Engine for modeling and executing custom business processes

• US 10,445,680 B2
• Filed: 02/02/2017
• Issued: 10/15/2019
• Est. Priority Date: 02/02/2017
• Status: Active Grant

• Current Assignee: Okta Incorporated
• Original Assignee: Azuqua, Inc. (Okta Incorporated)
• Inventors: Hasija, Nikhil, Unger, Craig Howard, Embke, Alec James
• Primary Examiner(s): Knox, Tyler W
• Application Number:
  US15/423,508
• Publication Number:
  US 20180218295A1
• Time in Patent Office: 985 Days
• CPC Class Codes: G06F 8/10 Requirements analysis; Specification techniques
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling

Abstract

Embodiments are directed towards managing online computer services to create custom business processes. A visualization model representing a business process may be provided. If the visualization model a modeling engine may produce a flow model from the visualization model. A flow model may be provided based on the visualization model, such that the flow model includes flow nodes and edges associating the flow nodes. A control model that is overlaid on the flow model may be provided, such that the control model may be arranged to share the flow nodes and the edges of the flow model. A data model that is overlaid on the flow model may be provided. The data model may be arranged to include one or more data model edges. The flow model may be provided to an executive engine that executes the flow model using one or more execution engines.

Claims

1. A method for managing online computer services using a network computer that performs actions comprising:

instantiating a visualization of a visualization model of a process that includes a plurality of card user-interfaces that are arranged for user display and user interaction based on the visualization model; and

instantiating a modeling engine that employs the visualization model to perform further actions, including;

providing a flow model based on the visualization model that is arranged for one or more of processing or data modeling, wherein the flow model includes two or more flow nodes and one or more edges that associate one or more multi-directional flow fields as both inputs and outputs of the one or more flow nodes;

providing a control model overlaid on the flow model, wherein the control model shares the one or more flow nodes and the one or more edges;

providing a data model overlaid on the flow model that includes one or more data model edges, wherein the data model shares the one or more flow nodes and at least a portion of the one or more edges, and wherein the data model and the control model that are overlaid on the flow model share a display of a same topology for laying out the one or more flow nodes and the at least portion of the one or more edges, wherein each of the one or more edges separately associated with just the control model or the data model are presented differently in the display of the same topology;

employing geo-location information provided by a global positioning systems (GPS) device at a client computer to determine one or more features that are included in the visual presentation to improve a user'"'"'s understanding of the plurality of card interfaces for the user display and the user interaction, wherein these features include one or more of time zones, languages, currencies, or calendar formatting that is displayed to the user of the client computer when the client computer is located at a particular geo-location;

associating one or more data transformation rules with one or more of the one or more data model edges, wherein the one or more data edges are associated with a flow node that produces data and another flow node that consumes data; and

configuring and arranging a memory to store the flow model, the data model, and the control model; and

instantiating an executive engine to perform actions including;

executing that executes the flow model using one or more execution engines, wherein the executive engine selects the one or more execution engines based on one or more of heuristics to identify an execution engine that has access to enough resources to handle a load or binding an operation of the flow model to a particular execution engine for secure execution;

in response to discovery of one or more errors in the flow model, performing actions, comprising;

suspending each task associated with the flow model and storing context information associated with the flow model;

partitioning the flow model into one or more broken partitions associated with the one or more discovered errors and one or more working partitions non-associated with the one or more discovered errors, wherein the one or more broken partitions are assigned to an error task queue, and wherein the one or more working partitions are assigned to a task queue; and

resuming execution of the flow model; and

employing a hardware security module, installed in the network computer, to provide tamper resistant safeguards for generation and management of cryptographic information used for secure communication over a network.

2. The method of claim 1, further comprising:

associating field type information with one or more fields of one or more of the plurality of card user-interfaces; and

employing the modeling engine to modify the data model to include data transformation rules that correspond to the field type information.

3. The method of claim 1, further comprising:

traversing the visualization model to select one or more visualization model nodes associated with the plurality of card user-interfaces; and

transforming the one or more visualization model nodes into the one or more flow nodes.

4. The method of claim 1, further comprising, modifying the control model by associating one or more retry policies with the one or more flow nodes, wherein the one or more retry policies define a maximum number of automatic retries for one or more flow tasks associated with the one or more flow nodes.

