IP Library Granted Patent US 12,223,311
Granted Patent B2
US 12,223,311 · App. 18/433,235 · Granted Feb 11, 2025

Configurable deployment of data science environments

Inventors: Prasad Paravatha (Chicago, IL); Abdul Nafeez Mohammad (Chicago, IL)
Assignee: Discover Financial Services
G06F8/65G06F9/5055
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Quick Facts
Patent No.
US 12,223,311
App. No.
18/433,235
Granted
Feb 11, 2025
Kind
B2
Abstract

An example client device is configured to (i) display an interface for deploying a new data science environment at a computing platform, (ii) receive, via the interface, a user selection of (a) a given data science application from a list of data science applications that is presented by the interface and (b) one or more deployment configuration parameters from a set of deployment configuration parameters that is presented by the interface, (iii) transmit, to the computing platform, a first network-based communication comprising an indication of the user selection of (a) the given data science application and (b) the one or more deployment configuration parameters, and (iv) receive, from the computing platform, a second network-based communication comprising an indication that the new data science environment has been deployed based on the user selection of the (a) the given data science application and (b) the one or more configuration parameters.

Claims (46)

1. A client device comprising:

a network interface;

at least one processor;

at least one non-transitory computer-readable medium; and

program instructions stored on the at least one non-transitory computer-readable medium that, when executed by the at least one processor, cause the client device to:

display an interface for deploying a new data science environment at a computing platform;

receive, via the interface, a user selection of (i) a given data science application from a list of data science applications that is presented by the interface and (ii) one or more deployment configuration parameters from a set of deployment configuration parameters that is presented by the interface;

transmit, to the computing platform, a first network-based communication comprising an indication of the user selection of (i) the given data science application and (ii) the one or more deployment configuration parameters, wherein the first network-based communication causes the computing platform to deploy the new data science environment; and

receive, from the computing platform, a second network-based communication comprising an indication that the new data science environment has been deployed based on the user selection of the (i) the given data science application and (ii) the one or more configuration parameters.

2. The client device of claim 1 , wherein the given data science application corresponds to one or more deployment templates maintained at the computing platform.

3. The client device of claim 2 , wherein each of the one or more deployment templates corresponding to the given data science applications comprises data specifying (i) a respective executable environment package and (ii) a respective set of predefined deployment configuration parameters.

4. The client device of claim 1 , wherein the first network-based communication causes the computing platform to deploy the new data science environment using a given deployment template maintained at the computing platform that is selected based at least in part on the user selection of the given data science application.

5. The client device of claim 1 , wherein the one or more deployment configuration parameters comprise a version of the given data science application for which to deploy the new data science environment.

6. The client device of claim 1 , wherein the one or more deployment configuration parameters comprise a computing resource allocation to use for deploying the new data science environment.

7. The client device of claim 1 , wherein the one or more deployment configuration parameters comprise a given shared workspace to use for the new data science environment.

8. The client device of claim 1 , wherein the presented set of deployment configuration parameters is defined based at least in part on the user selection of the given data science application.

9. The client device of claim 1 , wherein the presented list of data science applications is defined based on a set of user permissions.

10. The client device of claim 1 , further comprising program instructions stored on the at least one non-transitory computer-readable medium that, when executed by the at least one processor, cause the client device to:

access the new data science environment that has been deployed.

11. The client device of claim 1 , further comprising program instructions stored on the at least one non-transitory computer-readable medium that, when executed by the at least one processor, cause the client device to:

receive, from the computing platform, a third network-based communication comprising an indication of a deployment status of the new data science environment; and

present the indication of the deployment status of the new data science environment.

12. The client device of claim 1 , further comprising program instructions stored on the at least one non-transitory computer-readable medium that, when executed by the at least one processor, cause the client device to:

receive a user request to change a deployment status of the new data science environment;

based on receiving the user request, transmit, to the computing platform, a third network-based communication comprising an indication of the user request to change the deployment status of the new data science environment; and

receive, from the computing platform, a fourth network-based communication comprising an indication that the deployment status of the new data science environment has been changed based on the user request.

13. A non-transitory computer-readable medium, wherein the non-transitory computer-readable medium is provisioned with program instructions that, when executed by at least one processor, cause a client device to:

display an interface for deploying a new data science environment at a computing platform;

receive, via the interface, a user selection of (i) a given data science application from a list of data science applications that is presented by the interface and (ii) one or more deployment configuration parameters from a set of deployment configuration parameters that is presented by the interface;

transmit, to the computing platform, a first network-based communication comprising an indication of the user selection of (i) the given data science application and (ii) the one or more deployment configuration parameters, wherein the first network-based communication causes the computing platform to deploy the new data science environment; and

receive, from the computing platform, a second network-based communication comprising an indication that the new data science environment has been deployed based on the user selection of the (i) the given data science application and (ii) the one or more configuration parameters.

14. The non-transitory computer-readable medium of claim 13 , wherein the given data science application corresponds to one or more deployment templates maintained at the computing platform.

15. The non-transitory computer-readable medium of claim 14 , wherein each of the one or more deployment templates corresponding to the given data science applications comprises data specifying (i) a respective executable environment package and (ii) a respective set of predefined deployment configuration parameters.

