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Danger bot

The GitLab CI/CD pipeline includes a danger-review job that uses Danger to perform a variety of automated checks on the code under test.

Danger is a gem that runs in the CI environment, like any other analysis tool. What sets it apart from (for example, RuboCop) is that it's designed to allow you to easily write arbitrary code to test properties of your code or changes. To this end, it provides a set of common helpers and access to information about what has actually changed in your environment, then simply runs your code!

If Danger is asking you to change something about your merge request, it's best just to make the change. If you want to learn how Danger works, or make changes to the existing rules, then this is the document for you.

Danger comments in merge requests

Danger only posts one comment and updates its content on subsequent danger-review runs. Given this, it's usually one of the first few comments in a merge request if not the first. If you didn't see it, try to look from the start of the merge request.

Advantages

  • You don't get email notifications each time danger-review runs.

Disadvantages

  • It's not obvious Danger updates the old comment, thus you need to pay attention to it if it is updated or not.

Run Danger locally

A subset of the current checks can be run locally with the following Rake task:

bin/rake danger_local

Operation

On startup, Danger reads a Dangerfile from the project root. Danger code in GitLab is decomposed into a set of helpers and plugins, all within the danger/ subdirectory, so ours just tells Danger to load it all. Danger then runs each plugin against the merge request, collecting the output from each. A plugin may output notifications, warnings, or errors, all of which are copied to the CI job's log. If an error happens, the CI job (and so the entire pipeline) fails.

On merge requests, Danger also copies the output to a comment on the MR itself, increasing visibility.

Development guidelines

Danger code is Ruby code, so all our usual backend guidelines continue to apply. However, there are a few things that deserve special emphasis.

When to use Danger

Danger is a powerful tool and flexible tool, but not always the most appropriate way to solve a given problem or workflow.

First, be aware of the GitLab commitment to dogfooding. The code we write for Danger is GitLab-specific, and it may not be most appropriate place to implement functionality that addresses a need we encounter. Our users, customers, and even our own satellite projects, such as Gitaly, often face similar challenges, after all. Think about how you could fulfill the same need while ensuring everyone can benefit from the work, and do that instead if you can.

If a standard tool (for example, rubocop) exists for a task, it's better to use it directly, rather than calling it by using Danger. Running and debugging the results of those tools locally is easier if Danger isn't involved, and unless you're using some Danger-specific functionality, there's no benefit to including it in the Danger run.

Danger is well-suited to prototyping and rapidly iterating on solutions, so if what we want to build is unclear, a solution in Danger can be thought of as a trial run to gather information about a product area. If you're doing this, make sure the problem you're trying to solve, and the outcomes of that prototyping, are captured in an issue or epic as you go along. This helps us to address the need as part of the product in a future version of GitLab!

Implementation details

Implement each task as an isolated piece of functionality and place it in its own directory under danger as danger/<task-name>/Dangerfile.

Each task should be isolated from the others, and able to function in isolation. If there is code that should be shared between multiple tasks, add a plugin to danger/plugins/... and require it in each task that needs it. You can also create plugins that are specific to a single task, which is a natural place for complex logic related to that task.

Danger code is just Ruby code. It should adhere to our coding standards, and needs tests, like any other piece of Ruby in our codebase. However, we aren't able to test a Dangerfile directly! So, to maximize test coverage, try to minimize the number of lines of code in danger/. A non-trivial Dangerfile should mostly call plugin code with arguments derived from the methods provided by Danger. The plugin code itself should have unit tests.

At present, we do this by putting the code in a module in tooling/danger/..., and including it in the matching danger/plugins/... file. Specs can then be added in spec/tooling/danger/....

To determine if your Dangerfile works, push the branch that contains it to GitLab. This can be quite frustrating, as it significantly increases the cycle time when developing a new task, or trying to debug something in an existing one. If you've followed the guidelines above, most of your code can be exercised locally in RSpec, minimizing the number of cycles you need to go through in CI. However, you can speed these cycles up somewhat by emptying the .gitlab/ci/rails.gitlab-ci.yml file in your merge request. Just don't forget to revert the change before merging!

Adding labels via Danger

NOTE: This is applicable to all the projects that use the gitlab-dangerfiles gem.

Danger is often used to improve MR hygiene by adding labels. Instead of calling the API directly in your Dangerfile, add the labels to helper.labels_to_add array (with helper.labels_to_add << label or helper.labels_to_add.concat(array_of_labels). gitlab-dangerfiles will then take care of adding the labels to the MR with a single API call after all the rules have had the chance to add to helper.labels_to_add.

Shared rules and plugins

If the rule or plugin you implement can be useful for other projects, think about upstreaming them to the gitlab-dangerfiles project.

Enable Danger on a project

To enable the Dangerfile on another existing GitLab project, complete the following steps:

  1. Add gitlab-dangerfiles to your Gemfile.

  2. Create a Dangerfile with the following content:

    require "gitlab-dangerfiles"

Gitlab::Dangerfiles.for_project(self, &:import_defaults)

  3. Add the following to your CI/CD configuration:

    include:
  - project: 'gitlab-org/quality/pipeline-common'
    file:
      - '/ci/danger-review.yml'
    rules:
      - if: '$CI_SERVER_HOST == "gitlab.com"'

  4. If your project is in the gitlab-org group, you don't need to set up any token as the DANGER_GITLAB_API_TOKEN variable is available at the group level. If not, follow these last steps:

    1. Create a Project access tokens.
    2. Add the token as a CI/CD project variable named DANGER_GITLAB_API_TOKEN.

You should add the ~"Danger bot" label to the merge request before sending it for review.

Current uses

Here is a (non-exhaustive) list of the kinds of things Danger has been used for at GitLab so far:

  • Coding style
  • Database review
  • Documentation review
  • Merge request metrics
  • Reviewer roulette. Reviewers and maintainers are chosen based on:
    • Their roles (backend, frontend, database, etc).
    • Their availability:
      • No "OOO"/"PTO"/"Parental Leave" in their GitLab or Slack status.
      • No :red_circle:/:palm_tree:/:beach:/:beach_umbrella:/:beach_with_umbrella: emojis in GitLab or Slack status.
    • (Experimental) Their time zone: people for which the local hour is between 6 AM and 2 PM are eligible to be picked. This is to ensure they have a good chance to get to perform a review during their current work day. The experimentation is tracked in this issue
  • Single codebase effort

Limitations

Danger is run but its output is not added to a merge request comment if working on a fork. This happens because the secret variable from the canonical project is not shared to forks.

Configuring Danger for forks

Contributors can configure Danger for their forks with the following steps:

  1. Add an environment variable called DANGER_GITLAB_API_TOKEN with a personal API token to your fork that has the api scope set.
  2. Making the variable masked makes sure it doesn't show up in the job logs. The variable cannot be protected, as it needs to be present for all feature branches.