DETAILED ACTION
Response to Amendment
This Non-Final Office Action is in response to the applicant’s remarks and arguments filed on June 24, 2025.
Claims 1, 9 and 17 were amended.
Claims 1-20 remain pending in the application. Claims 1-20 are being considered on the merits.
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 .
Response to Arguments
Claim Rejections -35 U.S.C. & 101
Applicant argues that:
“the pending claims are patent eligible because they are not directed towards abstract ideas, and, even assuming, arguendo, the claimed invention were directed towards abstract ideas, the claimed invention includes an inventive concept that provides a patent-eligible application of any alleged abstract idea. Like ENFISH, the claimed invention is directed towards a specific improvement to computer technology and is therefore not directed towards abstract ideas.”.
Examiner respectfully disagree and submit that:
In response to applicant argues based on Enfish, the pending claims are directed to merely utilizing the computer as a tool for determining remediation action related to at least one of placement or load balancing based metrics , rather than “the organization of a logical structure in software to improve computer capacity” as directed in Enfish.
Thus, taken alone, the additional elements do not amount to significantly more the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functionality of the computer itself. Accordingly, the additional elements of do not amount to significantly more than the abstract idea and cannot provide an inventive concept.
Claims 1, 8 and 17 also fails both Step 2A prong 2, thus the claims are directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more Therefore, Claims 1, 8 and 17 do not recite patent eligible subject matter under 35 U.S.C. § 101.
Therefore, claims 1-20 appear to be patent ineligible under 35 USC 101.
Rejections of Claims 1-20 under 35 U.S.C. $ 103
Applicant argues that:
“Nowhere does Smith teach or suggest a remediation based on first data collected by the resource manager from the compute cluster and second data including custom metrics associated with the service “, “nowhere does Smith teach or suggest a remediation based on first data received via a first API associated with the resource manager and second data received via a second API that is different from the first API and unassociated with the resource manager”, “Smith and Verma fail to teach or suggest each and every feature of claim 1”
.
In response, Singh et al (US 2021/0224178) is added only as directly corresponding evidence to support the prior common knowledge finding as stated above.” (emphasis added).
Examiner respectfully disagree and submit that: Applicant’s arguments with respect to the newly added limitations have been considered but are moot because the arguments do not apply to the newly cited reference Singh et al (US 2021/0224178) being used in the current rejection.
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 a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Under Step 2A, Prong 1, Claim 1 recites A system, comprising: a compute cluster comprising one or more nodes, each of the one or more nodes comprising at least one of a physical machine or a virtual machine; and placement and load balancing (PLB) logic executing on the compute cluster, the PLB logic being configured to: determine whether a remediation action related to at least one of placement or load balancing is indicated based on the first data and the second data”, “ in response to determining that the remediation action is indicated, executing the remediation action at least in part by sending a command to the resource manager to execute the remediation action.”. The limitations of “determine …”, , “sending …”, are a process that, under their broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitation of generic computer components. That is, other than reciting an " A system”, “ a compute cluster”, “ nodes”, “a physical machine”, “a virtual machine”, “placement and load balancing (PLB) logic”, “remediation action related to at least one of placement or load balancing” , “data”, “command “, ” resource manager”, nothing in the claim element precludes the step from practically being performed in a human mind or with the aid of pen and paper. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas (concepts performed in the human mind including an observation, evaluation, judgment, and opinion).
Under Prong 2,
The judicial exception is not integrated into a practical application.
The additional elements “receive first data relating to a service executing on the compute cluster from a resource manager executing on the compute cluster via a first application programming interface (API) associated with the resource manager, the first data including state metadata collected by the resource manager from the compute cluster” , “receive second data relating to the service from the service via a second API that is different from the first API and unassociated with the resource manager, the second data including custom metrics associated with the service” which “receive …” are amounts to data gathering which is considered to be insignificant extra solution activity (MPEP 2106.05(g).
The additional element of " data relating to a service executing on the compute cluster from a resource manager executing on the compute cluster via a first application programming interface (API)”, “state metadata collected by the resource manager from the compute cluster”, “second API that is different from the first API and unassociated with the resource manager, the second data including custom metrics associated with the service “ are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. (see MPEP 2106.05(f)). The claim is directed to an abstract idea.
