DETAILED ACTION
Claims 1-6, 8-17 and 19-22 are pending in this 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 factual inquiries 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 1-4, 15-17 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Elias et al. (US PGPUB No. 2015/0006693) [hereinafter “Elias”] in view of Shua (US PGPUB No. 2020/0244692) in further view of Agarwal et al. (US PGPUB No. 2020/0204618) [hereinafter “Agarwal”] in further view of Eksten et al. (WO-2013033824-A2) [hereinafter “Eksten”].
As per claim 1, Elias teaches a method comprising: capturing, by a data platform using a heuristic, compute asset data associated with each of a plurality of compute assets deployed within a cloud environment ([0034], capturing health check monitoring data of deployed tools and agents); determining, by the data platform and based on the compute asset data, a condition associated with the plurality of compute assets, wherein the determining the condition comprises determining that an agent is not deployed on a first compute asset included in the plurality of compute assets ([0034], determining that agent is missing from a resource or deployed on the wrong device).
Elias does not explicitly teach capturing, by a data platform using an agentless heuristic, a snapshot representative of a state of compute asset data associated with each of a plurality of compute assets deployed within a cloud environment. Shua teaches capturing, by a data platform using an agentless heuristic, a snapshot representative of a state of compute asset data associated with each of a plurality of compute assets deployed within a cloud environment ([0031], a security system that monitors VM’s on the cloud without using agents including capturing snapshots of the VM’s which represent various states of the VM’s at different times see [0034]).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Elias with the teachings of Shua, capturing, by a data platform using an agentless heuristic, a snapshot representative of a state of compute asset data associated with each of a plurality of compute assets deployed within a cloud environment, wherein an agentless heuristic comprises a serverless function performed without computing resources of the compute assets, to allow for scanning network metrics without the need to distribute dedicated software which could be burdensome to upkeep.
The combination of Elias and Shua does not explicitly teach a serverless function performed without computing resources of the compute assets. Agarwal teaches a serverless function performed without computing resources of the compute assets ([0066] and [0070], serverless functions that don’t have access to underlying resources of host).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Elias and Shua with the teachings of Agarwal, a serverless function performed without computing resources of the compute assets, to provide well known techniques that don’t require the cumbersome aspects of installing agents at servers or other cloud components.
The combination of Elias, Shua and Agarwal does not explicitly teach performing, an agent-based operation with respect to the one or more compute assets, wherein the performing the agent-based operation comprises generating a graph based on the compute asset data. Eksten teaches performing, an agent-based operation with respect to the one or more compute assets ([18], deploying a cloud agent to a user system to manage the resources), wherein the performing the agent-based operation comprises generating a graph based on the compute asset data ([10], wherein the agents receive blueprints and instantiate graphs that represent components, connections and properties).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Elias, Shua and Agarwal with the teachings of Eksten, performing, an agent-based operation with respect to the one or more compute assets, wherein the performing the agent-based operation comprises generating a graph based on the compute asset data, to ensure the assets are quickly and efficiently equipped with necessary software to provide cloud services.
As per claim 2, the combination of Elias, Shua, Agarwal and Eksten teaches the method of claim 1, wherein serverless function comprises a programmatic function for performing a single purpose (Agarwal; Abstract and [0007], serverless function as specific program code executed to perform a service).
As per claim 3, the combination of Elias, Shua, Agarwal and Eksten teaches the method of claim 1, wherein the determining the condition associated the plurality of compute assets further comprises determining whether the compute asset data includes an anomaly (Shua; Abstract and [0022], scanning for vulnerabilities in various assets on virtual cloud assets).
As per claim 4, the combination of Elias, Shua, Agarwal and Eksten teaches the method of claim 1, wherein the compute asset data comprises one or more of: a configuration of the compute assets (Elias; [0006], tracking configuration of the various components in an IT environment), a type of the compute assets, a number of the compute assets (Examiner Note: a type and number of assets are optional features but a possible citation will be included to expedite prosecution) (Elias; [0006], all relevant information about components in an IT environment would include type and number), a customer identification of the one or more compute assets (Examiner Note: this is an optional feature but a possible citation will be included to expedite prosecution) (Elias; [0032], customer designation of IT devices), an identity of a user accessing the one or more compute assets (Examiner Note: this is an optional feature but a possible citation will be included to expedite prosecution) (Elias; [0030], customer identity included in SLA agreements and other contracts with services), a service associated with the one or more compute assets (Examiner Note: this is an optional feature but a possible citation will be included to expedite prosecution) (Elias; [0030], services provided to customer included in contracts), an action performed by the one or more compute assets (Examiner Note: this is an optional feature but a possible citation will be included to expedite prosecution) (Elias; [0033], management components include various operations performed by system), a response from the one or more compute assets (Examiner Note: this is an optional feature but a possible citation will be included to expedite prosecution) (Elias; [0009], responses can be from policy definitions), a size of the one or more compute assets (Examiner Note: a size of an asset is an optional feature but a possible citation will be included to expedite prosecution) (Elias; [0006], all relevant information about components in an IT environment would include size), a time associated with the one or more compute assets (Examiner Note: this is an optional feature but a possible citation will be included to expedite prosecution) (Elias; [0064], time of validation of consistency for components), or a keyword associated with the one or more compute assets (Examiner Note: this is an optional feature but a possible citation will be included to expedite prosecution) (Elias; [0030], contracts can contain keywords associated with components).
