With GitLab 14, GitLab is reaffirming its view of a unified DevOps platform integrating all the tools and tech stacks that are required by development teams. The latest release of the platform includes many new features meant to improve development velocity, application security, and analytics.
GitLab allows teams to use one tool for source code management (SCM), continuous integration (CI), and continuous delivery (CD) making teams more efficient and productive with streamlined collaboration.
To make it easier to manage epics, GitLab 14 introduce Epic Boards, which allow team members to view and modify all of their epics in a single place through a multi-column, drag-and-drop, card-like UI. Epic boards could be seen as kanban boards applied to epics, which are collections of related issues that span across projects or milestones. Epics in GitLab may also include other epics as their children in addition to usual issues.
In previous versions of GitLab, working with CI/CD pipelines required starting with an empty pipeline, which did not provide an extremely friendly experience to beginner pipeline authors. GitLab 14 introduces an initial template for its pipeline editor which defines a 3-stage pipeline that can be used as a base for further exploration.
Similarly, to make working with Kubernetes clusters more efficient, GitLab 14 introduces a new template to create a cluster management project. The new template uses the Helm v3 package manager and includes some pre-configured apps aiming to show how you can integrate various GitLab features.
Another area where GitLab 14 brings new features is security. In particular, after introducing fuzz testing and security dashboards in version 13.9, GitLab 14 improves container scanning with the introduction of the Trivy engine, which should provide more timely vulnerability updates, more accurate results, and extends OS support.
As a final note, it is worth mentioning the new visibility and measurement features, including improved Value Stream Analytics, which enables to identify inefficiencies along with their root causes, and Deployment charts, which enable to monitor deployment efficiency over time and to find bottlenecks.