Databricks-DE-Pro Cost and Performance Optimization Practice Question
An organization wants to monitor and limit the spend of their Databricks SQL warehouses. Which feature is most appropriate for setting alerts when costs exceed a certain threshold?
⚠ Common exam trap
Candidates often confuse cluster auto-termination policies with Unity Catalog permissions, forgetting that account-level budget policies are specifically designed for spend monitoring and alerts.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Implement Budget Policies in the Databricks account console to set alerts on usage.
Databricks provides budget policies and administrative controls to manage costs. Setting up budget alerts via the Databricks account console allows administrators to define spending limits and receive notifications when consumption approaches these levels. This proactive monitoring is essential for governance, ensuring that cost overruns are identified early and addressed by the relevant teams, preventing unexpected bills and promoting responsible use of compute resources across the organization.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable auto-termination on every individual query executed.
Why it's wrong here
Auto-termination applies to the warehouse level when idle, not to individual queries. There is no feature to automatically terminate a query based on its cost until it has finished, and attempting to manage costs at the per-query level would disrupt the functionality of the SQL warehouse entirely.
- ✗
Use the Databricks Billing System to set a hard limit that automatically shuts down the account.
Why it's wrong here
While you can monitor costs, there is no 'hard limit' feature that shuts down the entire account automatically upon hitting a budget. Budget alerts are notification-based, requiring manual intervention or automation via APIs to stop workloads. A hard shutdown would likely disrupt production systems, which is not recommended.
- ✓
Implement Budget Policies in the Databricks account console to set alerts on usage.
Why this is correct
Budget policies in the Databricks account console allow administrators to define budgets and receive proactive alerts. This is the official and most effective way to track consumption and manage costs across different workspaces, providing the visibility needed to prevent excessive spending before it impacts the monthly cloud bill.
- ✗
Manually check the Spark UI after every query to calculate the cost.
Why it's wrong here
Manually checking the Spark UI after every query is impractical and inefficient. It does not provide an automated way to monitor total spend or set alerts. This approach is prone to human error and cannot scale to teams with many concurrent users or automated, high-frequency analytical workloads.
About these practice questions
This Databricks-DE-Pro question is part of Courseiva's 267-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-DE-Pro practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-DE-Pro exam.