5. The method of claim 1, further comprising, modifying the control model by associating one or more error handling flow models with the one or more flow nodes, wherein the one or more error handling flow models define a separate process for handling one or more discovered errors.

6. The method of claim 1, further comprising, when the visualization model references one or more embedded flow models, associating the one or more embedded flow models with the flow model, wherein the one or more embedded flow models is linked to one or more of the one or more flow nodes.

7. The method of claim 1, wherein providing the flow model based on the visualization model, further comprises:

providing one or more section attributes based on section information included in the visualization model; and

associating the one or more section attributes with one or more of the one or more flow nodes based on the section information.

8. A system for managing online computer services, comprising:

a network computer, comprising;

a transceiver that communicates over the network;

a memory that stores at least instructions; and

one or more processor devices that execute instructions that perform actions, including;

instantiating a visualization engine to provide a visualization of a visualization model of a process that includes a plurality of card user-interfaces that are arranged for user display and user interaction based on the visualization model; and

instantiating a modeling engine that employs the visualization model to perform further actions, including;

providing a flow model based on the visualization model that is arranged for one or more of processing or data modeling, wherein the flow model includes two or more flow nodes and one or more edges that associate one or more multi-directional flow fields as both inputs and outputs of the one or more flow nodes;

providing a control model overlaid on the flow model, wherein the control model shares the one or more flow nodes and the one or more edges;

providing a data model overlaid on the flow model that includes one or more data model edges, wherein the data model shares the one or more flow nodes and at least a portion of the one or more edges, and wherein the data model and the control model that are overlaid on the flow model share a display of a same topology that includes the one or more flow nodes and the at least portion of the one or more edges, wherein each of the one or more edges separately associated with just the control model or the data model are presented differently in the display of the same topology;

employing geo-location information provided by a global positioning systems (GPS) device at a client computer to determine one or more features that are included in the visual presentation to improve a user'"'"'s understanding of the plurality of card interfaces for the user display and the user interaction, wherein these features include one or more of time zones, languages, currencies, or calendar formatting that is displayed to the user of the client computer when the client computer is located at a particular geo-location;

associating one or more data transformation rules with one or more of the one or more data model edges, wherein the one or more data edges are associated with a flow node that produces data and another flow node that consumes data; and

configuring and arranging a memory to store the second flow model, the data model, and the control model; and

instantiating an executive engine to perform actions including;

executing that executes the flow model using one or more execution engines, wherein the executive engine selects the one or more execution engines based on one or more of heuristics to identify an execution engine that has access to enough resources to handle a load or binding an operation of the flow model to a particular execution engine for secure execution;

in response to discovery of one or more errors in the flow model, performing actions, comprising;

 

suspending each task associated with the flow model and storing context information associated with the flow model;

 

partitioning the flow model into one or more broken partitions associated with the one or more discovered errors and one or more working partitions non-associated with the one or more discovered errors, wherein the one or more broken partitions are assigned to an error task queue, and wherein the one or more working partitions are assigned to a task queue; and

 

resuming execution of the flow model; and

employing a hardware security module, installed in the network computer, to provide tamper resistant safeguards for generation and management of cryptographic information employed for secure communication over a network; and

the client computer, comprising;

the GPS device;

a client computer transceiver that communicates over the network;

a client computer memory that stores at least instructions; and

one or more processor devices that execute instructions that perform actions, including;

displaying the visualization model in the visualization presentation to the user.

9. The system of claim 8, further comprising:

associating field type information with one or more fields of one or more of the plurality of card user-interfaces; and

employing the modeling engine to modify the data model to include data transformation rules that correspond to the field type information.

10. The system of claim 8, further comprising:

traversing the visualization model to select one or more visualization model nodes associated with the plurality of card user-interfaces; and

transforming the one or more visualization model nodes into the one or more flow nodes.

11. The system of claim 8, wherein the one or more network computer processor devices execute instructions that perform actions, further comprising, modifying the control model by associating one or more retry policies with the one or more flow nodes, wherein the one or more retry policies define a maximum number of automatic retries for one or more flow tasks associated with the one or more flow nodes.

