Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Office Action is in response to application filed on July 1, 2024.
Claims 1-20 are pending.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-3, 8-10 and 15-17 are rejected under 35 U.S.C. 103 as being unpatentable over Hitchcock et al. (US 2017/0277615) in view of De Rosa et al. (US 9,215,151).
With respect to Claim 1, Hitchcock et al. disclose:
providing, to a first client device, a first instance of a first instrumented application comprising a first agent, (Service-oriented systems may be configured to process requests from various internal or external systems, such as client computer systems (first client device) or computer systems consuming networked-based services (e.g., web services). For instance, an end-user operating a web browser on a client computer system may submit a request for data (e.g., data associated with a product detail page, a shopping cart application, a checkout process, search queries, etc.). In another example, a computer system may submit a request for a web service (e.g., a data storage service, a data query, etc.). In general, services may be configured to perform any of a variety of business processes. The service interactions may include requests (e.g., for services to be performed), responses to requests, and other suitable events, Paragraph 26; each service within the service-oriented system may include a log reporting agent, such as log reporting agent 2350. Log reporting agent 2350 may in various embodiments report the contents of inbound request log 2330 and/or outbound request log 2340 to a log repository (e.g., a data store, such as a database or other location in memory), Paragraph 91) wherein the first agent is configured to log a first set of telemetry data associated with performance metrics of the first instance of the first instrumented application and a time period associated with the first set of telemetry data; (To monitor the service interactions, lightweight instrumentation may be added to the services (first instrumented application). The instrumentation (e.g., a reporting agent (first agent) associated with each service) may collect and report data (telemetry data) associated with each inbound request, outbound request, or other service interaction (e.g., a timer-based interaction) processed by a service., Paragraph 29; the service-oriented system of various embodiments may in some cases receive numerous (e.g., thousands, millions, or some other quantity) of services requests per a given time period (e.g., per day, per week, or some other time period), such as requests from network-based browsers (e.g., web browsers) on client systems or requests from computer systems consuming network-based services (e.g., web services), Paragraph 75)
determining an overall data throughput associated with the first instrumented application based on the first set of telemetry data; (the collective performance of the service and the additional services, (first set of telemetry data associated with a first instrumented application) as well as other components, may be monitored to generate the information external to the service (determine overall data throughput), Paragraph 51; externalities used to inform the dynamic adjustment of the sampling rate for a service may include, for example: the volume of traffic in all or part of the service-oriented system, the size of a fleet of hosts implementing the service, a determination of redundancy in the trace information, an anticipation of higher or lower traffic volume at a future point in time, a determination that a performance threshold has been crossed, (overall data throughput/first set of telemetry data) and/or a determination that a performance threshold will be crossed at a future point in time, Paragraph 51)
and comparing the overall data throughput to a first threshold, wherein when the overall data throughput exceeds the first threshold; (externalities used to inform the dynamic adjustment of the sampling rate for a service may include, for example: the volume of traffic in all or part of the service-oriented system, the size of a fleet of hosts implementing the service, a determination of redundancy in the trace information, an anticipation of higher or lower traffic volume at a future point in time, a determination that a performance threshold has been crossed, (compare overall data throughput to a first threshold) and/or a determination that a performance threshold will be crossed at a future point in time, Paragraph 51)
determine a reduced sampling rate to reduce the overall data throughput below the first threshold; (a second sampling rate may be determined based (at least in part) on information external to the service (externalities), Paragraph 51; the sampling rate may be reduced for one or more relevant services. As another example, as total network traffic increases, the number of different use cases may not scale linearly, so the sampling rates for services may be reduced, Paragraph 42)
and update an application performance monitoring server to set a sampling rate of the application performance monitoring server to the reduced sampling rate; (the second sampling rate (reduced sampling rate) may be assigned to the service, Paragraph 52)
comparing the overall data throughput to a second threshold; (determine that total traffic decreases (overall throughput compared to a second threshold), Paragraph 42)
wherein when the overall data throughput is lower than the second threshold; (when the total traffic decreases (lower than the second threshold), Paragraph 42)
determine an increased sampling rate to increase the overall data throughput above the second threshold; (sampling rates may be increased as total traffic decreases, Paragraph 42)
and update the application performance monitoring server to set the sampling rate to the increased sampling rate; (the second sampling rate (increased sampling rate) may be assigned to the service, Paragraph 52)
and when the overall data throughput does not exceed the first threshold or is not lower than the second threshold, store the first set of telemetry data in memory. (trace information may be collected or preserved (stored in memory) at the entity according to the new rate (does not exceed the first threshold or is not lower than the second threshold), Paragraph 63)
Hitchcock et al. do not disclose:
a second threshold lower than the first threshold
However, De Rosa et al. disclose:
a second threshold lower than the first threshold (dynamic sampling rate adjustment that varies the sampling rate. The rate can be varied based on the needs of the service and the desired amounts of trace data to be collected over the network. Although the description below uses RPC traffic to explain certain principles, the teachings herein are applicable to any sampling-based statistical data gathering. The teachings herein can therefore be utilized by any group that collects sampled data from a wide variety of sources where the rate of data production varies significantly from source to source and where there is a minimum sampling rate (in samples/second, for example) (second threshold lower than the first threshold necessary to establish valid statistical data, Column 2, lines 24-35)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of De Rosa et al. into the teaching of Hitchcock et al. to include a second threshold lower than the first threshold in order to establish valid statistical data (De Rosa et al., Column 2, lines 24-35)
