Adopting CI/CD tools can be highly beneficial for ML projects. These tools aid in the detection of code errors and contradictions as well as the reduction of long-term downtime costs.
Continuous integration (CI) – It is about how a project should be built and tested automatically and multiple runtimes at all times.
Continuous deployment (CD) – It is needed so that every new piece of code that passes automated testing can be in production without any extra work.
In real-world projects, it can be challenging for experts to choose high-quality machine learning models that don’t clash with how businesses manage projects.
Let’s see the top seven CI/CD tools for machine learning projects.
Jenkins
Jenkins is a well-known CI/CDJava application that runs on Windows, Mac OS X, and other Unix-like operating systems under the MIT license. It includes a comprehensive set of features for automating the tasks of developing, testing, deploying, integrating, and releasing software.
Jenkins can be installed stand-alone or as Docker on any machine with the Java Runtime Environment (JRE) installed and via a traditional installation package. Jenkins X, a subproject of the Jenkins team, specializes in CI/CD within Kubernetes clusters. In addition, the Jenkins team has released approximately 1,500 plugins with other solutions, such as Slack or Jira. We can also integrate a variety of DevOps testing tools.
Furthermore, there is REST API support for remote system access. The product, like GitLab, has a large and enthusiastic community.
CML
Continuous Machine Learning is an open-source tool. CML is one of the few projects specifically designed for the needs of MLOps, so you can easily try it out.
CML strives to simplify ML model implementation and deployment and get them to the delivery stage faster and with fewer bugs.
This tool supports GitFlow for data science projects, allows for automatic report generation, and saves you from having to delve deeper into the complex details of using external services. Cloud platforms such as AWS, Azure, and Google Cloud are examples of these external services.
TeamCity
The JetBrains team created TeamCity, an enterprise-level continuous integration server. It has robust functionality and a free version for small projects (up to 100 build configurations).
TeamCity includes extensive support for many open-source plugins, JetBrains products, and third-party applications and tools. In addition, TeamCity provides excellent.NET support.
The software lets you track commits and start building and running unit tests immediately. For example, if tests or compilations fail following a commit, the tool will notify the developer that we must revise the code.
GitHub Actions
GitHub Actions is a new workflow automation feature from Github. GitHub provides CI/CD functionality, such as pushing code, creating releases, and managing issues.
You can immediately access GitHub Actions after logging in to GitHub. In addition, it offers numerous CI/CD possibilities, such as automated testing, container building, web service deployment, and automating the onboarding of new users in your open-source project.
GitHub isn’t just an MLOps tool; its applications are far more diverse. However, because many companies write and store code for their ML projects on GitHub, it may be more convenient for some teams than any other tool on our list. In addition, one of the most active communities in the world works on improving and developing this project, which is an undeniable benefit.
GitLab for CI/CD
GitLab CI/CD is a free, open-source product written in Go and Ruby and released under the MIT license. It can handle more than 25,000 users on a separate server.
You can use GitLab CI/CD to work with repositories and perform code reviews. It also has an error management system. By installing the tool locally, you can connect it to Active Directory and LDAP servers to improve user privacy.
Working with the product is made more accessible by a large and engaged community. GitLab is not only for writing code but also for thoroughly reviewing it. Almost every type of build environment and version control system is supported.
Travis CI
Travis CI is a free continuous integration platform for all GitHub-hosted open-source projects. Developers can trigger automatic builds whenever your codebase changes in the main branch, other branches, or even on a pull request with just a file named.travis.yml containing some information about your project. Don’t get travis-ci.org and travis-ci.com mixed up. The first is open-source, and the second is a paid continuous integration system. CircleCI and Travis CI are very similar.
Source: indiaai.gov.in
