Today, I am proud to announce our new partnership with GitLab and Dotscience. GitLab and Dotscience are passionate about bringing DevOps tools and processes to the AI/ML ecosystem with the goal of achieving MLOps. The combination of GitLab and Dotscience provides a fully integrated DevOps & MLOps platform by combining source repository, issue tracking, and continuous integration. Together we can offer a machine learning environment that provides the ability to build, train, deploy, monitor, reproduce data, code, and models, and collaborate on notebooks.
Dotscience and GitLab integration
The integration highlights include the following:
- Combine Dotscience and GitLab to achieve a complete DevOps & MLOps platform
- Apply the same merge request workflow you know and love in GitLab to AI & ML projects with Jupyter Notebooks, data, parameters & metrics with Dotscience
- Customize the Docker images you build in Dotscience by implementing the Docker build step of deploying an ML model to production as a GitLab repo, custom Dockerfile + build pipeline
Let’s see it in action
Luke Marsden and I sat down with Tina Sturgis, manager of partner marketing at GitLab, and provided a little overview of the integration.
Ready to give it a spin? The easiest way to get started is to sign up for a free trial at Dotscience and read the integration documentation.
Dotscience is also available on-prem, on AWS, Azure and Google Cloud, and in multi-cloud configurations.
If you have questions, please join our Slack channel.
“.@getdotscience announces an integration with @gitlab for #MLOps” – Chris Sterry, Dotscience
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