How to Orchestrate our DBT Batch Jobs to be Resilient to Single Data Source Failures?

As a Data Engineer, I would like to understand how we can orchestrate our DBT batch jobs to be resilient to single data source failures. Currently, our production run job is structured so that a failure in a staging model will impact subsequent models, even if they are not dependencies. Please offer any insights or best practice guidance you may have.