Further claim 2, it recites “ a PLB durable storage communicatively coupled to the PLB logic, wherein the PLB logic is further configured to:store at least one of the first data or the second data in the PLB durable storage”, Which is merely a recitation of insignificant pre-solution data gathering activity (see MPEP § 2106.05(g)) which does not integrate a judicial exception into practical application and is also Well-Understood, Routine and Conventional. See at least MPEP § 2106.05(d)(ll) “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”. That is, in the instant claims these limitations merely receive data which is Well-Understood, Routine and Conventional
Further claim 3, it recites “wherein the PLB logic is communicatively coupled to a PLB client and the PLB logic is further configured to: receive and reply to queries from the PLB client about current state information”. Which is merely a recitation of insignificant pre-solution data gathering activity (see MPEP § 2106.05(g)) which does not integrate a judicial exception into practical application and is also Well-Understood, Routine and Conventional. See at least MPEP § 2106.05(d)(ll) “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”. That is, in the instant claims these limitations merely receive data which is Well-Understood, Routine and Conventional
Further claim 4, it recites “wherein the PLB logic is communicatively coupled to a PLB client and the PLB logic is further configured to:receive and process a PLB solution request from the PLB client” , Which is merely a recitation of insignificant pre-solution data gathering activity (see MPEP § 2106.05(g)) which does not integrate a judicial exception into practical application and is also Well-Understood, Routine and Conventional. See at least MPEP § 2106.05(d)(ll) “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”. That is, in the instant claims these limitations merely receive data which is Well-Understood, Routine and Conventional
Further claim 4, recites “determine a PLB action command based on the PLB solution request”, “control the resource manager to execute the PLB action command”, The limitations of “to determine…” , “control…” , is a process that, under their broadest reasonable interpretation, covers performance of the limitation in the mind .
Further claim 5, recites “ wherein the PLB logic is communicatively coupled to a PLB client and the PLB logic is further configured to:receive a what-if scenario query from the PLB client and reply to the what-if scenario query with a potential PLB solution relative to the what-if scenario query”, Which is merely a recitation of insignificant pre-solution data gathering activity (see MPEP § 2106.05(g)) which does not integrate a judicial exception into practical application and is also Well-Understood, Routine and Conventional. See at least MPEP § 2106.05(d)(ll) “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”. That is, in the instant claims these limitations merely receive data which is Well-Understood, Routine and Conventional
.
Further claim 6, recites “wherein the PLB logic is communicatively coupled to a PLB client and the PLB logic is further configured to perform at least one of: receive and reply to queries from the PLB client about PLB logic current state information”, “receive and process an operation control command from the PLB client for determining a PLB action command and transmit the PLB action command to the resource manager for execution by the resource manager”, Which is merely a recitation of insignificant pre-solution data gathering activity (see MPEP § 2106.05(g)) which does not integrate a judicial exception into practical application and is also Well-Understood, Routine and Conventional. See at least MPEP § 2106.05(d)(ll) “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”. That is, in the instant claims these limitations merely receive data which is Well-Understood, Routine and Conventional
Further claim 7, recites, “ wherein the PLB logic is further configured to:in response to receiving a query or request from an external PLB client, spawn a PLB logic child and offload processing of the query or request from the PLB logic to the child PLB logic”, Which is merely a recitation of insignificant pre-solution data gathering activity (see MPEP § 2106.05(g)) which does not integrate a judicial exception into practical application and is also Well-Understood, Routine and Conventional. See at least MPEP § 2106.05(d)(ll) “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”. That is, in the instant claims these limitations merely receive data which is Well-Understood, Routine and Conventional
Further claim 8, recites “ wherein the service executing on the compute cluster comprises a database service”, which are merely recitations of generic computing components (see MPEP §2106.05(f)) which does not integrate a judicial exception into practical application. These elements represent no more than mere instructions to apply the judicial exception on a computer. Further, the claim does not contain any additional elements that comprise significantly more than the judicial exception. In particular, the additional elements identified above are merely recitations of generic computing components (see MPEP 2106.05(f)) which do not amount to significantly more. The claim is therefore not patent eligible.
