Configurable metadata-based automation and content classification architecture for cloud-based collaboration platforms
US-2016065627-A1 · Mar 3, 2016 · US
US9535909B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9535909-B2 |
| Application number | US-201314026674-A |
| Country | US |
| Kind code | B2 |
| Filing date | Sep 13, 2013 |
| Priority date | Sep 13, 2013 |
| Publication date | Jan 3, 2017 |
| Grant date | Jan 3, 2017 |
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Scalable architectures, systems, and services are provided herein for generating jobs by applying user-specified rules to events in an action log framework (ALF) stream is disclosed. More specifically, collaboration environments can include features or mechanisms that allow end-users or collaborators to perform a variety of actions such as, for example, file uploads and previews, or collaboration operations such as, for example, task assignment and comments. These actions can be captured or logged by an action log framework and, as described herein, automatically translated into one or more jobs by applying customizable user-specified rules.
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What is claimed is: 1. A computer-implemented method of facilitating event-based automation in a collaborative cloud-based platform involving a front-end system and one or more back-end systems, the method comprising: receiving an event at the front-end system of the collaborative cloud-based platform, wherein the front-end system communicates with client systems via a first network for receiving events via the first network, the one or more back-end systems communicate with the front-end system via a second network, wherein the event is received at the front-end system responsive to an action taken by a collaborator of the collaborative cloud-based platform on a content item stored in the one or more back-end systems of the collaborative cloud-based platform, the one or more back-end systems including one or more jobs manager systems and a rule manager system, the one or more back-end systems supplement the one or more jobs manager systems with additional jobs manager systems in response to detecting an increase in the number of events received at the front end system, wherein the content item comprises electronic content that is remotely accessible to the collaborator via a user device in communication with the collaborative cloud-based platform; and translating the event into one or more job requests by: parsing, by the back-end system, the event to identify event criteria; accessing, by the back-end system, pre-defined rules from a memory in communication with the computer processor; scanning, by the back-end system, the pre-defined rules to select a first pre-defined rule that matches the event criteria; and generating, by the back-end system, a job request associated with the first pre-defined rule. 2. The computer implemented method of claim 1 , wherein scanning the pre-defined rules to select the first pre-defined rule that matches the event criteria further comprises: parsing the first pre-defined rule to identify an associated first condition; and selecting the first pre-defined rule if the first condition matches the event criteria. 3. The computer implemented method of claim 2 , further comprising: identifying a job description associated with the first pre-defined condition, the job description identifying a type of job, wherein the job request associated with the first pre-defined rule indicates the type of job identified by the job description associated with the first pre-defined condition. 4. The computer implemented method of claim 2 , wherein the first pre-defined rule includes multiple conditions each having a corresponding job description. 5. The computer implemented method of claim 1 , wherein the event is initiated via a web application and distributed to the rule manager system via an event load balancer, the rule manager system coupled to the one or more jobs manager systems and the web application. 6. The computer implemented method of claim 1 , wherein the event is associated with an action captured by an action log framework. 7. The computer implemented method of claim 1 , further comprising: batching multiple job requests by a jobs load balancer; and distributing, by the jobs load balancer, the batched job requests to the additional jobs manager systems. 8. The computer implemented method of claim 1 , further comprising: receiving, at an administrator interface of the rule manager system, information defining the first pre-defined rule including a user-defined condition and a user-defined job description, wherein the information for generating the first pre-defined rule includes a condition and a corresponding job description and wherein the condition, when met, triggers generation of a job defined by the corresponding job description. 9. The computer implemented method of claim 1 , wherein the information for generating the first pre-defined rule is described in a Rule Descriptive Language (RDL). 10. The computer implemented method of claim 1 , further comprising: receiving, at an administrator interface of the rule manager system, information defining the first pre-defined rule including a first action associated with the event; and identifying, by the rule manager system, one or more conditions associated with the action and a corresponding job description for each of the one or more conditions. 11. The computer implemented method of claim 1 , wherein the criteria comprises an action type or an enterprise identifier. 12. The computer implemented method of claim 1 , further comprising: distributing, by the rule manager system, jobs to the one or more job manager systems. 13. The computer implemented method of claim 12 , further comprising: generating, by the one or more jobs manager system, a job responsive to the job request. 14. The computer implemented method of claim 13 , further comprising: determining, by the one or more job manager systems, an appropriate queue of multiple queues, wherein each queue is associated with a different worker; and adding, by the one or more jobs manager system, the job to the appropriate queue. 15. The computer implemented method of claim 14 , wherein determining the appropriate queue is based on a type of the job. 16. The computer implemented method of claim 13 , wherein the system is further configured for maintaining a status of the job. 17. The computer implemented method of claim 13 , wherein the system is further configured for: persistently storing, by the one or more jobs manager system, the jobs; and responsive to the storing, sending, by the one or more jobs manager system, an acknowledgment of the jobs to the rule manager system. 18. The computer implemented method of claim 1 , wherein the back-end system is configured to supplement the rule manager system with additional rule manager systems in response to detecting an increase in the number of user-specified rules. 19. A distributed computing collaboration system for facilitating event-based automation in a collaborative cloud-based platform, the system comprising: one or more processors associated with a front-end system and a back-end system, wherein the front-end system communicates with client systems via a first network for receiving events via the first network, wherein the back-end system communicates with the front-end system via a second network, the back-end system including one or more jobs manager systems and a rule manager system, wherein the back-end system supplements the one or more jobs manager systems with additional jobs manager systems in response to detecting an increase in the number of events received at the front end system; an interface receiving an event responsive to an action taken by a collaborator of the collaborative cloud-based platform on a content item stored in the back-end system of the collaborative cloud-based platform, wherein the content item comprises electronic content that is remotely accessible to the collaborator via a user device in communication with the collaborative cloud-based platform; and a memory unit having instructions stored thereon which, when executed by the one or more processors, cause the collaboration system to translate the event into one or more job requests by: parsing, by the back-end system, the event to identify event criteria; accessing, by the back-end system, pre-defined rules from a memory in communication with the one or more processors; scanning, by the back-end system, the pre-defined rules to select a first pre-defined rule that matches the event criteria; and generating a job requ
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