Autoscaling strategies for robotic process automation
Systems and methods for allocating computing environments for completing an RPA (robotic process automation) workload are provided. A request for completing an RPA workload is received. A number of computing environments to allocate for completing the RPA workload is calculated based on a selected one of a plurality of RPA autoscaling strategies. The calculated number of computing environments is allocated for allocating one or more RPA robots to complete the RPA workload. The computing environments may be virtual machines.
1. A computer-implemented method comprising:
receiving a request for completing an RPA (robotic process automation) workload;
determining a number of computing environments to allocate for completing the RPA workload based on a selected one of a plurality of RPA autoscaling strategies and a number of licensed RPA robots, wherein the plurality of RPA autoscaling strategies comprises a dynamic strategy in which one or more control variables are automatically adjusted based on workload type;
allocating the determined number of computing environments for allocating one or more RPA robots to complete the RPA workload; and
completing the RPA workload by the one or more RPA robots using the allocated number of computing environments.
2. The computer-implemented method of claim 1 , wherein the computing environments comprise virtual machines.
3. The computer-implemented method of claim 1 , wherein the plurality of RPA autoscaling strategies comprises a speed over cost strategy, a balanced strategy, and a cost over speed strategy.
4. The computer-implemented method of claim 1 , wherein the number of computing environments to allocate is determined based on a number of computing environments that would complete the RPA workload, and a maximum number of computing environments that can be created in a pool.
5. The computer-implemented method of claim 1 , wherein the plurality of RPA autoscaling strategies comprises a custom strategy in which a user configures one or more control variables.
6. The computer-implemented method of claim 1 , further comprising:
receiving a selection of the selected RPA autoscaling strategy from a user.
7. The computer-implemented method of claim 1 , further comprising:
automatically selecting the selected RPA autoscaling strategy according to a schedule defining start and end times for applying the selected RPA autoscaling strategy.
8. The computer-implemented method of claim 1 , further comprising:
automatically selecting the selected RPA autoscaling strategy based on a source of the RPA workload.
9. An apparatus comprising:
a memory storing computer instructions; and
at least one processor configured to execute the computer instructions, the computer instructions configured to cause the at least one processor to perform operations of:
receiving a request for completing an RPA (robotic process automation) workload;
determining a number of computing environments to allocate for completing the RPA workload based on a selected one of a plurality of RPA autoscaling strategies and a number of licensed RPA robots, wherein the plurality of RPA autoscaling strategies comprises a dynamic strategy in which one or more control variables are automatically adjusted based on workload type;
allocating the determined number of computing environments for allocating one or more RPA robots to complete the RPA workload; and
completing the RPA workload by the one or more RPA robots using the allocated number of computing environments.
10. The apparatus of claim 9 , wherein the computing environments comprise virtual machines.
11. The apparatus of claim 9 , wherein the plurality of RPA autoscaling strategies comprises a speed over cost strategy, a balanced strategy, and a cost over speed strategy.
12. The apparatus of claim 9 , wherein the number of computing environments to allocate is determined based on a number of computing environments that would complete the RPA workload, and a maximum number of computing environments that can be created in a pool.
13. The apparatus of claim 9 , wherein the plurality of RPA autoscaling strategies comprises a custom strategy in which a user configures one or more control variables.
14. A non-transitory computer-readable medium storing computer program instructions, the computer program instructions, when executed on at least one processor, cause the at least one processor to perform operations comprising:
receiving a request for completing an RPA (robotic process automation) workload;
determining a number of computing environments to allocate for completing the RPA workload based on a selected one of a plurality of RPA autoscaling strategies and a number of licensed RPA robots, wherein the plurality of RPA autoscaling strategies comprises a dynamic strategy in which one or more control variables are automatically adjusted based on workload type;
allocating the determined number of computing environments for allocating one or more RPA robots to complete the RPA workload; and
completing the RPA workload by the one or more RPA robots using the allocated number of computing environments.
15. The non-transitory computer-readable medium of claim 14 , wherein the computing environments comprise virtual machines.
16. The non-transitory computer-readable medium of claim 14 , the operations further comprising:
receiving a selection of the selected RPA autoscaling strategy from a user.
17. The non-transitory computer-readable medium of claim 14 , the operations further comprising:
automatically selecting the selected RPA autoscaling strategy according to a schedule defining start and end times for applying the selected RPA autoscaling strategy.
18. The non-transitory computer-readable medium of claim 14 , the operations further comprising:
automatically selecting the selected RPA autoscaling strategy based on a source of the RPA workload.