As to claims 9-16,
Similar analysis as claims 1-8 is applied to claims 9-16 .
As to claims 17-20,
Further Claim 17: The judicial exception is not integrated into a practical application. In particular, the claim recites the following additional elements “A computer-readable storage medium having program code recorded thereon that when executed”, “ least one processor” which are merely recitations of generic computing components (see MPEP §2106.05(f)) which does not integrate a judicial exception into practical application. These elements represent no more than mere instructions to apply the judicial exception on a computer. A computer-readable storage medium having program code recorded thereon that when executed by at least one processor, are all mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). This does not integrate into a practical application, NOR does it provide significantly more.
Similar analysis as claims 2-4 is applied to claims 18-20.
For at least these reasons, claims 1-20 are not patent eligible.
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.
Claim(s) 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Smith et al. (US 2017/0060636, Smith hereinafter) in view of Singh et al (US 2021/0224178, Singh hereinafter).
As to claim 1, Smith teaches a system (e.g., see FIG. 1) , comprising:
a compute cluster comprising one or more nodes (e.g., “COMPUTE NODE 112a”, FIG. 1, for “a cluster of virtual machines (e.g., a cloud)” in para 35) , each of the one or more nodes comprising at least one of a physical machine or a virtual machine (e.g., para 19, “the compute nodes 112a-c may be any combination of virtual machines”); and
placement and load balancing (PLB) logic (e.g., “Action Adapter 230”, FIG 2) executing on the compute cluster (e.g., [0042] The example action adapters 230a-b are instructions, programs, executable code, scripts, etc. configured to route data and perform actions., “ an action(s) may be an operation(s) and/or a function(s) to “ reallocating a virtual machine executed by a first manager 114”.
Thus, one of the “action adapters 230a-b “ coupled with “an action(s) may be an operation(s) and/or a function(s) that rearranges” , “reallocating a virtual machine” represent placement and load balancing (PLB) logic ) , the PLB logic being configured to:
receive first data relating to a service executing on the compute cluster from a resource manager (e.g., “Resource manager 108”, FIG. 1, para 66, “ data to be routed to and/or received by different components”) executing on the compute cluster via a first application programming interface (API) (e.g., para 42, “action adapters 230a-b are instructions, programs, executable code, scripts) associated with the resource manager, the first data including state metadata collected by the resource manager from the compute cluster (e.g., para 28, “cloud manager 106 generates performance and/or health metrics corresponding to the example resource platform 102 and/or the example network 104 (e.g., bandwidth, throughput, latency, error rate, etc.)” and “etc. configured to route data and perform actions)” in para 42.
Thus, the “instructions, programs, executable code, scripts” represent the API , The “data “ coupled with the “health metrics” represent the first data including state metadata ) ;
receive second data relating to the service from the service via a second API (e.g., another one of the “Client interface(s) 110”, FIG. 1 “) that is different from the first API (e.g., para 66, “widget(s) 310 may initiate execution of a particular operation and/or cause data to be routed to and/or received by different components of the example computing environment 100. In some examples, the example widget(s) 310 may include a graphically illustrated recommendation(s) or compute issue(s) resolution(s) in response to an alert(s)”)” ;
determine whether a remediation action related to at least one of placement or load balancing is indicated based on the first data (e.g., para 14, “remediation operations and/or functions and apply the new remediation operations ‘ and “to remediate computing issues that may arise in the example resource platform(s) 102.” in para 30) is indicated (e.g., para ) ; and
in response to determining that the remediation action is indicated, send a command to the resource manager to execute the PLB action , executing the remediation action at least in part by sending a command to the resource manager to execute the remediation action (e.g.,
[[0079] The example recommendation database 430 stores recommendations and/or resolutions for compute issues experienced by ones of the compute resources of the example resource platform(s) 102. For example, the example recommendation database 430 may store recommendations or resolutions that suggest an end user(s) perform remediation approaches such as, for example, adding a new virtual hard disk(s) to expand an existing disk(s) of a virtual machine(s), adding more CPU capacity, adding capacity to a data store, bringing any failed hosts online or resolving a network partition if one exists, etc “
[0055] In some examples, the example alert determiner 215 accesses and/or receives alerts. The example alert determiner 215 evaluates and/or analyzes the alerts. The example alert determiner 215 may also access databases to identify default or recommended compute resource(s) settings and recommendations. In examples disclosed herein, the example alert determiner 215 determines if actions associated with recommendations are applicable in resolving compute resource issues
Also, see para [0076] action executor 415 accesses and/or receives and executes the example adapters 230a-b, 235 in response to automatic or manual compute issue(s) remediation. The example adapter executor 415 also accesses and/or receives and executes one(s) of the example adapters 230a-b, 235 in response to an alert(s). In other examples, the example adapter executor 415 accesses and/or receives and executes one(s) of the example adapters 230a-b, 235 at times when an alert is not generated (e.g., a user initiates compute issue(s) remediation via the example client interface(s) 110).).
