentiment from the user communication with the node.).
Kozhaya and Das do not explicitly teach wherein the analyzing one or more electronic communications comprises detecting a service keyword and a service availability keyword in the one or more electronic communications.
Shanmugam teaches wherein the analyzing one or more electronic communications comprises detecting a service keyword and a service availability keyword in the one or more electronic communications (par 27).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kozhaya and Das with the keyword analyzing of Shanmugam because it allows user to be able to access more relevant services based on keywords that were mentioned, thereby improving user experience.
Regarding Claim 13, Claim 13 is rejected with the same reasoning as Claim 3.
Regarding Claim 18, Claim 18 is rejected with the same reasoning as Claim 3.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Kozhaya and Das in view of Mahajan et al (“Mahajan”, US 20200314176).
Regarding Claim 5, Kozhaya and Das teach the method of claim 1.
Kozhaya does not explicitly teach further comprising: creating a story comprising a data structure that includes information defining the service, the impact urgency score, the scale-by value, and a date and time the scaling was performed; and saving the story in a repository.
Das teaches the impact urgency score, the scale-by value (par 74; The impact urgency score is the importance of the software component, such as medium or high. The scale-by value is the predetermined amount resources are scaled up by.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of scale up functionality of Das because it allows for demand of services to be met without compromising on performance. Infrastructure can be dynamically scaled up and down based on demand (Das; par 74) so that resources are available when not needed and not wasted.
Kozhaya and Das do not explicitly teach further comprising: creating a story comprising a data structure that includes information defining the service, and a date and time the scaling was performed; and saving the story in a repository.
Mahajan teaches further comprising: creating a story comprising a data structure that includes information defining the service, and a date and time the scaling was performed (par 49);
and saving the story in a repository (par 49).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kozhaya and Das with the database of Mahajan because it allows for the history of a node to be tracked, which may be useful for debugging purposes if an error occurs.
Claims 9-10, 15, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Kozhaya and Das in view of Devendranath et al (“Devendranath”, US 11843548).
Regarding Claim 9, Kozhaya and Das teach the method of claim 1.
Kozhaya and Das do not explicitly teach wherein: the workload comprises a containerized application; the computing cluster comprises nodes that run the containerized application; the nodes host pods that run one or more containers of the containerized application; and the scaling comprises deploying one or more additional pods running one or more additional containers of the containerized application.
Devendranath teaches wherein: the workload comprises a containerized application (Col. 2 lines 28-67; Col. 3 lines 1-63);
the computing cluster comprises nodes that run the containerized application (Col. 2 lines 28-67; Col. 3 lines 1-63);
the nodes host pods that run one or more containers of the containerized application (Col. 2 lines 28-67; Col. 3 lines 1-63);
and the scaling comprises deploying one or more additional pods running one or more additional containers of the containerized application (Col. 2 lines 28-67; Col. 3 lines 1-63).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kozhaya and Das with the containerized applications of Devendranath because it allows for improved efficiency, scalability, and management of computing resources.
Regarding Claim 10, Kozhaya and Das teach the method of claim 1.
Kozhaya and Das do not explicitly teach wherein: the workload comprises a containerized application; the computing cluster comprises nodes that run the containerized application; the nodes host pods that run one or more containers of the containerized application; and the scaling comprises allocating additional computing resources to existing pods running the one or more containers of the containerized application.
Devendranath teaches wherein: the workload comprises a containerized application (Col. 2 lines 28-67; Col. 3 lines 1-63);
the computing cluster comprises nodes that run the containerized application (Col. 2 lines 28-67; Col. 3 lines 1-63);
the nodes host pods that run one or more containers of the containerized application (Col. 2 lines 28-67; Col. 3 lines 1-63);
and the scaling comprises allocating additional computing resources to existing pods running the one or more containers of the containerized application (Col. 2 lines 28-67; Col. 3 lines 1-63).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kozhaya and Das with the containerized applications of Devendranath because it allows for improved efficiency, scalability, and management of computing resources.
Regarding Claim 15, Kozhaya and Das teach the computer program product of claim 11.
Devendranath teaches wherein the scaling comprises one of: horizontal scaling of pods in the computing cluster running the workload that provides the service (Col. 2 lines 28-67; Col. 3 lines 1-63);
and vertical scaling of pods in the computing cluster running the workload that provides the service (Col. 2 lines 28-67; Col. 3 lines 1-63).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kozhaya and Das with the containerized applications of Devendranath because it allows for improved efficiency, scalability, and management of computing resources.
Regarding Claim 20, Claim 20 is rejected with the same reasoning as Claim 15.
Allowable Subject Matter
Claims 6, 14, and 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.
The following is a statement of reasons for the indication of allowable subject matter:
In interpreting the currently amended claims, in light of the specification, the Examiner finds the claimed invention to be patentably distinct from the prior art of record.
Regarding Claims 6, 14, and 19, the closest prior art of record Kozhaya et al (“Kozhaya”, US 20190347326) in view of Das et al (“Das”, US 20200004591) in further view of Mahajan et al (“Mahajan”, US 20200314176) in even further view of Devendranath et al (“Devendranath”, US 11843548) does not teach a method, comprising: determining, by a processor set, a service availability impact and a user tone associated with a service by analyzing one or more electronic communications using natural language processing; determining, by the processor set, an impact urgency score based on the service availability impact and the user tone; determining, by the processor set, a scale-by value based on the impact urgency score; and scaling, by the processor set and based on the scale-by value, a computing cluster running a workload that provides the service; further comprising: creating a story comprising a data structure that includes information defining the service, the impact urgency score, the scale-by value, and a date and time the scaling was performed; and saving the story in a repository; further comprising: identifying a pattern by analyzing plural stories saved in the repository as a time series; and proactively scaling the computing cluster running the workload based on the identified pattern.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Nouri (US 20220246146), Abstract - Systems and methods are provided for determining importance and urgency of a task based on acoustic features of audio input associated with the task. The determining includes classifying the task into one or more classes associated with importance, urgency, and priority of the task. The classification may use a trained machine learning model of acoustic features and embedding for a neural network. The task classifier uses feature acoustics of either or both the foreground and background audio. The feature acoustics include a pitch, a tone, and a volume over a time duration of the audio input. A combination of the acoustic features determines a class associated with the task. The machine learning model includes a regression model of acoustic features over time and a model with embedding for a neural network.
Tanniru et al (US 20210263733), Abstract - A device may receive input data identifying user stories, test case documents, event logs, and application logs associated with an application, and may perform natural language processing on the user stories and the test case documents, identified in the input data, to generate a first state diagram associated with the application. The device may process the event logs identified in the input data, with a heuristic miner model, to generate a second state diagram associated with the application, and may process the application logs identified in the input data, with a clustering model, to generate a volumetric analysis associated with the application. The device may perform post processing of the first state diagram, the second state diagram, and the volumetric analysis, to remove duplicate data and unmeaningful data and to generate modified outputs, and may perform actions based on the modified outputs.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RAQIUL AMIN CHOUDHURY whose telephone number is (571)272-2482. The examiner can normally be reached Monday-Friday 7:30 AM - 5:30 PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, John Follansbee can be reached at 571-272-3964. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/RAQIUL A CHOUDHURY/Examiner, Art Unit 2444