12. The system of claim 8, wherein the one or more network computer processor devices execute instructions that perform actions, further comprising, modifying the control model by associating one or more error handling flow models with the one or more flow nodes, wherein the one or more error handling flow models define a separate process for handling one or more discovered errors.

13. The system of claim 8, wherein the one or more network computer processor devices execute instructions that perform actions, further comprising, when the visualization model references one or more embedded flow models, associating the one or more embedded flow models with the flow model, wherein the one or more embedded flow models is linked to one or more of the one or more flow nodes.

14. The system of claim 8, wherein the one or more network computer processor devices execute instructions that perform actions, wherein providing the flow model based on the visualization model, further comprises:

providing one or more section attributes based on section information included in the visualization model; and

associating the one or more section attributes with one or more of the one or more flow nodes based on the section information.

15. A processor readable non-transitory storage media that includes instructions for managing online computer services, wherein execution of the instructions by one or more hardware processors performs actions, comprising:

instantiating a visualization engine to provide a visualization of a visualization model of a process that includes a plurality of card user-interfaces that are arranged for user display and user interaction based on the visualization model; and

instantiating a modeling engine that employs the visualization model to perform further actions, including;

providing a flow model based on the visualization model that is arranged for one or more of processing or data modeling, wherein the flow model includes two or more flow nodes and one or more edges that associate one or more multi-directional flow fields as both inputs and outputs of the one or more flow nodes;

providing a control model overlaid on the flow model, wherein the control model shares the one or more flow nodes and the one or more edges;

providing a data model overlaid on the flow model that includes one or more data model edges, wherein the data model shares the one or more flow nodes and at least a portion of the one or more edges, and wherein the data model and the control model that are overlaid on the flow model share a display of a same topology that includes the one or more flow nodes and the at least portion of the one or more edges, wherein each of the one or more edges separately associated with just the control model or the data model are presented differently in the display of the same topology;

employing geo-location information provided by a global positioning systems (GPS) device at a client computer to determine one or more features that are included in the visual presentation to improve a user'"'"'s understanding of the plurality of card interfaces for the user display and the user interaction, wherein these features include one or more of time zones, languages, currencies, or calendar formatting that is displayed to the user of the client computer when the client computer is located at a particular geo-location;

associating one or more data transformation rules with one or more of the one or more data model edges, wherein the one or more data edges are associated with a flow node that produces data and another flow node that consumes data; and

configuring and arranging a memory to store the flow model, the data model, and the control model; and

instantiating an executive engine to perform actions including;

executing that executes the flow model using one or more execution engines, wherein the executive engine selects the one or more execution engines based on one or more of heuristics to identify an execution engine that has access to enough resources to handle a load or binding an operation of the flow model to a particular execution engine for secure execution;

in response to discovery of one or more errors in the flow model, performing actions, comprising;

suspending each task associated with the flow model and storing context information associated with the flow model;

partitioning the flow model into one or more broken partitions associated with the one or more discovered errors and one or more working partitions non-associated with the one or more discovered errors, wherein the one or more broken partitions are assigned to an error task queue, and wherein the one or more working partitions are assigned to a task queue; and

resuming execution of the flow model; and

employing a hardware security module, installed in the network computer, to provide tamper resistant safeguards for generation and management of cryptographic information employed for secure communication over a network.

16. The media of claim 15, further comprising:

associating field type information with one or more fields of one or more of the plurality of card user-interfaces; and

employing the modeling engine to modify the data model to include data transformation rules that correspond to the field type information.

17. The media of claim 15, further comprising:

traversing the visualization model to select one or more visualization model nodes associated with the plurality of card user-interfaces; and

transforming the one or more visualization model nodes into the one or more flow nodes.

18. The media of claim 15, further comprising, modifying the control model by associating one or more retry policies with the one or more flow nodes, wherein the one or more retry policies define a maximum number of automatic retries for one or more flow tasks associated with the one or more flow nodes.

19. The media of claim 15, further comprising, modifying the control model by associating one or more error handling flow models with the one or more flow nodes, wherein the one or more error handling flow models define a separate process for handling one or more discovered errors.

