Home How RPA Works in the Cloud, Its Deployment Model, and Governance

How RPA Works in the Cloud, Its Deployment Model, and Governance

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As interest grows in automation technology, RPA seeks to move these bots from desktop computers to the cloud. RPA in the cloud could simplify the infrastructure, improve scalability and provide better integration with other cloud applications. Cloud providers are seeing the benefits of RPA and are acting accordingly. Recently, Microsoft revamped its Power Automate tooling for the cloud and Google invested in Automation Anywhere, one of the leading RPA vendors. Additionally, all the major RPA vendors have been busy refactoring their offerings to run more efficiently in the cloud. Let’s learn how RPA works in the cloud, its deployment model, and the governance aspect.

How RPA works in the cloud
According to Maurice Dubey, the author of “
Adopting a Digital Workforce“, in the cloud, RPA can take advantage of cloud-native architectures, security models, and scalability more efficiently than it can on desktop or on-premises servers. Designing the technology, design approval, security reviews and the actual establishment of RPA platforms can be a major cause of delays when kicking off a digital workforce program in a larger organization – but the cloud option reduces those delays significantly.

Amardeep Modi, practice director at Everest Group, adds: “With architectures built on containerized microservices and serverless infrastructure, cloud RPA provides better scalability.” Containers reduce the time required for configuration and setup, as well as simplify auto-scalability without manual intervention. This lowers resource utilization since IT teams can scale up and down microservices’ underlying RPA capabilities independently, rather than the traditional approach of replicating the whole servers. These factors can lead to a lower total cost of ownership.

Deployment model
RPA infrastructure can be dynamically scaled up in the appropriate cloud platform to be closer to other applications. This reduces the burden on IT staff that had to traditionally manage physical servers. All the RPA vendors have created cloud-specific automations that improve the provisioning and management bots on the cloud.

For example, the Blue Prism RPA platform currently supports deployments on AWS, Google Cloud Platform, Microsoft Azure, IBM, Oracle Cloud Infrastructure, and Salesforce AppExchange. It also enables IT teams to integrate bots into cloud-native services, such as cognitive services and productivity applications.

Governance
Cloud RPA also allows enterprises to change the way they govern automations, even for ones that automate the desktop UI of an application running on a local PC. This centralizes administration and governance so that administrators get greater visibility into everything that is created and run by users in the organization. Also, IT leaders need to ensure governance is implemented appropriately.

“By giving RPA to citizen developers, we may end up with the Microsoft Access scenario where organizations’ IT departments ended up having to support a lot of poorly designed and developed Access solutions, some of which ended up managing mission-critical aspects of their business,” Dubey said. He believes that baking some of the governance capabilities into cloud RPA could help reduce this risk.

Future

Deloitte’s Krugar predicts that demand for cloud RPA will grow faster as more organizations move to cloud-native applications in general. This acceleration will be fueled by independent and professional developers creating and sharing automations through the cloud.

In the video below, Deloitte shares how it has cultivated the tools and capabilities needed to help enterprises accelerate their migration to Automation 360 (as the top tool of Intelligent Automation in the Cloud) and capitalize on the benefits of intelligent automation in the cloud.


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