Databricks Multi Env Setup

Databricks Multi-Environment Setup

Overview

Configure Databricks across dev, staging, and production with isolated workspaces (or catalog-level isolation), per-environment secrets, Asset Bundle targets, and Terraform for workspace provisioning. Each environment gets its own credentials, Unity Catalog namespace, and compute policies.

Prerequisites

• Databricks account with multiple workspaces (or Premium for catalog-level isolation)
• Service principals per environment
• Secret management (Databricks Secret Scopes, AWS Secrets Manager, or GCP Secret Manager)
• CI/CD pipeline (GitHub Actions, Azure DevOps, etc.)

Environment Strategy

Instructions

Step 1: CLI Profiles per Environment

# ~/.databrickscfg
[dev]
host = https://adb-dev-workspace.7.azuredatabricks.net
token = dapi_dev_token

[staging]
host = https://adb-staging-workspace.7.azuredatabricks.net
client_id = staging-sp-client-id
client_secret = staging-sp-secret

[production]
host = https://adb-prod-workspace.7.azuredatabricks.net
client_id = prod-sp-client-id
client_secret = prod-sp-secret

# Use a specific environment
databricks workspace list / --profile staging
databricks clusters list --profile production

Step 2: Asset Bundle Targets

# databricks.yml — single project, multiple targets
bundle:
  name: data-platform

variables:
  catalog:
    description: Unity Catalog for this environment
    default: dev_catalog
  alert_email:
    default: dev@company.com
  cluster_size:
    default: "2X-Small"

targets:
  dev:
    default: true
    mode: development
    workspace:
      host: https://adb-dev-workspace.7.azuredatabricks.net
      root_path: /Users/${workspace.current_user.userName}/.bundle/${bundle.name}/dev
    variables:
      catalog: dev_catalog

  staging:
    workspace:
      host: https://adb-staging-workspace.7.azuredatabricks.net
      root_path: /Shared/.bundle/${bundle.name}/staging
    variables:
      catalog: staging_catalog
      alert_email: staging-alerts@company.com

  prod:
    mode: production
    workspace:
      host: https://adb-prod-workspace.7.azuredatabricks.net
      root_path: /Shared/.bundle/${bundle.name}/prod
    variables:
      catalog: prod_catalog
      alert_email: oncall@company.com
      cluster_size: "Medium"

Step 3: Per-Environment Secret Scopes

# Create environment-specific secret scopes in each workspace
for env in dev staging prod; do
    databricks secrets create-scope "${env}-secrets" --profile $env
    databricks secrets put-secret "${env}-secrets" db-password --profile $env
    databricks secrets put-secret "${env}-secrets" api-key --profile $env
done

# Access secrets in notebooks — scope name matches environment
import os

env = os.getenv("ENVIRONMENT", "dev")
db_password = dbutils.secrets.get(scope=f"{env}-secrets", key="db-password")
api_key = dbutils.secrets.get(scope=f"{env}-secrets", key="api-key")

Step 4: Environment-Aware Python Config

# config/databricks_config.py
from dataclasses import dataclass
import os

@dataclass
class DatabricksEnvConfig:
    host: str
    catalog: str
    secret_scope: str
    debug: bool
    max_retries: int
    timeout_seconds: int

CONFIGS = {
    "dev": DatabricksEnvConfig(
        host=os.getenv("DATABRICKS_HOST_DEV", ""),
        catalog="dev_catalog",
        secret_scope="dev-secrets",
        debug=True,
        max_retries=3,
        timeout_seconds=30,
    ),
    "staging": DatabricksEnvConfig(
        host=os.getenv("DATABRICKS_HOST_STAGING", ""),
        catalog="staging_catalog",
        secret_scope="staging-secrets",
        debug=False,
        max_retries=3,
        timeout_seconds=60,
    ),
    "prod": DatabricksEnvConfig(
        host=os.getenv("DATABRICKS_HOST_PROD", ""),
        catalog="prod_catalog",
        secret_scope="prod-secrets",
        debug=False,
        max_retries=5,
        timeout_seconds=120,
    ),
}

def get_config() -> DatabricksEnvConfig:
    env = os.getenv("ENVIRONMENT", "dev")
    config = CONFIGS.get(env)
    if not config:
        raise ValueError(f"Unknown environment: {env}")
    if not config.host:
        raise ValueError(f"DATABRICKS_HOST_{env.upper()} not set")
    return config

Step 5: CI/CD with Environment Secrets

# .github/workflows/deploy.yml
name: Deploy Pipeline

on:
  push:
    branches: [main]

jobs:
  deploy-staging:
    runs-on: ubuntu-latest
    environment: staging
    steps:
      - uses: actions/checkout@v4
      - uses: databricks/setup-cli@main
      - run: databricks bundle deploy -t staging
        env:
          DATABRICKS_HOST: ${{ secrets.DATABRICKS_HOST }}
          DATABRICKS_CLIENT_ID: ${{ secrets.DATABRICKS_CLIENT_ID }}
          DATABRICKS_CLIENT_SECRET: ${{ secrets.DATABRICKS_CLIENT_SECRET }}

  deploy-production:
    needs: deploy-staging
    runs-on: ubuntu-latest
    environment: production  # Requires manual approval
    steps:
      - uses: actions/checkout@v4
      - uses: databricks/setup-cli@main
      - run: databricks bundle deploy -t prod
        env:
          DATABRICKS_HOST: ${{ secrets.DATABRICKS_HOST_PROD }}
          DATABRICKS_CLIENT_ID: ${{ secrets.DATABRICKS_CLIENT_ID_PROD }}
          DATABRICKS_CLIENT_SECRET: ${{ secrets.DATABRICKS_CLIENT_SECRET_PROD }}

Step 6: Terraform for Workspace Provisioning (Optional)

# terraform/main.tf
resource "databricks_workspace" "staging" {
  provider                = databricks.accounts
  workspace_name          = "data-platform-staging"
  aws_region             = "us-east-1"
  pricing_tier           = "PREMIUM"
  deployment_name        = "data-platform-staging"
  managed_services_customer_managed_key_id = var.cmk_id
}

resource "databricks_catalog" "staging" {
  provider = databricks.staging
  name     = "staging_catalog"
  comment  = "Staging environment catalog"
}

resource "databricks_schema" "staging_bronze" {
  provider   = databricks.staging
  catalog_name = databricks_catalog.staging.name
  name       = "bronze"
}

Output

• CLI profiles configured per environment (~/.databrickscfg)
• Asset Bundle with dev/staging/prod targets and variable overrides
• Per-environment secret scopes with isolated credentials
• Python config class for environment-aware code
• CI/CD pipeline with GitHub environment secrets and approval gates

Error Handling

Examples

Quick Environment Verification

for profile in dev staging production; do
    echo "=== $profile ==="
    databricks current-user me --profile $profile 2>/dev/null && echo "OK" || echo "FAILED"
done

Startup Validation

config = get_config()
print(f"Environment: {os.getenv('ENVIRONMENT', 'dev')}")
print(f"Catalog: {config.catalog}")
print(f"Debug: {config.debug}")

Resources

• Declarative Automation Bundles
• CLI Authentication
• Terraform Provider

Next Steps

For deployment, see databricks-deploy-integration.