Configuration Reference

Ready-to-use configurations, cluster settings, YAML snippets, and environment setups.

8 categories Updated Aug 2026
 Azure Databricks

Cluster Configuration — ETL Workloads

Optimised cluster config for large-scale PySpark ETL: node types, autoscaling, Spark settings.

Coming Soon

Databricks Secrets & Key Vault Integration

Linking Azure Key Vault secret scopes to Databricks for secure credential management.

Coming Soon

Unity Catalog Setup — Metastore & Permissions

Step-by-step Unity Catalog metastore configuration, workspace binding, and RBAC setup.

Coming Soon

Databricks Asset Bundles (DABs) — Project Structure

Reference project layout and databricks.yml for deploying jobs and notebooks via DABs.

Coming Soon
 Snowflake

Snowflake Connection — Python & Spark Connector

Connection string templates and authentication patterns for Python, PySpark, and ADF.

Coming Soon
 Azure Data Factory

Linked Service Templates — ADLS, SQL, Databricks

ARM-ready linked service JSON for ADLS Gen2, Azure SQL, Databricks, and Snowflake.

Coming Soon
 Azure DevOps / CI-CD

Databricks CI/CD Pipeline — azure-pipelines.yml

Full YAML pipeline: lint, test, bundle, and deploy Databricks jobs via DABs.

Coming Soon
 VS Code Settings

settings.json — Data Engineering Setup

Recommended VS Code settings for Python, PySpark, YAML, SQL, and Databricks extension.

Coming Soon
 Multi-Agent Templates

Orchestrator Agent — Design Template

State schema, routing logic, and retry strategy for the Orchestrator agent.

New
 Git Configuration

.gitconfig & Branching Strategy

Global git config, aliases, and branching conventions for data engineering projects.

Coming Soon
 Apache Airflow

DAG Templates — Databricks Job Trigger

Airflow DAG to trigger and monitor Databricks jobs with retry and alerting config.

Coming Soon