Databricks ML-PRO Asset Bundles for ML Assets Guide
April 13, 2026
Study Databricks ML-PRO Asset Bundles for ML Assets: key concepts, common traps, and exam decision cues.
On this page
Environment questions are where many strong modelers become weak production engineers. Databricks wants environment isolation and asset promotion that survive repeated releases.
Environment map
Requirement
Better first instinct
define and deploy ML assets across environments
Databricks Asset Bundles
separate dev, test, and prod responsibilities
explicit environment architecture
deploy experiments, registered models, or endpoints repeatably
target-aware bundle configuration
What the exam is really testing
If the stem says…
Strong reading
“define and configure Databricks ML assets using DABs”
multiple asset types may move through the same promotion system
Decision order that usually wins
Start with environment separation, not notebook convenience.
Decide which assets must move together across dev, test, and prod.
Use Asset Bundles to make that promotion repeatable and target-aware.
Keep environment-specific differences in configuration, not hard-coded logic.
Treat repeatable deployment as part of ML quality, not a later ops add-on.
ML-PRO treats environment architecture as a production control, not a packaging detail. The better answer usually reduces manual workspace drift and makes promotion reproducible.
Scenario triage
Scenario
Better first move
ML assets must be deployed repeatably across environments
use Databricks Asset Bundles
prod and dev use different manual notebook steps
replace them with target-aware config
experiments, models, and endpoints must move under one release pattern
bundle the relevant assets intentionally
team collapses all work into one shared workspace habit
restore environment isolation
Common traps
Trap
Better rule
hard-coding environment differences into notebooks
promotion should be target-aware and repeatable
treating bundles as optional decoration
Databricks uses them as a real deployment control surface
collapsing dev and prod behavior into one workspace habit