The rapyuta.io platform takes the responsibility of building and delivering the software across the cloud and device.
Under the hood, rapyuta.io solves the hard problems of native arm compiles, software versioning, artifact delivery, transactional upgrades and provisioning.
With all these features backed by a complete API, it makes it possible for the developer to automate the flow from git to operations and integrate it with existing CI/CD systems and QA processes.
rapyuta.io builds as catkin and docker build recipes. The goal of each build recipe is to generate a running docker container at the end of the build creation process.
In the Builds section to add a new build, add the Build name and provide the URL address of git repository. Suppose you want to add the address of a git repository say https://github.com/rapyuta-robotics/io_tutorials, where io_tutorials is the project folder that contains the source code on the master branch and is hosted on GitHub.
If you want to add source code located on a different branch, say io_turtlesim_qos of the same project, your git repository URL will look like: https://github.com/rapyuta-robotics/io_tutorials#io_turtlesim_qos
This recipe builds ros based source code using catkin into a container image. We allow our users to add any valid catkin parameters in this recipe.
The ROS Publisher Subscriber walkthrough is an example of the catkin build recipe.
rapyuta.io supports cross-compilation of source code to be able to run on devices with arm64, arm32 CPU architectures.
rapyuta.io supports cloning and fetching from repositories that deal with large files (as large as a couple of GB in size) with Git Large File System (LFS) extension. If you want to use Git LFS with a private git repository, you must select SSH authentication while adding a source secret because the LFS extension will fail with the Basic authentication, and the corresponding source secret will not be applied to the private repository.
This recipe builds source code using Dockerfile into a container image. The Dockerfile is usually saved in your git repository. You may explicitly specify the absolute path of the Dockerfile, or the root of the git repository is set as the location of the Dockerfile.
The Basic Web Application walkthrough is an example of the docker build recipe.
If you are going to deploy a docker container image onto a device, ensure that the CPU architecture of the device is compatible with that of the image being deployed. You may select the appropriate target architecture while creating the build.