With respect to Claim 2, all the limitations of Claim 1 have been addressed above; and Hitchcock et al. further disclose:
wherein the performance metrics of the first instrumented application include one or more of: latency, resource usage, and availability. (the system monitoring functionality 210 may monitor any suitable performance metrics, such as metrics relating to throughput, latency, processor usage, memory usage, storage usage, network usage, cache efficiency, component I/O performance, etc. The performance metrics may relate to individual components, such as the network traffic at a particular service or host, or to components in the aggregate, such as the network traffic at a set of services or hosts., Paragraph 39)
With respect to Claim 3, all the limitations of Claim 1 have been addressed above; and Hitchcock et al. further disclose:
wherein when the overall data throughput does not exceed the first threshold: retaining the first set of telemetry data based on enterprise rules associated with the first instrumented application when the overall data throughput does not exceed the first threshold. (externalities used to inform the dynamic adjustment of the storage rate for a storage node may include, for example: the volume of traffic in all or part of the service-oriented system, the size of a fleet of hosts, a determination of redundancy in the trace information, an anticipation of higher or lower traffic volume at a future point in time, a determination that a performance threshold has been crossed, (overall throughput does not exceed a first threshold) and/or a determination that a performance threshold will be crossed at a future point in time, Paragraph 59; the amount of trace information that is generated and/or preserved (retraining the first set of telemetry data) may be adjusted based on conditions in the distributed system (overall data throughput does not exceed a first threshold/enterprise rules), Paragraph 22; adjust the preservation rate based on recent conditions, current conditions, and/or anticipated conditions in the system. (enterprise rules), Paragraph 60)
Claims 8-10 are system claims corresponding to the method claims above (Claims 1-3) and, therefore, are rejected for the same reasons set forth in the rejections of Claims 1-3.
Claims 15-17 are non-transitory computer readable medium claims corresponding to the method claims above (Claims 1-3) and, therefore, are rejected for the same reasons set forth in the rejections of Claims 1-3.
Claims 5, 12 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Hitchcock et al. (US 2017/0277615) in view of De Rosa et al. (US 9,215,151) and in further view of Obaidi et al. (US 2022/0121773).
With respect to Claim 5, all the limitations of Claim 1 have been addressed above; and Hitchcock et al. and De Rosa et al. further disclose:
wherein when the overall data throughput exceeds the first threshold, (Hitchcock et al., externalities used to inform the dynamic adjustment of the storage rate for a storage node may include, for example: the volume of traffic in all or part of the service-oriented system, the size of a fleet of hosts, a determination of redundancy in the trace information, an anticipation of higher or lower traffic volume at a future point in time, a determination that a performance threshold has been crossed, (overall throughput exceed a first threshold) and/or a determination that a performance threshold will be crossed at a future point in time, Paragraph 59
generate a request to set the sampling rate to the reduced sampling rate; (Hitchcock et al., As shown in 610, a second sampling rate may be determined based (at least in part) on information external to the service. The second rate may be higher or lower than the first rate. For example, the second sampling rate may be determined by an interaction monitoring server based on the monitoring of suitable conditions and/or attributes throughout the service-oriented system, Paragraph 51; sampling policies (including sampling rates) may be distributed from the server 200 to various clients (including services 150A-150N) using distribution/update techniques with client-side reactions. As additional examples, sampling rates may be changed using client-side responses to metric queries or peer-based communication between members of a host class (generate a request), Paragraph 43)
transmit the request; (Hitchcock et al., As shown in 615, the second sampling rate may be assigned to the service (transmit the request), Paragraph 52; sampling policies (including sampling rates) may be distributed from the server 200 to various clients (including services 150A-150N) using distribution/update techniques with client-side reactions. As additional examples, sampling rates may be changed using client-side responses to metric queries or peer-based communication between members of a host class (transmit the request), Paragraph 43)
and set the sampling rate to the reduced sampling rate. (Hitchcock et al., As shown in 615, the second sampling rate may be assigned to the service (set the sampling rate), Paragraph 52)
Hitchcock et al. and De Rosa et al. do not disclose:
receive an approval to set the sampling rate
However, Obaidi et al. disclose:
receive an approval to set the sampling rate (Examples of adjustments that may require approval by the user 304 before implementing reducing the sampling rate of an audio call from 88.2 kilohertz to 44.1 kilohertz when the computing device 306 includes audio equipment that is capable of processing the audio sampled at the higher rate, Paragraph 86)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Obaidi et al. into the teaching of Hitchcock et al. and De Rosa et al. to include receiving an approval to set the sampling rate in order to give a user greater control over the adjusting of sampling rates and/or to allow a user to verify that appropriate adjustments to sampling rates are being implemented.
Claim 12 is a system claim corresponding to the method claim above (Claim 5) and, therefore, is rejected for the same reasons set forth in the rejection of Claim 5.
Claim 19 is a non-transitory computer readable medium claim corresponding to the method claim above (Claim 5) and, therefore, is rejected for the same reasons set forth in the rejection of Claim 5.
Allowable Subject Matter
Claims 4, 6-7, 11, 13-14, 18 and 20 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.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Mahato et al. (US 2025/0138821) disclose optimizing telemetry volume.
Harikrishnan et al. (US 2020/0358674) discloses dynamic determination of data traffic sampling policy in a network visibility appliance.
Altman et a. (US 2017/0168914) discloses rule-based adaptive monitoring of application performance.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LANNY N UNG whose telephone number is (571)270-7708. The examiner can normally be reached Mon-Thurs 6am-4pm.
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/LANNY N UNG/ Primary Examiner, Art Unit 2197
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