However, Smith does not explicitly teach the second data unassociated with the resource manager, the second data including custom metrics associated with the service , the remediation action based on the first data and the second data.
Sing teaches second data via and a second API (e.g., para 61, “All metrics can be accessed programmatically using a Representational State Transfer (REST) API that returns either the JavaScript Object Notation (JSON) or the eXtensible Markup Language (XML) format. Also, the REST API can be used to query and manipulate the application environment.”) , second data unassociated with the resource manager, the second data including custom metrics associated with the service (e.g., [0058] Policies can be configured to trigger actions when a health rule is violated or when any event occurs. Triggered actions can include … running remediation scripts. “ and “ dynamic baselines can be used to automatically establish what is considered normal behavior for a particular application. Policies and health rules can be used against baselines or other health indicators for a particular application to detect and troubleshoot problems before users are affected. Health rules can be used to define metric conditions to monitor, such as when the “average response time is four times slower than the baseline”. The health rules can be created and modified based on the monitored application environment” in para 56, ) , the remediation action based on the first data and the second data (para 31, “the collected data may include performance data (e.g., metrics, metadata, etc.) and topology data (e.g., indicating relationship information). The agent-collected data may then be provided to one or more servers or controllers to analyze the data.” And “extensions that use the machine agent can be created to report user defined custom metrics. These custom metrics are base-lined and reported in the controller, just like the built-in metrics. In in para 60 ).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Smith with those of Singh because both references are directed to related systems addressing similar technical problems within the same field and seek to improve system performance, reliability, and efficiency.
Smith et al. disclose a management system that manages grid computing processing, the calculation capability of the arithmetic device , allowing a user to select the arithmetic device that is available in the grid computing processing while Singh et al. teach prediction processing of predicting the temporal change in the calculation capability available in the grid computing processing, matching processing of allocating on a basis of a result of the prediction processing.
Incorporating the teachings of Singh et al. into the system of Smith et al. would have been a predictable and logical modification, yielding improved operational robustness and efficiency without requiring undue experimentation.
Such a combination would merely involve the substitution or integration of known elements performing their established functions, as taught by Singh et al., into the system of Smith et al., consistent with design incentives and market demands for improved performance and scalability. Moreover, Singh et al. explicitly recognize benefits to provide “ automatic configuration of software systems for optimal workload management and performance using machine learning (see Singh, para 12) . —that would naturally be desirable in the system of Smith et al.
Accordingly, to one of ordinary skill in the art would have had a reasonable expectation of success in combining Smith et al. with Singh et al., and the combination represents no more than the predictable use of prior art elements according to their known functions.
As to claim 2, Smith teaches a PLB durable storage (e.g., “parameter(s) database 425 “, FIG. 4) communicatively coupled to the PLB logic, wherein the PLB logic is further configured to: store at least one of the first data or the second data in the PLB durable storage (e.g., para [0078] The example parameter(s) database 425 stores parameters associated with the compute resource(s) of the example resource platform(s) 102. For example, the example parameter(s) database 425 may store parameters or information defining a default or recommended compute resource(s) setting(s).).