As per claim 8, the combination of Elias, Shua, Agarwal and Eksten teaches the method of claim 1, wherein the agent-based operation further comprises one or more of: deploying an agent to the compute asset or providing a notification to deploy the agent to the computer asset (Eksten; [18], deploying a cloud agent to user system).
As per claim 15, the substance of the claimed invention is identical or substantially similar to that of claim 1. Accordingly, this claim is rejected under the same rationale.
As per claim 16, the substance of the claimed invention is identical or substantially similar to that of claim 2. Accordingly, this claim is rejected under the same rationale.
As per claim 17, the substance of the claimed invention is identical or substantially similar to that of claim 3. Accordingly, this claim is rejected under the same rationale.
As per claim 19, the substance of the claimed invention is identical or substantially similar to that of claim 8. Accordingly, this claim is rejected under the same rationale.
As per claim 20, the substance of the claimed invention is identical or substantially similar to that of claim 1. Accordingly, this claim is rejected under the same rationale.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Elias, Shua, Agarwal and Eksten in further view of Chen (CN-102750184-A).
As per claim 5, the combination of Elias, Shua, Agarwal and Eksten teaches the method of claim 1.
The combination of Elias, Shua, Agarwal and Eksten does not explicitly teach ingesting the compute asset data from the cloud environment and storing the compute asset data in a data store. Chen teaches ingesting the compute asset data from the cloud environment and storing the compute asset data in a data store (Abstract, collecting resource data across the cloud for classification and identification and storing in a database).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Elias, Shua, Agarwal and Eksten with the teachings of Chen, ingesting the compute asset data from the cloud environment and storing the compute asset data in a data store, to encapsulate cloud service information for easy storage and analysis.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Elias, Shua, Agarwal, Eksten and Chen in further view of Turner et al. (US PGPUB No. 2015/0213463) [hereinafter “Turner”].
As per claim 6, the combination of Elias, Shua, Agarwal, Eksten and Chen teaches the method of claim 5.
The combination of Elias, Shua, Agarwal, Eksten and Chen does not explicitly teach wherein the determining the condition associated with the one or more compute assets comprises querying the data store using a query created using a query language associated with the data platform. Turner teaches wherein the determining the condition associated with the one or more compute assets comprises querying the data store using a query created using a query language associated with the data platform ([0035], SQL database used to search events and data).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Elias, Shua, Agarwal, Eksten and Chen with the teachings of Turner, wherein the determining the condition associated with the one or more compute assets comprises querying the data store using a query created using a query language associated with the data platform, to encapsulate cloud service information for easy storage, analysis and querying.
Claims 9, 10, 11, 13, 21 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Elias, Shua, Agarwal, and Eksten in further view of Apostolopoulos (US PGPUB No. 2018/0219888).
As per claim 9, the combination of Elias, Shua, Agarwal and Eksten teaches the method of claim 8.
The combination of Elias, Shua, Agarwal and Eksten does not explicitly teach wherein the prioritizing the compute asset is based on an anomaly of the compute asset identified in a graph of the compute asset data. Apostolopoulos teaches wherein the prioritizing the compute asset is based on an anomaly of the compute asset identified in a graph of the compute asset data (Abstract, storing anomaly source events in a graph database).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Elias, Shua, Agarwal and Eksten with the teachings of Apostolopoulos, wherein the prioritizing the compute asset is based on an anomaly of the compute asset identified in a graph of the compute asset data, to provide a more relationship based storage option which can provide for more nuanced querying for users.
As per claim 10, Elias, Shua, Agarwal and Eksten teaches the method of claim 1.
The combination of Elias, Shua, Agarwal and Eksten does not explicitly teach determining whether the compute asset data includes an anomaly. Apostolopoulos teaches determining whether the compute asset data includes an anomaly (Abstract, storing anomaly source events in a database).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Elias, Shua, Agarwal and Eksten with the teachings of Apostolopoulos, determining whether the compute asset data includes an anomaly, to extend the tracking of data to security anomalies to improve network integrity and confidence.
