What a cloud-native approach to RPA could mean to your business – TechNative
More and more companies are relying on Robotic Process Automation (RPA)
According to Gartner, this is the fastest growing business software market. According to Gartner, sales in 2018 will increase 63.1% to USD 846 million. RPA software revenue is expected to reach $ 1.3 billion in 2019.
Despite these remarkable numbers, we have not yet reached the peak where this emerging technology that has the power to transform global businesses can lead businesses and a broader society. However, the key to leveraging this transformative technology lies in the company’s ability to blend it with the human workforce. IDG’s Future of Work survey found that “86% of executives surveyed stated that human work, AI systems and robot automation must be well integrated by 2020”. Only 12% of executives said their companies are doing this really well today. ‘”
The technology needs to be more widely accessible and easily scalable to increase RPA adoption. This allows non-technical business users to create their own function-specific software bots. It must benefit from the integrated artificial intelligence and enable an intelligent RPA platform that is more intuitive to use and more powerful.
It is crucial that RPA is available through various delivery channels. According to the CompTIA report “Trends in Cloud Computing” from 2018, almost half of all companies state that 31% to 60% of their IT systems are based in the cloud. Given the cost and versatility benefits the cloud offers, it is no shock that “81% of organizations say the cloud has significantly improved or moderately improved their automation efforts”. Organizations are clearly looking for ways to increase efficiency and get the most out of the cloud.
When you put all of these business needs together, i.e. RPA enhanced by AI and available to anyone with access to the web, a single solution emerges: a cloud-native intelligent RPA platform that is easy to access, use, and scale . and works with all applications, whether locally (within the company, on the desktop or a server) or in the cloud.
Cloud-native: Designed to optimize cloud technology
What exactly does “cloud-native” mean? According to the Cloud Native Computing Foundation, the term means that the entire application – from the control plane to the data plane from top to bottom – is designed to take full advantage of the capabilities of the cloud.
Cloud-native applications use complete functional units that are packaged in containers (e.g. Kubernetes) and provided as microservices (collections of loosely coupled, independent services) in an elastic cloud infrastructure through agile DevOps processes and continuous delivery workflows.
In a nutshell, cloud-native is much more than just virtualizing your on-premises application and delivering it via the cloud. If you get it right, you will have to design, implement, deploy, and operate your applications from scratch.
RPA providers have traditionally built their applications for on-premise deployment and, in response to demand for the cloud, moved their on-premises software to the cloud unchanged. This is colloquially referred to as “cloud-washed” architecture and thus leaves the hassle of providing and maintaining traditional software and infrastructure – but none of the many advantages of a cloud-native architecture.
A little help from above
The company’s affinity for cloud computing is traditionally not reflected in the RPA industry. That is, until now – with the world’s first cloud-native RPA platform, we’re offering companies worldwide the benefits of cloud-native, intelligent RPA deployments.
For business users, cloud-native RPA acts as a self-service technology that can be accessed from anywhere via a web-based graphical interface. With a single click or drag-and-drop motion, users can automate those parts of a job that don’t require human creativity, problem-solving skills, empathy, or judgment.
Just like with common SaaS apps (Software-as-a-Service), users can create what they need via an intuitive web interface in the browser. Many common bots don’t require coding. There is no need to install and manage large client downloads or save commands. Automation and processes are made available via drag-and-drop functions and flow charts.
Since there is no software client, IT does not have to interfere. There are no infrastructure management costs and the total cost of ownership (TCO) is significantly reduced.
From an IT perspective, the software is always up to date – there is no need to perform intrusive upgrades on all client computers every time the vendor releases new features or fixes. In addition, continuous integration, continuous delivery, and continuous delivery methods ensure that the latest RPA technology is seamlessly deployed without disruption.
Finally, an ideal RPA platform allows customers to be natively deployed in the cloud, on-premises, or in a hybrid mode where the data is local while the orchestration is in the cloud.
Because the same software stack runs both in the cloud and on-premises, developers don’t have to rebuild their bots when working in a hybrid environment, as many organizations are used to these days. This means that intelligent automation can be provided seamlessly from local to the entire cloud without additional administration costs or complexity.
Everything else is legacy
Cloud-native architecture is radically changing the way modern organizations think about developing, deploying, and managing applications. Cloud-native RPA, which executes and coordinates processes and workflows within a company, is the next piece of the intelligent automation puzzle for companies serious about taking advantage of RPA.
The benefits of cloud-native architectures extend across the board – in terms of scalability, management, security, cost, and easy access – while providing a great experience for all users.
About the author
Prince Kohli, CTO at Automation Anywhere. Extensive and diverse experience building products and teams for cloud computing, enterprise software, network transportation, systems, and security. Founded and managed startups in high-growth organizations with successful exits. Have led extremely large and very small teams. I’ve played a variety of leadership roles, both product and business oriented. Doctorate in computer science with a focus on distributed systems.
Selected image: © Peshkova