16. The non-transitory computer-readable medium of claim 13 , wherein the one or more deployment configuration parameters comprise at least one of (i) a version of the given data science application for which to deploy the new data science environment, (ii) a computing resource allocation to use for deploying the new data science environment, or (iii) a given shared workspace to use for the new data science environment.

17. The non-transitory computer-readable medium of claim 13 , wherein the presented set of deployment configuration parameters is defined based at least in part on the user selection of the given data science application.

18. The non-transitory computer-readable medium of claim 13 , wherein the non-transitory computer-readable medium is further provisioned with program instructions that, when executed by at least one processor, cause the client device to:

access the new data science environment that has been deployed.

19. The non-transitory computer-readable medium of claim 13 , wherein the non-transitory computer-readable medium is further provisioned with program instructions that, when executed by at least one processor, cause the client device to:

receive a user request to change a deployment status of the new data science environment;

based on receiving the user request, transmit, to the computing platform, a third network-based communication comprising an indication of the user request to change the deployment status of the new data science environment; and

receive, from the computing platform, a fourth network-based communication comprising an indication that the deployment status of the new data science environment has been changed based on the user request.

20. A method carried out by a client device, the method comprising:

displaying an interface for deploying a new data science environment at a computing platform;

receiving, via the interface, a user selection of (i) a given data science application from a list of data science applications that is presented by the interface and (ii) one or more deployment configuration parameters from a set of deployment configuration parameters that is presented by the interface;

transmitting, to the computing platform, a first network-based communication comprising an indication of the user selection of (i) the given data science application and (ii) the one or more deployment configuration parameters, wherein the first network-based communication causes the computing platform to deploy the new data science environment; and

receiving, from the computing platform, a second network-based communication comprising an indication that the new data science environment has been deployed based on the user selection of the (i) the given data science application and (ii) the one or more configuration parameters.

Assignments (2)
MERGER Recorded Jul 2, 2025
From: DISCOVER FINANCIAL SERVICES
To: CAPITAL ONE FINANCIAL CORPORATION
Reel/Frame 071784/0903 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 30, 2024
From: PARAVATHA, PRASAD; MOHAMMAD, ABDUL NAFEEZ
To: DISCOVER FINANCIAL SERVICES
Reel/Frame 067263/0593 →
Continuity (2)
Continuation 17580264 · Jan 20, 2022
Related Publication 20240176610A1 · May 30, 2024
References Cited (25)
US 9710767B1 · Dietrich et al. · 2017 [cited by applicant]
US 11068254B1 · Gau · 2021 [cited by examiner]
US 20160148115A1 · Sirosh et al. · 2016 [cited by applicant]
US 20160232457A1 · Gray et al. · 2016 [cited by applicant]
US 20170017903A1 · Gray · 2017 [cited by examiner]
US 20170177309A1 · Bar-Or et al. · 2017 [cited by applicant]
US 20170315791A1 · Mascaro et al. · 2017 [cited by applicant]
US 20180004363A1 · Tompkins · 2018 [cited by examiner]
US 20180004784A1 · Tompkins · 2018 [cited by applicant]
US 20180174056A1 · Madison et al. · 2018 [cited by applicant]
US 20180357654A1 · Huang et al. · 2018 [cited by applicant]
US 20190042068A1 · Tompkins · 2019 [cited by applicant]
US 20190171438A1 · Franchitti · 2019 [cited by examiner]
US 20200117434A1 · Biskup et al. · 2020 [cited by applicant]
US 20200364606A1 · Sawant et al. · 2020 [cited by applicant]
US 20210034581A1 · Boven et al. · 2021 [cited by applicant]
US 20210209099A1 · Marsden · 2021 [cited by examiner]
US 20210342725A1 · Marsden et al. · 2021 [cited by applicant]
US 20220043978A1 · Wang et al. · 2022 [cited by applicant]
US 20220076165A1 · Minkin · 2022 [cited by examiner]
Discover Accelerates Analytics and Time-to-Insights Using AWS. Discover. 2020, 8 pages [online], [retrieved online Apr. 7, 2022]. Retrieved from the Internet <URL: https://aws.amazon.com/solutions/case-studies/discover-… [cited by applicant]
Harris et al. Air9 Analytics Environment. Discover. 2019, 21 pages [online], [retrieved online Apr. 7, 2022]. Retrieved from the internet < URL:https://cloud.redhat.com/hubfs/Discover-OpenShift-Commons-Oct28-Final.pdf>. [cited by applicant]
Harris et al. Digital transformation at Discover using AWS Storage. AWS Storage Blog. Apr. 22, 2020, 7 pages [online], [retrieved online Apr. 7, 2022].Retrieved from the Internet <URL: https://aws.amazon.com/blogs/stora… [cited by applicant]
Oppenheim et al. AWS re: Invent AIM 204-S. Discovering the value of a cloud data platform. 2019, 15 pages [online], [retrieved online Apr. 7, 2022]. Retrieved from the Internet: <URL: https://d1.awsstatic.com/events/rei… [cited by applicant]
International Searching Authority. International Search Report and Written Opinion issued in International Application No. PCT/US2022/053127, mailed on Apr. 28, 2023, 10 pages. [cited by applicant]