This article will run through the steps to set up a pipeline in Gearset.

To set up a Gearset Pipeline, navigate to the side menu on the top left corner in our app, and under Continuous Delivery select Pipelines:

This will take you to the Deployment pipelines landing page.
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Select Create a pipeline to get started!

You'll then be taken to the pipeline setup wizard.
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This page will prompt you to enter a Pipeline name, and you'll need to decide whether your pipeline will be team-shared or user-owned. Our recommendation is to use a team-shared pipeline.

In the next step, you'll be prompted to set up your repository.
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This includes selecting your Git provider, repository, and the default base branch for your repository.
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First, select your Git provider. You'll need to link the Git provider you're using to your Gearset account if you haven't done so already.
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For guidance on how to add source control connections, follow our guide here.

Once you've connected your Git provider to your Gearset account, select the repository you'll use for this pipeline.

If you haven't created a repository yet, you'll need to create one first. The exact instructions vary with each Git provider, and for more information, check out our guide on how to set up a new source control repository.

Once a Git provider and repository have been added, the next step is to select a Default base branch for new features.
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Usually, this is Main or Master. For more information on this, check out our document on the pipelines branching model.

The next step is to populate your repository. This means populating your main branch with a baseline of metadata.
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Best practice states that your main branch in your Git repository should be your source of truth, which is why you should populate this branch from your Production org in order to capture and track the latest changes.
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You can use our Default comparison filter (63 metadata types) as a starting point, and make changes to this filter based on which types you actually modify.

We recommend that you keep the metadata filter as wide and all encompassing as possible, and then make exclusions based on the metadata type(s) you don’t need. However, we recommend excluding a certain subset of metadata that may introduce problems down the line.

For more information, we recommend reading through our guide what metadata types should I include for Gearset pipelines?

In this step, you can optionally add issue tracking to your pipeline.

Don't worry if you haven't made any decisions on issue tracking just yet; you may always add this in at a later date.
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If you'd like to add issue tracking, tick Link features to user stories and then select your issue tracker.

You'll need to connect your Jira or ADO to do this. We have guides on integrating with Jira and updating an azure work item's status in pipelines that will help you with this.

Select which format you want your feature branches to use (read more about this feature here). You may see a preview of what this format looks like underneath your selection:

Lastly, we'll configure our pull requests.

Here, you may choose whether your pull requests Require a description, or Copy reviewers when promoting a PR through environments.

You may change these settings at a later date if you are unsure.

Congratulations! You have now created your first Gearset pipeline using the pipeline wizard.

Now, you'll be prompted to create your first static environment to automatically deploy changes to an org from a long-lived branch.

For help on this, check out our guide on setting up your first CI job in Gearset.