How to deploy Data Kits with Gearset

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Data Kits in Salesforce Data 360 are a specialized packaging mechanism used to streamline the deployment and management of your Data 360 configuration across different environments (e.g. from sandbox to production). They ensure that all interdependent Data 360 components deploy reliably and in the correct order, separate from traditional Salesforce platform metadata.

Gearset simplifies the Data Kit deployment. With intuitive comparison and deployment workflows, users can effectively move complex Data 360 metadata configuration between development, testing, and production instances.

Before deploying Data Kits, you will need to enable Data Cloud in both source and target orgs. You may also need to assign the Data Cloud Admin permission set to your deployment user.

In your pipeline, click on the sandbox where you created the Data Kit. Create a new feature branch.

Input the details of your feature branch like the branch name and associated ticket/work item. Switch to an "on-demand" comparison, and click compare now.

Once the comparison is opened, click into the comparison filter.

There is a specific section for Data 360 metadata, where you will find a list of your Data Kits. You will be able to search this list for the specific Data Kit that you want to deploy.

Selecting your Data Kit will tell Gearset to retrieve the components, which you will see on screen as a list.

Once you confirm that selection by clicking "+Add data kit to package" the chosen Data Kit and all of its components will be added to your comparison.

Click "Compare now" and the focused comparison will be created. This comparison includes your specified Data Kit, its components and dependencies. Select the Data Kit, and Data Kit Components.

After making your selections, click Next.

You might see some problem analyzer suggested fixes if you are missing any dependencies. Add the missing components to the deployment and go to the Pre-deployment Summary.

Gearset will display a summary of the commit. Make sure to add your issue tracking for Jira/Asana/Azure if you use it, and any notes you want to make about the commit.

Once you're returned to the main pipelines view, click Create pull request.

After you've added any descriptive details, open the Deployment steps tab, and add a post-deployment step to activate the Data Kit automatically after the deployment completes.

A note on the term "activation": the technically correct term for what Gearset does to your Data Kit automatically post-deployment is "publish" or "Data Kit deploy", but to avoid confusion between the act of making the deployment to the target org vs making the Data Kit components available in the target org, we have chosen to refer to this action as "activation". This matches the other automatic post deployment steps where we activate Flows or Agentforce agents. Thus when we refer to the action of deploying the data kit, we are specifically talking about a deployment in the traditional sense, where a package of changes is sent to a target org and applied.

After the step has been added, create your pull request. This will trigger the automatic validation of the Data Kit. If that passes validation (and all other checks on the pull request pass) then you will be able to promote the change, and the Data Kit activation will run automatically once that deployment completes.

The pull request automatically opens against the next environment, complete with the post-deployment step. This will allow you to deploy the same Data Kit uniformly throughout your pipeline.

Before you run a comparison, select "on-demand comparison" and open up the custom filter.

There is a specific section for Data 360 metadata, where you will find a list of your Data Kits. You will be able to search this list for the specific Data Kit that you want to deploy.

Selecting your Data Kit will tell Gearset to retrieve the components, which you will see on screen as a list.

Once you confirm that selection by clicking "+Add data kit to package" the chosen Data Kit and all of its components will be added to your comparison.

Click "Compare now" and the focused comparison will be created. This comparison includes your specified Data Kit, its components and dependencies. Select the Data Kit, and Data Kit Components.

After making your selections, click Next.

You might see some problem analyzer suggested fixes if you are missing any dependencies. Add the missing components to the deployment and go to the Pre-deployment Summary.

Gearset will display a summary of the deployment package. Make sure to add your issue tracking for Jira/Asana/Azure and any notes you want to make about the deployment.

The technically correct term for what Gearset does to your Data Kit automatically post-deployment is "publish" or "Data Kit deploy", but to avoid confusion between the act of making the deployment to the target org vs making the Data Kit components available in the target org, we have chosen to refer to this action as "activation" to match the other automatic post deployment steps where we activate Flows or Agentforce agents. Thus when we refer to the action of deploying the data kit, we are specifically talking about a deployment in the traditional sense, where a package of changes is sent to a target org and applied.

On the summary of items to deploy page, the Activate Data Kits after deployment option is by default set to "on" to make sure that the components you are deploying are made available in the target org as soon as possible post-deployment.

If you choose to toggle this off, and later decide that you would like Gearset to activate your Data Kit you can locate the deployment in your deployment history and use the Activate deployed Data Kits button.

We will then display a message if this is successful:

"Activation has started. It may take a few minutes for all of your Data Kits to become active in the target org."