This new dashboard provides strategic insights into metrics that help decision-makers
identify trends and patterns to optimize software delivery. The first iteration of the GitLab Value Streams Dashboard
is focused on enabling teams to continuously improve software delivery workflows by benchmarking value stream life cycle
(value stream analytics, DORA4),
and vulnerabilities metrics.
Organizations can use the Value Streams Dashboard
to track and compare these metrics over a period of time, identify downward trends early, understand security exposure,
and drill down into individual projects or metrics to take actions for improvements.
This comprehensive view built as a single application with a unified data store allows all stakeholders, from
executives to individual contributors, to have visibility into the software development life cycle, without needing
to buy or maintain a third-party tool.
When you’re commenting in issues, epics, or merge requests you might repeat yourself and need to write the same comment over and over. Maybe you always need to ask for more information about a bug report. Maybe you’re applying labels via a quick action as part of a triage process. Or maybe you just like to finish all your code reviews with a funny gif or appropriate emoji. 🎉
Comment templates enable you to create saved responses that you can apply in comment boxes around GitLab to speed up your workflow. To create a comment template, go to User settings > Comment templates and then fill out your template. After it’s saved, select the Insert comment template icon on any text area, and your saved response will be applied.
This is a great way to standardize your replies and save you time!
Managing your fork just got easier. When your fork is behind, select Update fork in the GitLab UI to catch it up with upstream changes. When your fork is ahead, select Create merge request to contribute your change back to the upstream project. Both operations previously required you to use the command line.
See how many commits your fork is ahead (or behind) on your project’s main page and at Repository > Files. If merge conflicts exist, the UI gives guidance on how to resolve them using Git from the command line.
Do you need to mirror a busy repository with many branches, but you only need a few of them? Limit the number of
branches you mirror by creating a regular expression that matches only the branches you need.
Previously, mirrors required you to mirror an entire repository, or all protected branches. This new flexibility
can decrease the amount of data your mirrors push or pull, and keep sensitive branches out of public mirrors.
Since its introduction, we’ve been iterating on the usability, performance, and stability of the Web IDE, which
has enabled us to build features like remote development workspaces and code suggestions on a powerful foundation.
We have received overwhelmingly positive feedback on the Web IDE Beta and starting in GitLab 16.0, we are making
it the default multi-file code editor across GitLab.
Stop spending hours, or even days, troubleshooting your local development environment and interpreting inscrutable package installation errors. Now you can define a consistent, stable, and secure development environment in code and use it to create on-demand, remote development workspaces.
These workspaces serve as personal, ephemeral development environments in the cloud. By eliminating the need for a local development environment, you can focus more on your code and less on your dependencies. Accelerate the process of onboarding to a new project and get up and running in minutes instead of days.
After the GitLab Agent for Kubernetes is configured and the dependencies are installed in your self-hosted cluster or cloud platform of choice, you can define your development environment in a .devfile.yaml file and store it in a public project. Then, you and any other developers with access to the agent can create a workspace based on the .devfile.yaml file and edit directly in the embedded Web IDE. You’ll have full terminal access to the container, allowing you to work more efficiently. When you’re done, or if something goes wrong, you can shut down the workspace and start a fresh, new workspace for your next development task.
This short video walks you through the lifecycle of a workspace in the current Beta. Learn more about workspaces in the documentation and let us know what you think in the feedback issue.
As security shifts left, remediating security findings without guidance can be challenging. Developers need actionable advice so they can resolve vulnerabilities and continue
building features. Contextual training that is relevant to the specific vulnerabilty detected was released in GitLab 14.9.
In this release, we are adding an integration with SecureFlag based upon the CWE of the vulnerability. SecureFlag’s
training solution is unique in that the labs involve remediating the vulnerability in a live environment,
which can be transferred to a real environment.
GitLab is evolving into an AI‑powered DevSecOps platform. Over the past month, we’ve introduced 10 new experiments
to improve efficiency and productivity across various GitLab features, all leveraging AI.
These AI-powered workflows boost efficiency and reduce cycle times in every phase of the software development lifecycle.