As to claim 3, Smith does not teach wherein the PLB logic is communicatively coupled to a PLB client and the PLB logic is further configured to: receive and reply to queries fromealth rules for testing business transaction performance can include business transaction response time and business transaction error rate. For example, health rule that tests whether the business transaction response time is much higher than normal can define a critical condition as the combination of an average response time greater than the default baseline by 3 standard deviations and a load greater than 50 calls per minute” for “The network 420 may include one or more machines such as load balance machines and other machines” in para 68) Thus, 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 method of Smith by adopting the teachings of Singh to provide “ automatic configuration of software systems for optimal workload management and performance using machine learning (see Singh, para 12) .
As to claim 4, Smith does not teach wherein the PLB logic is communicatively coupled to a PLB client and the PLB logic is further configured to: receive and process a PLB solution request from the PLB client; determine a PLB action command based on the PLB solution request; and control the resource manager to execute the PLB action command. However, Singh teaches wherein the PLB logic is communicatively coupled to a PLB client and the PLB logic is further configured to: receive and process a PLB solution request from the PLB client ; determine a PLB action command based on the PLB solution request; and control the resource manager to execute the PLB action command (e.g., para 100, wherein “provide for automatic configuration of software systems for optimal workload management and performance using machine learning. “, “finding appropriate software solutions for a given workload through an automated machine learning driven approach that leverages a vast data repository of diverse data about various technology stacks”, and “FIGS. 9A-9B illustrate an example of the flow. Assume for the example that the sub-system comprises a virtual machine (type and hardware) that a software solution is running on, and nd “finding alternative software solutions for a given workload, the techniques herein produce efficient topologies, in terms of performance and cost, for desired use-cases”.” in para 133. Thus, receive and process a PLB solution request from the PLB client; determine a PLB action command based on the PLB solution request; and control the resource manager to execute the PLB action command).
Thus, 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 method of Smith by adopting the teachings of Singh to provide “ automatic configuration of software systems for optimal workload management and performance using machine learning (see Singh, para 12) .
As to claim 5, Smith does not teach wherein the PLB logic is communicatively coupled to a PLB client and the PLB logic is further configured to: receive a what-if scenario query from the PLB client and reply to the what-if scenario query with a potential PLB solution relative to the what-if scenario query. However, Singh teaches wherein the PLB logic is communicatively coupled to a PLB client and the PLB logic is further configured to: receive a what-if scenario query from the PLB client and reply to the what-if scenario query with a potential PLB solution relative to the what-if scenario query (e.g., see FIGs 9A-9B, para 123, wherein “a virtual machine (type and hardware) that a software solution is running on, and the techniques herein obtain n observations (aggregated metric data and metadata for each observation). As shown in the graph 900a of FIG. 9A, consider that the techniques herein cluster these n sub-systems into two clusters A and B based on the workload metrics L1 and L2 (e.g., L1<L2), thus two clusters each representing a specific load profile. The sub-system metric data also comprises of sub-system performance, resource utilization, and cost metrics.” and “finding alternative software solutions for a given workload, the techniques herein produce efficient topologies, in terms of performance and cost, for desired use-cases”.” in para 133 ) .
Thus, 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 method of Smith by adopting the teachings of Singh to provide “ automatic configuration of software systems for optimal workload management and performance using machine learning (see Singh, para 12) .
As to claim 6, Smith does not teach wherein the PLB logic is communicatively coupled to a PLB client and the PLB logic is further configured to perform at least one of: receive and reply to queries from the PLB client about PLB logic current state information; or receive and process an operation control command from the PLB client for determining a PLB action command and transmit the PLB action command to the resource manager for execution by the resource manager. However, Singh teaches wherein the PLB logic is communicatively coupled to a PLB client and the PLB logic is further configured to perform at least one of: receive and reply to queries from the PLB client about PLB logic current state information (e.g., para [0056] health indicators “, “ to define metric conditions to monitor, such as when the “average response time is four times slower than the baseline”. The health rules can be created and modified based on the monitored application environment.
