databricks-spark-structured-streaming
Pass
Audited by Gen Agent Trust Hub on Apr 8, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill demonstrates secure credential management by using
dbutils.secrets.get()to retrieve Kafka authentication details rather than hardcoding them, aligning with security best practices. - [SAFE]: Data ingestion patterns (Kafka, Auto Loader) use explicit schema definitions with
from_jsonand provide patterns for schema validation and routing invalid records to a Dead Letter Queue (DLQ), mitigating risks from malformed external data. - [SAFE]: File system operations utilize standard Databricks utilities (
dbutils.fs) and follow recommended storage patterns using Unity Catalog Volumes and persistent paths, ensuring data integrity and proper access controls. - [SAFE]: The skill uses established open-source and vendor-provided libraries including
pysparkanddelta-sparkfor all data processing and table management operations.
Audit Metadata