Code Suggestions is now available on GitLab.com for all users for free while the feature is in Beta. Teams can
boost efficiency with the help of generative AI that suggests code while you’re developing.
We’ve extended language support from our initial six languages to now include 13 languages: C/C++, C#, Go, Java,
We are making improvements to the Code Suggestions underlying AI model weekly to improve the quality of suggestions.
Please remember that AI is non-deterministic, so you may not get the same suggestion week to week.
GitLab Error Tracking, which allows developers to discover and view errors generated by their application, is now generally available on GitLab.com! GitLab error tracking helps to increase efficiency and awareness by surfacing error information directly in the same interface as the code is developed, built, deployed, and released.
Now you can use a Jira personal access token to authenticate
if you are using Jira Data Center and Jira Server with Jira 8.14 and later. A Jira personal access token is a safer alternative to a username and password.
In GitLab 15.10, we started mapping GitHub repository collaborators as GitLab project members during GitHub project imports. We received
feedback that this led to confusion and that some GitHub collaborators were
unexpectedly added and consumed seats.
In GitLab 16.0, we’ve iterated and added GitHub repository collaborators to the list of
additional items to import. This gives users the option
to avoid importing these users and to understand the possible implications of importing them.
This option is selected by default. Leaving it selected might result in new users using a seat in the group or namespace, and being granted permissions
as high as project owner. Only
direct collaborators are imported. Outside collaborators are never imported.
GitLab 16.0 features an all-new navigation experience! To get started, go to your avatar in the top right of the UI and turn on the New navigation toggle. The left sidebar changes to a new and improved design, based on user feedback we’ve received over the last year.
Please let us know about your experience in this issue. Based on the feedback, we will be progressively enabling the new navigation across our user base, with the final step being removal of the old navigation.
In previous versions of GitLab, cookies of different GitLab Pages sites under the same top-level group were visible for other projects under the same top-level because of the GitLab Pages default URL format.
Now, you can secure your sites by assigning a unique subdomain to each GitLab Pages project.
When working on merge requests, it’s important to make sure that what you’re seeing is the latest information for approvals, pipelines or other information that might impact your ability to get the changes merged. Historically, this has meant refreshing the merge request or waiting for polling updates to come through.
We’ve improved the experience of both the merge button widget and approval widget inside of the merge request, so that they now update in real-time in the merge request. This is a great improvement to improve the speed at which you can deliver changes, and the confidence at which you can move a merge request forward knowing you’re seeing the latest information.
The include keyword lets you compose your CI/CD configuration from multiple files. For example, you can split one
long .gitlab-ci.yml file into multiple files to increase readability, or reuse one CI/CD configuration file in multiple projects.
Previously, a single CI/CD configuration could include up to 150 files, but in GitLab 16.0 administrators can modify this limit to a different value in the instance settings.
In this new workflow, adding a new runner to a GitLab instance requires authorized users to create a runner in the GitLab UI and include essential configuration metadata. With this method, the runner is now easily traceable to the user, which will help administrators troubleshoot build issues or respond to security incidents.
We’re also releasing GitLab Runner 16.0 today! GitLab Runner is the lightweight, highly-scalable agent that runs your CI/CD jobs and sends the results back to a GitLab instance. GitLab Runner works in conjunction with GitLab CI/CD, the open-source continuous integration service included with GitLab.
Users can now use the new REST API endpoint, POST /user/runners, to automate the creation of runners associated with a user. When a runner is created, an authentication token is generated. This new endpoint supports the Next GitLab Runner Token Architecture workflow.
Previously, a trigger job configured with strategy: depends mirrored the job status of the downstream pipeline. If the downstream pipeline was in the running status, the trigger job was also marked as running. Unfortunately, if the downstream job did not comnplete and had a status canceled, the trigger job’s status was inaccurately failed.
In this release, we have updated trigger jobs with strategy: depend to reflect the downstream’s pipelines’s statis accurately. When a downstream pipeline is cancelled, the trigger also shows canceled.