[0057] Examples of health rules for testing business transaction performance can include business transaction response time and business transaction error rate. For example, health rule that tests whether the business transaction response time is much higher than normal can define a critical condition as the combination of an average response time greater than the default baseline by 3 standard deviations and a load greater than 50 calls per minute”, “health rules and other health rules can be defined as desired by the user.) ; or receive and process an operation control command from the PLB client for determining a PLB action command and transmit the PLB action command to the resource manager for execution by the resource manager (e.g., see FIG. 4, “Agent 412 may determine network browser navigation timing metrics, access browser cookies, monitor code, and transmit data to data collection 495, controller 490, or another device. Agent 412 may perform other operations related to monitoring a request or a network at client 405 as discussed herein including report generating)..
Thus, 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 method of Smith by adopting the teachings of Singh to provide “ automatic configuration of software systems for optimal workload management and performance using machine learning (see Singh, para 12) .
As to claim 7, Smith does not teach wherein the PLB logic is further configured to: in response to receiving a query or request from an external PLB client, spawn a PLB logic child and offload processing of the query or request from the PLB logic to the child PLB logic. However, Singh teaches wherein the PLB logic is further configured to: in response to receiving a query or request from an external PLB client, spawn a PLB logic child and offload processing of the query or request from the PLB logic to the child PLB logic (e.g., see FIG. 4, para [0068] Network 420 may facilitate communication of data among different servers, “, “The network 420 may include one or more machines such as load balance machines and other machines”. Thus, one of the” load balance machines” include the PLB logic child).
Thus, 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 method of Smith by adopting the teachings of Singh to provide “ automatic configuration of software systems for optimal workload management and performance using machine learning (see Singh, para 12) .
As to claim 8, Smith teaches wherein the service executing on the compute cluster comprises a database service (e.g., para [0055] In some examples, the example alert determiner 215 accesses and/or receives alerts. The example alert determiner 215 evaluates and/or analyzes the alerts. The example alert determiner 215 may also access databases to identify default or recommended compute resource(s) settings and recommendations. In examples disclosed herein, the example alert determiner 215 determines if actions associated with recommendations are applicable in resolving compute resource issues..
As to claim 9, see rejection of claim 1 above.
As to claim 10-15, see rejection of claims 2-7 above.
As to claim 16, see rejection of claim 8 above.
As to claim 17, see rejection of claim 1 above. Smith teaches further a computer-readable storage medium having program code recorded thereon that when executed by at least one processor causes the at least one processor to perform a method (e.g., para [0112] Flowcharts representative of example machine readable instructions for implementing the example resource manager 108 of FIGS. 1-are shown in FIGS. 6-11. In these examples, the machine readable instructions comprise a program(s) for execution by a processor such as the processor 1212 shown in the example processor platform 1200 discussed below in connection with FIG. 12. The program(s) may be embodied in software stored on a tangible computer readable storage medium such as a CD-ROM, a floppy disk, a hard drive, a digital versatile disk (DVD), a Blu-ray disk, or a memory associated with the processor 1212, but the entire program(s) and/or parts thereof could alternatively be executed by a device other than the processor 1212 and/or embodied in firmware or dedicated hardware. Further, although the example program(s) are described with reference to the flowchart illustrated in FIGS. 6-11, many other methods of implementing the example resource manager 108 may alternatively be used. For example, the order of execution of the blocks may be changed, and/or some of the blocks described may be changed, eliminated, or combined.).
As to claims 18-20, see rejection of claims 2-4 above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Dar et al. discloses A system is for use with a data communication network that includes a plurality of servers and a plurality of programs to be run by the servers to provide a plurality of services to devices communicating with the servers over the network. The system comprises a memory that contains computer-readable and computer-executable instructions, and a processor coupled to the memory and configured to read and execute the instructions, the instructions being configured to cause the processor to determine a suggested mapping of the programs to the servers that is different than a current mapping of the programs to the servers.
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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ABDOU K SEYE whose telephone number is (571)270-1062. The examiner can normally be reached M-F 9-5:30.
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, Pierre Vital can be reached at 5712724215. 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.
/ABDOU K SEYE/Examiner, Art Unit 2198
/PIERRE VITAL/Supervisory Patent Examiner, Art Unit 2198
Prosecution Insights