Databricks DE-ASSOC Production Pipelines Guide

Study Databricks DE-ASSOC Production Pipelines: key concepts, common traps, and exam decision cues.

This section is where DE-ASSOC stops rewarding notebook-only thinking. The exam wants to know whether you can package, deploy, schedule, recover, and observe a real pipeline after the logic already exists.

Work this chapter in order

Lesson Focus
4.1 Asset Bundles Learn what Asset Bundles are solving and how they differ from ad hoc manual deployment.
4.2 Workflows & Jobs Learn how jobs are scheduled, recovered, repaired, and rerun in production.
4.3 Spark UI & Tuning Learn how runtime evidence points to skew, shuffle, or other performance bottlenecks.

Fast routing inside this chapter

If the question is really about… Go first to…
deployment structure, targets, bundle content, or repeatable promotion 4.1 Databricks Asset Bundles and Deployment Structure
scheduling, task dependencies, repair, rerun, or serverless jobs 4.2 Workflows, Scheduling, Repair/Rerun & Serverless Jobs
runtime evidence, stages, tasks, or query bottlenecks 4.3 Spark UI, Query Bottlenecks & Runtime Optimization

What strong answers usually do

  • separate code authoring from deployment packaging
  • distinguish repair or rerun decisions from rebuilding the whole pipeline blindly
  • choose serverless when the question rewards hands-off managed operation
  • read performance evidence before changing runtime settings

In this section

Revised on Sunday, May 10, 2026