This change may have an impact on your existing pipelines, especially if you have jobs that rely on the trigger job’s status being marked as failed. We recommend reviewing your pipeline configurations and making any necessary adjustments to accommodate this change in behavior.
Have you been thinking about moving your Maven or Gradle repository to GitLab, but haven’t been able to invest the time to plan the migration? GitLab is proud to announce the MVC launch of a Maven/Gradle package importer.
You can now use the Packages Importer tool to import packages from any Maven/Gradle compliant registry, like Artifactory.
To use the tool, simply create a config.yml file that contains the details of the packages you want to import into GitLab. Then add the importer to a .gitlab-ci.yml pipeline configuration file, and the importer does the rest. It runs in the pipeline, dynamically generating a child pipeline with jobs that import all the packages into your GitLab package registry.
GitLab Static Application Security Testing (SAST) now offers Semgrep-based scanning for Scala code.
This work builds on our previous introduction of Semgrep-based Java scanning in GitLab 14.10.
As with the other languages we have transitioned to Semgrep-based scanning, Scala scanning coverage uses GitLab-managed detection rules to detect a variety of security issues.
The new Semgrep-based scanning runs significantly faster than the existing analyzer based on SpotBugs.
It also doesn’t need to compile your code before scanning, so it’s simpler to use.
GitLab’s Static Analysis and Vulnerability Research teams worked together to translate rules to the Semgrep format, preserving most existing rules.
We also updated, refined, and tested the rules as we converted them.
If you use the GitLab-managed SAST template (SAST.gitlab-ci.yml), both Semgrep-based and SpotBugs-based analyzers now run whenever Scala code is found.
In GitLab Ultimate, the Security Dashboard combines findings from the two analyzers, so you won’t see duplicate vulnerability reports.
In GitLab 15.11, we added bulk adding and
removing of compliance frameworks to the
compliance frameworks report.
Now in GitLab 16.0, you can also add and remove compliance frameworks from projects directly from the report table row.
Before GitLab 16.0, you had to create and edit frameworks in the group’s settings.
Now in GitLab 16.0, you can create or edit your compliance frameworks in the
compliance framework report as well. This simplifies the framework creation workflow and reduces the need to switch contexts while managing your frameworks.
Updates to GitLab 16.0 also update cert-manager to version 1.11.x. This cert-manager update includes breaking changes you must
read before upgrading.
These changes include a change to container names that was best done during a major release of GitLab. To see details of updated features, see the
releases notes for cert-manager 1.11.
PostgreSQL 12 is no longer supported. The minimum required version is PostgreSQL 13, and support for PostgreSQL 14 is added.
New chart installs of GitLab include PostgreSQL 14 by default, and upgrades must follow the steps for
upgrading the bundled PostgreSQL version.
Updates to GitLab 16.0 include an update to the Redis subchart to version 16.13.2, including Redis 6.2.7.
Starting with 16.0, self-managed installations of GitLab will have two database connections by default, instead of
one. This change makes self-managed versions of GitLab behave similarly to GitLab.com, and is a step towards enabling
a separate database for CI features for self-managed versions of GitLab.
This change applies to installation methods with Omnibus GitLab, GitLab Helm chart, GitLab Operator, GitLab Docker images, and installation from source.
Administrators can remove the “Remember Me” option for users when signing in so that sessions cannot be extended and the user is forced to re-authenticate. Limiting the duration of a session may improve instance security.
Value Stream Analytics has been extended with two new stage events: issue first assigned and merge request first assigned.
These events can be useful for measuring the time it takes for an item to be first assigned to a user.
To implement this feature, GitLab started storing the history of assignment events in GitLab 16.0. This means that issue
and MR assignment events prior to GitLab 16.0 are not available.
In this release we are excited to announce the availability of CI/CD components, as an experimental feature. A CI/CD component is a reusable single-purpose building block that can be used to compose a part of a project’s CI/CD configuration, or even an entire pipeline.
When combined with the inputs keyword, a CI/CD component can be made much more flexible. You can configure the component to your exact needs by inputting values which can be used for job names, variables, credentials, and so on.
