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Since Version 14.3, GitLab has supported migrating GitLab groups by direct transfer, where, rather than manually uploading export files, data is transferred directly from the source instance to the destination instance. We have been working to extend this functionality to projects and are including the ability to migrate projects by direct transfer as a beta in GitLab 15.8.

The beta release for migrating GitLab projects with top-level groups by direct transfer is available on GitLab.com. You can migrate from a self-managed GitLab instance to GitLab.com or within GitLab.com right now!

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Once the migrating projects by direct transfer feature is ready for production use at any scale, migrating groups and projects using file exports

will be disabled by a feature flag and only migrating groups and projects by direct transfer will be available in the UI and API.

Because migrating by direct transfer requires network connection between instances or GitLab.com, customers that are using air-gapped networks with no

network connectivity between their GitLab instances will need to reenable migrating using file exports. They will be able to use migrating groups and

projects by direct transfer after we extend this solution to also support offline instances.

Disclaimer: This blog contains information related to upcoming products, features, and functionality. It is important to note that the information in this blog post is for informational purposes only. Please do not rely on this information for purchasing or planning purposes. As with all projects, the items mentioned in this blog and linked pages are subject to change or delay. The development, release, and timing of any products, features, or functionality remain at the sole discretion of GitLab.

I'm brand new to gitlab. I just decided to learn a little about it by watching an intro video on LinkedIn Learning. But I'm curious about how to search for other people's repos. This is really easy in github, but I don't see a simple way to do it in Gitlab. Specifically, how would I search for other projects that use a particular programming language? I've tried text searches and I get some results, but they're just text searches so they return lots of useless results. In Github, it's a simple thing to search public repos by programming language.

Both links are rather impressive! I would like to add another tip to complement your answer with an answer just focused on the very topic of my question. Please, check this StackOverflow thread: How to create a new gitlab repo from my existing local git repo, using CLI?

Machine learning operations (MLOps) are key to effectively transition from an experimentation phase to production. The practice provides you the ability to create a repeatable mechanism to build, train, deploy, and manage machine learning models. To quickly adopt MLOps, you often require capabilities that use your existing toolsets and expertise. Projects in Amazon SageMaker give organizations the ability to easily set up and standardize developer environments for data scientists and CI/CD (continuous integration, continuous delivery) systems for MLOps engineers. With SageMaker projects, MLOps engineers or organization administrators can define templates that bootstrap the ML workflow with source version control, automated ML pipelines, and a set of code to quickly start iterating over ML use cases. With projects, dependency management, code repository management, build reproducibility, and artifact sharing and management become easy for organizations to set up. SageMaker projects are provisioned using AWS Service Catalog products. Your organization can use project templates to provision projects for each of your users.

In this post, you use a custom SageMaker project template to incorporate CI/CD practices with GitLab and GitLab pipelines. You automate building a model using Amazon SageMaker Pipelines for data preparation, model training, and model evaluation. SageMaker projects builds on Pipelines by implementing the model deployment steps and using SageMaker Model Registry, along with your existing CI/CD tooling, to automatically provision a CI/CD pipeline. In our use case, after the trained model is approved in the model registry, the model deployment pipeline is triggered via a GitLab pipeline.

This post provides a detailed explanation of the SageMaker projects, GitLab, and GitLab pipelines integration. We review the code and discuss the components of the solution. To deploy the solution, reference the GitHub repo, which provides step-by-step instructions for implementing a MLOps workflow using a SageMaker project template with GitLab and GitLab pipelines.

The following screenshot contains a subset of the function code that triggers the GitLab pipeline in the .gitlab-ci.yml file. It deploys the SageMaker model endpoints using the CloudFormation template endpoint-config-template.yml in your model deploy repository.

After the project is successfully created, using our custom template in SageMaker projects per the steps in the code repo, navigate to your GitLab account to see two new repositories. Each repository has a GitLab CI pipeline associated with it that runs as soon as the project is created.

In this post, we walked through using a custom SageMaker MLOps project template to automatically build and configure a CI/CD pipeline. This pipeline incorporated your existing CI/CD tooling with SageMaker features for data preparation, model training, model evaluation, and model deployment. In our use case, we focused on using GitLab and GitLab pipelines with SageMaker projects and pipelines. For more detailed implementation information, review the GitHub repo. Try it out and let us know if you have any questions in the comments section!

Setting up the import of GitLab projects into SonarQube allows you to easily create SonarQube projects from your GitLab projects. If you're using Developer Edition or above, this is also the first step in adding merge request decoration.

To import your GitLab projects into SonarQube, you need to first set your global SonarQube settings. Navigate to Administration > Configuration > General Settings > DevOps Platform Integrations, select the GitLab tab, and specify the following settings:

Then, you'll be asked to provide a personal access token with read_api scope so SonarQube can access and list your GitLab projects. This token will be stored in SonarQube and can be revoked at any time in GitLab.

After saving your personal access token, you'll see a list of your GitLab projects that you can set up to add to SonarQube. Setting up your projects this way also sets your project settings for merge request decoration.

In order for the quality gate to fail on the GitLab side when it fails on the SonarQube side, the scanner needs to wait for the SonarQube quality gate status. To enable this, set the sonar.qualitygate.wait=true parameter in the .gitlab-ci.yml file.

SonarQube can also report your quality gate status to GitLab merge requests for existing and manually-created projects. After you've updated your global settings as shown in the Importing your GitLab projects into SonarQube section above, set the following project settings at Project Settings > General Settings > DevOps Platform Integration:

In a mono repository setup, multiple SonarQube projects, each corresponding to a separate project within the mono repository, are all bound to the same GitLab repository. You'll need to set up each SonarQube project that's part of a mono repository to report your quality gate status.

You need to set up projects that are part of a mono repository manually as shown in the Reporting your quality gate status in GitLab section above. You also need to set the Enable mono repository support setting to true at Project Settings > General Settings > DevOps Platform Integration.

You need to adjust the analysis scope to make sure SonarQube doesn't analyze code from other projects in your mono repository. To do this set up a Source File Inclusion for your project at Project Settings > Analysis Scope with a pattern that will only include files from the appropriate folder. For example, adding ./MyFolderName/**/* to your inclusions will only include code in the MyFolderName folder. See Narrowing the focus for more information on setting your analysis scope.

Because of the nature of a mono repository, SonarQube scanners might read all project names of your mono repository as identical. To avoid having multiple projects with the same name, you need to pass the sonar.projectName parameter to the scanner. For example, if you're using the Maven scanner, you would pass mvn sonar:sonar -Dsonar.projectName=YourProjectName.

SonarQube can report your quality gate status to multiple DevOps platform instances. To do this, you need to create a configuration for each DevOps platform instance and assign that configuration to the appropriate projects.

Defender CSPM features: Defender CSPM customers receive code to cloud contextualized attack paths, risk assessments, and insights to identify the most critical weaknesses that attackers can use to breach their environment. Connecting your GitLab projects will allow you to contextualize DevOps security findings with your cloud workloads and identify the origin and developer for timely remediation. For more information, learn how to identify and analyze risks across your environment

Since GitLab projects are onboarded at no additional cost, autodiscover is applied across the group to ensure Defender for Cloud can comprehensively assess the security posture and respond to security threats across your entire DevOps ecosystem. Groups can later be manually added and removed through Microsoft Defender for Cloud > Environment settings. 2351a5e196