Databricks-DE-Assoc Governance and Security Practice Question
Which security feature should a data engineer configure to ensure that audit logs from all Databricks workspaces are captured and stored in a single, centralized location?
⚠ Common exam trap
Candidates frequently confuse standard cluster log delivery with audit logs, missing that security events and governance tracking across workspaces require configuring diagnostic logs.
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
✓
Diagnostic logs.
Databricks diagnostic logs are the primary mechanism for collecting security, governance, and operational audit information. By configuring diagnostic log streaming to a centralized location, such as a cloud-native log repository (e.g., Azure Log Analytics or AWS S3), organizations can perform centralized monitoring, anomaly detection, and compliance reporting across their entire Databricks estate, ensuring no audit trail is lost or siloed in individual workspaces.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Cluster event logs.
Why it's wrong here
Cluster event logs are specific to the lifecycle of individual compute resources and are intended for debugging node-level issues. They do not contain the comprehensive security audit trails required for compliance, such as user access patterns or permission changes, which are captured by the broader platform-level diagnostic logging.
- ✓
Diagnostic logs.
Why this is correct
Diagnostic logs are the official channel for exporting audit data from Databricks. By streaming these to a workspace-external destination, administrators can aggregate audit data from multiple workspaces into one place, enabling a unified view of all user activity, configuration changes, and data access events for audit and security analysis.
- ✗
System schema (system.access).
Why it's wrong here
While system schemas provide metadata about access in Unity Catalog, they are not a substitute for full platform-level diagnostic logs. Diagnostic logs capture a much broader range of activities, including workspace-level events and configuration changes that fall outside the scope of the Unity Catalog system audit tables.
- ✗
Workspace-local storage.
Why it's wrong here
Storing logs within workspace-local storage creates a fragmented and insecure audit trail. It makes cross-workspace analysis impossible and risks data loss if a workspace is deleted. Centralized external storage is a fundamental requirement for maintaining a resilient and audit-ready governance framework in any enterprise Databricks deployment.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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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-Assoc 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-Assoc exam.