databricks-multi-env-setup
Configure Databricks across development, staging, and production environments. Use when setting up multi-environment deployments, configuring per-environment secrets, or implementing environment-specific Databricks configurations. Trigger with phrases like "databricks environments", "databricks staging", "databricks dev prod", "databricks environment setup", "databricks config by env".
Install
mkdir -p .claude/skills/databricks-multi-env-setup && curl -L -o skill.zip "https://mcp.directory/api/skills/download/2740" && unzip -o skill.zip -d .claude/skills/databricks-multi-env-setup && rm skill.zipInstalls to .claude/skills/databricks-multi-env-setup
About this skill
Databricks Multi-Environment Setup
Overview
Configure Databricks across development, staging, and production environments with isolated API keys, environment-specific settings, and proper secret management. Each environment gets its own credentials and configuration to prevent cross-environment data leakage.
Prerequisites
- Separate Databricks API keys per environment
- Secret management solution (environment variables, Vault, or cloud secrets)
- CI/CD pipeline with environment-aware deployment
- Application with environment detection logic
Environment Strategy
| Environment | Purpose | API Key Source | Settings |
|---|---|---|---|
| Development | Local development | .env.local | Debug enabled, relaxed limits |
| Staging | Pre-production testing | CI/CD secrets | Production-like settings |
| Production | Live traffic | Secret manager | Optimized, hardened |
Instructions
Step 1: Configuration Structure
config/
databricks/
base.ts # Shared defaults
development.ts # Dev overrides
staging.ts # Staging overrides
production.ts # Prod overrides
index.ts # Environment resolver
Step 2: Base Configuration
// config/databricks/base.ts
export const baseConfig = {
timeout: 30000, # 30000: 30 seconds in ms
maxRetries: 3,
cache: {
enabled: true,
ttlSeconds: 300, # 300: timeout: 5 minutes
},
};
Step 3: Environment-Specific Configs
// config/databricks/development.ts
import { baseConfig } from "./base";
export const developmentConfig = {
...baseConfig,
apiKey: process.env.DATABRICKS_TOKEN_DEV,
debug: true,
cache: { enabled: false, ttlSeconds: 60 },
};
// config/databricks/staging.ts
import { baseConfig } from "./base";
export const stagingConfig = {
...baseConfig,
apiKey: process.env.DATABRICKS_TOKEN_STAGING,
debug: false,
};
// config/databricks/production.ts
import { baseConfig } from "./base";
export const productionConfig = {
...baseConfig,
apiKey: process.env.DATABRICKS_TOKEN_PROD,
debug: false,
timeout: 60000, # 60000: 1 minute in ms
maxRetries: 5,
cache: { enabled: true, ttlSeconds: 600 }, # 600: timeout: 10 minutes
};
Step 4: Environment Resolver
// config/databricks/index.ts
import { developmentConfig } from "./development";
import { stagingConfig } from "./staging";
import { productionConfig } from "./production";
type Environment = "development" | "staging" | "production";
const configs = {
development: developmentConfig,
staging: stagingConfig,
production: productionConfig,
};
export function detectEnvironment(): Environment {
const env = process.env.NODE_ENV || "development";
if (env === "production") return "production";
if (env === "staging" || process.env.VERCEL_ENV === "preview") return "staging";
return "development";
}
export function getDatabricksConfig() {
const env = detectEnvironment();
const config = configs[env];
if (!config.apiKey) {
throw new Error(`DATABRICKS_TOKEN not set for environment: ${env}`);
}
return { ...config, environment: env };
}
Step 5: Secret Management
# Local development (.env.local - git-ignored)
DATABRICKS_TOKEN_DEV=your-dev-key
# GitHub Actions
# Settings > Environments > staging/production > Secrets
# Add DATABRICKS_TOKEN_STAGING and DATABRICKS_TOKEN_PROD
# AWS Secrets Manager
aws secretsmanager create-secret \
--name databricks/production/api-key \
--secret-string "your-prod-key"
# GCP Secret Manager
echo -n "your-prod-key" | gcloud secrets create databricks-api-key-prod --data-file=-
# .github/workflows/deploy.yml
jobs:
deploy-staging:
environment: staging
env:
DATABRICKS_TOKEN_STAGING: ${{ secrets.DATABRICKS_TOKEN_STAGING }}
deploy-production:
environment: production
env:
DATABRICKS_TOKEN_PROD: ${{ secrets.DATABRICKS_TOKEN_PROD }}
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| Wrong environment | Missing NODE_ENV | Set environment variable in deployment |
| Secret not found | Wrong secret path | Verify secret manager configuration |
| Cross-env data leak | Shared API key | Use separate keys per environment |
| Config validation fail | Missing field | Add startup validation with Zod schema |
Examples
Quick Environment Check
const config = getDatabricksConfig();
console.log(`Running in ${config.environment}`);
console.log(`Cache enabled: ${config.cache.enabled}`);
Startup Validation
import { z } from "zod";
const configSchema = z.object({
apiKey: z.string().min(1, "DATABRICKS_TOKEN is required"),
environment: z.enum(["development", "staging", "production"]),
timeout: z.number().positive(),
});
const config = configSchema.parse(getDatabricksConfig());
Resources
Next Steps
For deployment, see databricks-deploy-integration.
Output
- Configuration files or code changes applied to the project
- Validation report confirming correct implementation
- Summary of changes made and their rationale
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