I had created a data stream with snowflake connector. I am trying to deploy it with the data kit.
I have followed these steps.
1- I have created a devops data kit type.
2- Added data stream to the data kit. DMO is added with data stream.
3- I download the package from manifest file.
4- Authorize the VS code with source org.
5- Retrieve the component in VS code with package.xml.
6- Change the org in vs code to target org.
7- Deployed the components in the target org with package.xml.
8- On the target org. I can see the data kit but when i clicked on data kit deploy. It got failed with error.
"DataKit Job Failed due to Internal Error. Please reach out to support team with ID:" Can anyone help me on this error?
Is this correct way for data cloud deployment or do we have any other way to deploy with the help of data kit.
In my project, I encountered a similar situation where we were unable to promote Data Kits to other Salesforce instances, whether it was a Partial Copy or a Full Copy sandbox. We reached out to Salesforce Support, but they didn’t have a clue. From my perspective, combining Salesforce CLI, VS Code, and AI
is the best approach to successfully deploy Data Kits.
The Issue
Salesforce generates a single package.xml file for the DevOps Data Kit. While it contains all the items required for deployment, the deployment itself fails due to underlying Salesforce platform limitations and bugs.
The Resolution
- Extract the Data Kit package.xml file.
- Retrieve all metadata from your source organization.
- Run a validation against the destination organization.
- Capture all the deployment errors you receive.
- Feed the package.xml and error screenshots into an AI tool, then ask it to split the main package.xml into smaller, logical parts for deployment. Note: This step involves some trial and error. If you are lucky, you will get it right on the first try; otherwise, it might take 2 to 3 iterations.
- Deploy the single Data Kit in phases based on the split versions of the package.xml generated by the AI, bypassing the single-file method provided by Salesforce.
Additional Context
When you open a Salesforce Support ticket for assistance, they rarely know how to fix this particular issue. Eventually, they suggested we use Change Sets to promote the changes. However, manually selecting Data Kit dependencies is incredibly tedious—in our case, a single Data Kit had 1,000+ dependencies
. By using AI to break down the massive package into manageable parts, I successfully promoted our changes all the way to Production without any issues.
Probable Root Cause
Salesforce launched Data Cloud in a rush. I noticed a very similar pattern when they launched Community Cloud back in 2013, where we faced persistent deployment issues for it all the way up until 2020 and the main issue was promoting dependencies in sequence. same we are noticing in data kit deployments.
