Account settings in dbt Cloud

The following sections describe the different Account settings available from your dbt Cloud account in the sidebar (under your account name on the lower left-hand side).

Example of Account settings from the sidebar

Git repository caching enterprise

At the start of every job run, dbt Cloud clones the project's Git repository so it has the latest versions of your project's code and runs dbt deps to install your dependencies.

For improved reliability and performance on your job runs, you can enable dbt Cloud to keep a cache of the project's Git repository. So, if there's a third-party outage that causes the cloning operation to fail, dbt Cloud will instead use the cached copy of the repo so your jobs can continue running as scheduled.

dbt Cloud caches your project's Git repo after each successful run and retains it for 8 days if there are no repo updates. It caches all packages regardless of installation method and does not fetch code outside of the job runs.

dbt Cloud will use the cached copy of your project's Git repo under these circumstances:

• Outages from third-party services (for example, the dbt package hub).
• Git authentication fails.
• There are syntax errors in the packages.yml file. You can set up and use continuous integration (CI) to find these errors sooner.
• If a package doesn't work with the current dbt version. You can set up and use continuous integration (CI) to identify this issue sooner.

To use, select the Enable repository caching option from your account settings.

Example of the Enable repository caching option

Partial parsing

At the start of every dbt invocation, dbt reads all the files in your project, extracts information, and constructs an internal manifest containing every object (model, source, macro, and so on). Among other things, it uses the ref(), source(), and config() macro calls within models to set properties, infer dependencies, and construct your project's DAG. When dbt finishes parsing your project, it stores the internal manifest in a file called partial_parse.msgpack.

Parsing projects can be time-consuming, especially for large projects with hundreds of models and thousands of files. To reduce the time it takes dbt to parse your project, use the partial parsing feature in dbt Cloud for your environment. When enabled, dbt Cloud uses the partial_parse.msgpack file to determine which files have changed (if any) since the project was last parsed, and then it parses only the changed files and the files related to those changes.

Partial parsing in dbt Cloud requires dbt version 1.4 or newer. The feature does have some known limitations. Refer to Known limitations to learn more about them.

To use, select the Enable partial parsing between deployment runs option from your account settings.

Example of the Enable partial parsing between deployment runs option

Account access to Advanced CI features enterprise

Advanced CI features, such as compare changes, allow dbt Cloud account members to view details about the changes between what's in the production environment and the pull request.

To use Advanced CI features, your dbt Cloud account must have access to them. Ask your dbt Cloud administrator to enable Advanced CI features on your account, which they can do by choosing the Enable account access to Advanced CI option from the account settings.

Once enabled, the Run compare changes option becomes available in the CI job settings for you to select.

Example of the Enable account access to Advanced CI option