20. The media of claim 15, further comprising, when the visualization model references one or more embedded flow models, associating the one or more embedded flow models with the flow model, wherein the one or more embedded flow models is linked to one or more of the one or more flow nodes.

21. The media of claim 15, wherein providing the flow model based on the visualization model, further comprises:

providing one or more section attributes based on section information included in the visualization model; and

associating the one or more section attributes with one or more of the one or more flow nodes based on the section information.

22. A network computer for managing online computer services, comprising:

a transceiver that communicates over the network;

a memory that stores at least instructions; and

one or more processor devices that execute instructions that perform actions, including;

instantiating a visualization engine to provide a visualization of a visualization model of a process that includes a plurality of card user-interfaces that are arranged for user display and user interaction based on the visualization model; and

instantiating a modeling engine that employs the visualization model to perform further actions, including;

providing a flow model based on the visualization model that is arranged for one or more of processing or data modeling, wherein the flow model includes two or more flow nodes and one or more edges that associate one or more multi-directional flow fields as both inputs and outputs of the one or more flow nodes;

providing a control model overlaid on the flow model, wherein the control model shares the one or more flow nodes and the one or more edges;

providing a data model overlaid on the flow model that includes one or more data model edges, wherein the data model shares the one or more flow nodes and at least a portion of the one or more edges, and wherein the data model and the control model that are overlaid on the flow model share a display of a same topology that includes the one or more flow nodes and the at least portion of the one or more edges, wherein each of the one or more edges separately associated with just the control model or the data model are presented differently in the display of the same topology;

employing geo-location information provided by a global positioning systems (GPS) device at a client computer to determine one or more features that are included in the visual presentation to improve a user'"'"'s understanding of the plurality of card interfaces for the user display and the user interaction, wherein these features include one or more of time zones, languages, currencies, or calendar formatting that is displayed to the user of the client computer when the client computer is located at a particular geo-location;

associating one or more data transformation rules with one or more of the one or more data model edges, wherein the one or more data edges are associated with a flow node that produces data and another flow node that consumes data; and

configuring and arranging a memory to store the flow model, the data model, and the control model; and

instantiating an executive engine to perform actions including;

executing that executes the flow model using one or more execution engines, wherein the executive engine selects the one or more execution engines based on one or more of heuristics to identify an execution engine that has access to enough resources to handle a load or binding an operation of the flow model to a particular execution engine for secure execution;

in response to discovery of one or more errors in the flow model, performing actions, comprising;

suspending each task associated with the flow model and storing context information associated with the flow model;

partitioning the flow model into one or more broken partitions associated with the one or more discovered errors and one or more working partitions non-associated with the one or more discovered errors, wherein the one or more broken partitions are assigned to an error task queue, and wherein the one or more working partitions are assigned to a task queue; and

resuming execution of the flow model; and

employing a hardware security module, installed in the network computer, to provide tamper resistant safeguards for generation and management of cryptographic information employed for secure communication over a network.

23. The network computer of claim 22, further comprising:

associating field type information with one or more fields of one or more of the plurality of card user-interfaces; and

employing the modeling engine to modify the data model to include data transformation rules that correspond to the field type information.

24. The network computer of claim 22, further comprising:

traversing the visualization model to select one or more visualization model nodes associated with the plurality of card user-interfaces; and

transforming the one or more visualization model nodes into the one or more flow nodes.

25. The network computer of claim 22, further comprising, modifying the control model by associating one or more retry policies with the one or more flow nodes, wherein the one or more retry policies define a maximum number of automatic retries for one or more flow tasks associated with the one or more flow nodes.

26. The network computer of claim 22, further comprising, modifying the control model by associating one or more error handling flow models with the one or more flow nodes, wherein the one or more error handling flow models define a separate process for handling one or more discovered errors.

27. The network computer of claim 22, further comprising, when the visualization model references one or more embedded flow models, associating the one or more embedded flow models with the flow model, wherein the one or more embedded flow models is linked to one or more of the one or more flow nodes.

28. The network computer of claim 22, wherein providing the flow model based on the visualization model, further comprises:

providing one or more section attributes based on section information included in the visualization model; and

associating the one or more section attributes with one or more of the one or more flow nodes based on the section information.