As per claim 11, the combination of Elias, Shua, Agarwal, Eksten and Apostolopoulos teaches the method of claim 10, further comprising performing an anomaly-based operation when the compute asset data includes an anomaly (Apostolopoulos; [0035] and [0101], response action to detection of anomaly).
As per claim 13, the combination of Elias, Shua, Agarwal and Eksten teaches the method of claim 1.
The combination of Elias, Shua, Agarwal and Eksten does not explicitly teach the graph comprising a plurality of nodes connected by a plurality of edges, wherein each node of the plurality of nodes represents a logical entity from the compute asset data and each edge of the plurality of edges represents a behavioral relationship between nodes connected by the edge. Apostolopoulos teaches the graph comprising a plurality of nodes connected by a plurality of edges (Abstract, storing anomaly source events in a graph database with nodes and edges see [0194]), wherein each node of the plurality of nodes represents a logical entity from the compute asset data ([0099], nodes represent entity of focus) and each edge of the plurality of edges represents a behavioral relationship between nodes connected by the edge ([0135], edge represents a relationship between two entities).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Elias, Shua, Agarwal and Eksten with the teachings of Apostolopoulos, the graph comprising a plurality of nodes connected by a plurality of edges, wherein each node of the plurality of nodes represents a logical entity from the compute asset data and each edge of the plurality of edges represents a behavioral relationship between nodes connected by the edge, to provide a more relationship based storage option which can provide for more nuanced querying for users.
As per claim 21, the substance of the claimed invention is identical or substantially similar to that of claim 9.
As per claim 22, the substance of the claimed invention is identical or substantially similar to that of claim 10.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Elias, Shua, Agarwal and Eksten in further view of Bagwell et al. (US PGPUB No. 2010/0274601) [hereinafter “Bagwell”].
As per claim 12, the combination of Elias, Shua, Agarwal and Eksten teaches the method of claim 1 and agent-based operations see above rejection of claim 1.
The combination of Elias, Shua, Agarwal and Eksten does not explicitly teach deleting the compute asset data after the agent-based operation has been performed. Bagwell teaches deleting the compute asset data after an operation has been performed ([0090], a delete action executed after an alert is sent).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Elias, Shua, Agarwal and Eksten with the teachings of Bagwell, deleting the compute asset data after the agent-based operation has been performed, to remove logged event data that may be no longer necessary or may be harmful if not deleted.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Elias, Shua, Agarwal and Eksten in further view of Kushwaha et al. (US PGPUB No. 2009/0187929) [hereinafter “Kushwaha”].
As per claim 14, the combination of Elias, Shua, Agarwal and Eksten teaches the method of claim 1.
The combination of Elias, Shua, Agarwal and Eksten does not explicitly teach wherein the agentless heuristic is used in combination with an agent associated with the data platform and executed within the cloud environment to capture the compute asset data. Kushwaha teaches wherein the agentless heuristic is used in combination with an agent associated with the data platform and executed within the cloud environment to capture the compute asset data ([0019], using a combination of agent and agentless systems for monitoring network data see Abstract and [0007]).
At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Elias, Shua, Agarwal and Eksten with the teachings of Kushwaha, wherein the agentless heuristic is used in combination with an agent associated with the data platform and executed within the cloud environment to capture the compute asset data, to utilize both advantages of well known monitoring systems which can result in a more dynamic flexible data collection.
Response to Arguments
Applicant’s arguments with respect to the rejection of claims 1-6, 8-17 and 19-22 under 35 U.S.C. 103 have been fully considered. In light of the new amendments, two new prior art references have been introduced, Eksten.
To expedite prosecution, Examiner is open to an after-final interview to discuss the novelty of the invention and any claim amendments that will overcome the current rejection and/or place the application in condition for allowance.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Schoening et al. (US PGPUB No. 2015/0356153), Gershaft et al. (US PGPUB No. 2017/0195183), He et al. (US PGPUB No. 2018/0241638), Soni et al. ("Enhancing Coverage Efficiency through Intelligent Agent Deployment in Large-Scale IoT Environment," 2024 2nd International Conference on Advancement in Computation & Computer Technologies (InCACCT), Gharuan, India, 2024, pp. 811-816, doi: 10.1109/InCACCT61598.2024.10551145) all disclose various aspects of the claimed invention including agent and agent monitoring of cloud data environments.
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 PETER C SHAW whose telephone number is (571)270-7179. The examiner can normally be reached Max Flex.
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/PETER C SHAW/Primary Examiner, Art Unit 2493 February 3, 2026