In this new workflow, adding a new runner to a GitLab group requires authorized users to create a runner in the GitLab UI and include essential configuration metadata. With this method, the runner is now easily traceable to the user, which will help administrators troubleshoot build issues or respond to security incidents.
Using a cache is a great way to speed up your pipelines by reusing dependencies that were already fetched in a previous job or pipeline. But when there is no cache yet, the benefits of caching are lost because the job has to start from scratch, fetching every dependency.
We previously introduced a single fallback cache to use when no cache is found, that you can define globally. This was useful for projects that used a similar cache for all jobs. Now in 16.0 we’ve improved that feature with per-cache fallback keys. You can define up to 5 fallback keys for every job’s cache, greatly reducing the risk that a job runs without a useful cache. If you have a wide variety of caches, you can now use an appropriate fallback cache as needed.
The GitLab Package Registry now supports downloading Maven packages using the Scala build tool (sbt). Previously, Scala users had no way to download Maven packages from the registry because basic authentication was not supported. As a result, Scala users were either blocked from using the registry or had to use Maven (mvn) or Gradle as an alternative.
By adding support for Scala, we hope to help you use the Package Registry with your more data intensive projects.
Please note that publishing artifacts using sbt is not yet supported, but you can follow issue 408479 if you are interested in adding support for publishing.
We have optimized the way that the browser-based DAST analyzer performs its scans. These improvements have significantly
decreased the amount of time that it takes to run a DAST scan with the browser-based analyzer. The following improvements have been made:
Added log summary statistics to help determine where time is spent during a scan. This can be enabled by including the environment variable DAST_BROWSER_LOG="stat:debug".
Optimized passive checks by running them in parallel.
Optimized passive checks by caching regular expressions used when matching content in HTTP response bodies.
Optimized how DAST determines whether a page has finished loading. Now, we don’t wait for excluded document types or out-of-scope URLs.
Reduced waiting time for pages where the DOM stabilizes quickly after page load.
With these improvements, we have seen browser-based DAST scan times reduced by 50%-80%, depending on the complexity and size of the
application being scanned. While this percentage decrease may not be seen in all scans, your browser-based DAST scans should now take significantly less time to complete.
Previously, GitLab’s DAST analyzers did not support callback attacks while performing active checks. This meant that Out-of-band Application Security Testing (OAST) needed to be configured separately from your DAST scan.
In this release we are introducing the BAS.latest.gitlab-ci.yml template. The Breach and Attack Simulation CI/CD template features job configuration for the browser-based DAST analyzer and enables container-to-container networking to add extended DAST scans against service containers to your CI/CD pipeline.
We’re continuously iterating to develop new Breach and Attack Simulation features. We’d love to hear your feedback on the addition of callback attacks to browser-based DAST.
When a user raises an access request for a group or project, the request appears in the To-Do List of the group or project owner.
For groups and projects that have multiple owners, the request appears in each owner’s To-Do List.
With this new functionality, to-do items that have already been completed by another owner are marked Done in the others’ To-Do Lists.
We have received feedback from users who wanted to prevent getting unwanted followers of their user profile. We listened to your concerns, so now, in your user profile settings under Preferences, you can disable following.
When you disable this feature, no one can follow you, and you cannot follow anyone. All existing following and follower relationships are removed, and the count is set to zero.
Unauthenticated users of the Projects List API will be subject to rate limitations moving forward.
On GitLab.com, the limit is set to 400 requests per 10 minutes per unique IP address.
Users of self-managed GitLab instances have the same rate limitation by default, but administrators can change the rate limits as they see fit. We encourage users who need to make more than 400 requests per 10 minutes to the Projects List API to sign up for a GitLab account.
With role-based approval actions, you can configure scan result policies to require approval from GitLab-supported roles, including Owners, Maintainers, and Developers.
This gives you additional flexibility over requiring individual approvers or defined groups of users, making it easier to enforce policies based on roles you already leverage in GitLab, at scale, especially across large organizations.