Businesses around the world are increasingly employing RPA (Robotic Process Automation) tools to automate their processes, saving time and cost. One would imagine businesses to have achieved maximum optimization when it comes to integrating and delivering these bots. However, many businesses are yet to have complete control over their bots and thereby, realize efficiency when it comes to integration and deployment.
This is where a CI/CD pipeline enters the picture. With CI/CD (Continuous Integration and Continuous Delivery), the bot can be continuously built, integrated, deployed, and delivered. The time that goes into fixing errors also comes down drastically.
The CI/CD pipeline bridges the gaps between development and operational activities while automating a robot delivery process. It does so by automating the build, test, and continuous deployment phases.
Continuous Integration is a software engineering practice employed by developers to ensure simpler building and testing of codes, by automating the tasks involved. While applying continuous integration to RPA, the developers regularly integrate code changes into a central repository. The code is built using the NuGet package, and tests are run and published in the UiPath production server using Orchestrator. With CI teams can detect integration errors quicker, and update codes continually into the codebase.
Continuous Delivery/Deployment is a practice to ensure simpler code packaging and continuous deployment. With CD, teams can configure and package software, like building an RPA bot, and orchestrate continuous deployment at a lower cost. Developers can ensure that added features, configuration changes, bug fixes, and experiments in the bot, reflects in the production server.
A CI/CD pipeline, in a nutshell, is a method to automate any software delivery process. While deploying a bot, it's crucial to ensure that it runs smoothly with zero bugs.
Before developing the code, the CI/CD pipeline must be laid out – from building the code to testing it and deploying it on the production server. One can add processes to review and analyze the code, to the pipeline, to ensure that the code functions as expected.
Once a developer completes the source code, they push or commit it to a repository, such as GIT or SVN. This triggers the pipeline, which starts automating the build phase. Once the code is compiled in the build, it is reviewed to ensure it works alright. In the case it doesn’t, it has to be worked on to accommodate the requirements flawlessly.
Now that the code is reviewed, approval is requested from the change board. Suggestions and requests from the change board must be incorporated. Once approved, the compiled package can be uploaded onto UiPath Orchestrator. With that, the bot is ready to be executed.
There are methods to further optimize the CI/CD pipeline and enhance the benefits mentioned above. With RPA bots spanning across industries such as education, accounting, legal, and so on, it is imperative that the bots are deployed with minimum errors.
When automating a bot for a third party, the back-and-forth suggestions are often cumbersome. The whole code has to go through the pipeline before approval, which may involve further modifications. The client would have suggestions or the code could even have bugs when deployed. Now, the code has to be worked on and run through the pipeline again. In the case of larger modifications, this process can be quite time-consuming. This linear approach to automating bots, known as the waterfall method, is not cost-effective and rather time-consuming.
To ensure the project picks up pace, it is split. A whole project, let’s say, building an RPA bot, is split into sprints or segments. Each segment or sprint, a process followed to achieve a set of functionalities, is a subset of the entire project.
The first sprint involves planning and preparation. A project is thoroughly analyzed and studied before breaking it down into sprints or segments. Test cases are created, the RPA tool is installed on the client’s server, and a repository is created. A CI/CD pipeline is created on Azure DevOps to automate the project right from build to execution. The expectations from the rest of the sprints depend on the project and its requirements.
Every sprint is run through the CI/CD pipeline and delivered to the third party to ensure that the requirements of the sprint are approved. Once a sprint is approved, the code built and deployed as part of the previous sprint gets added to the current sprint. As each sprint gets approved, the bot is closer to completion, with lesser bugs as all the previous sprints would have low to zero bugs.
Connect with our experts today to integrate and deploy your RPA requests in strikingly lesser time by employing a CI/CD pipeline.
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