Azure Databricks — Deployment

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Deployment

Topic	URL
Configure managed disaster recovery for Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/managed-disaster-recovery
Set up and manage serverless SQL warehouses in Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/sql/serverless
Deploy Azure Databricks workspaces using Azure CLI	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace/azure-cli
Deploy Azure Databricks workspaces via Azure Portal	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace/create-workspace
Deploy Azure Databricks workspaces with PowerShell	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace/powershell
Deploy Databricks stacks using the legacy Stack CLI	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/cli/stack-cli
Deploy MLflow models with legacy Databricks Model Serving	https://learn.microsoft.com/en-us/azure/databricks/archive/legacy-model-serving/model-serving
Implement Git-based CI/CD for Databricks dashboards	https://learn.microsoft.com/en-us/azure/databricks/dashboards/automate/git-support
Export and import Databricks dashboards across workspaces	https://learn.microsoft.com/en-us/azure/databricks/dashboards/automate/import-export
Upgrade Azure Databricks Hive tables to Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/migrate
Use UCX utilities to migrate workspaces to Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/ucx
Run Databricks bundles in air-gapped environments via Docker	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/airgapped-environment
Migrate Databricks bundles to direct deployment engine	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/direct
Deploy and run Declarative Automation Bundles from workspace	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/workspace-deploy
Implement CI/CD pipelines for Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/ci-cd/
Implement CI/CD for Azure Databricks with Azure DevOps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/ci-cd/azure-devops
Design CI/CD workflows and practices on Databricks	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/ci-cd/flows
Use GitHub Actions for CI/CD on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/ci-cd/github
Set up Jenkins-based CI/CD pipelines for Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/ci-cd/jenkins
Automate Databricks Apps deployment with GitHub Actions	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/cicd-github-actions
Prepare workspace and local environment for Databricks Apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/configure-env
Deploy Databricks apps via UI and CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/deploy
Use Declarative Automation Bundles with Databricks VS Code	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/vscode-ext/bundles
Deploy custom AI agents using Databricks Apps	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/author-agent
Deploy chat UI agents with Databricks Apps	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/chat-app
Set up CI/CD pipelines for Databricks Apps agents with GitHub Actions	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/cicd-agent-app
Deploy Databricks AI agents using Model Serving	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/deploy-agent
Productionize Databricks Apps agents with governance and scaling	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/productionize-agent
Use Azure Databricks Genie mobile app on iOS and Android	https://learn.microsoft.com/en-us/azure/databricks/genie-one/mobile
Build GitHub ingestion pipelines with Lakeflow Connect	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/github-pipeline
Create managed Google Ads ingestion pipelines	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/google-ads-pipeline
Ingest GA4 data via Lakeflow Connect and BigQuery	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/google-analytics-pipeline
Build HubSpot ingestion pipelines with Lakeflow Connect	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/hubspot-pipeline
Create managed Jira ingestion pipelines in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/jira-pipeline
Automate Azure Databricks job management with CLI, SDK, and REST	https://learn.microsoft.com/en-us/azure/databricks/jobs/automate
Build and run JARs on Databricks serverless compute	https://learn.microsoft.com/en-us/azure/databricks/jobs/how-to/use-jars-in-workflows
Create Databricks-compatible JARs for Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/jar-create
Requirements and constraints for standalone pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/dbsql/compute
Run Databricks pipelines from Jobs, Airflow, or Data Factory	https://learn.microsoft.com/en-us/azure/databricks/ldp/workflows
Deploy provisioned throughput Foundation Model APIs in Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/foundation-model-apis/deploy-prov-throughput-foundation-model-apis
Implement CI/CD for machine learning on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/mlops/ci-cd-for-ml
Automate Databricks MLOps with Stacks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/mlops/mlops-stacks
Use express deployments for Databricks model endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/express-deployments
Start Ray clusters as jobs on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ray/start-ray
Use MLflow 3 deployment jobs for model lifecycle	https://learn.microsoft.com/en-us/azure/databricks/mlflow/deployment-job
Deploy Databricks GenAI apps with automatic tracing	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/prod-tracing
Migrate Databricks HTTP routing to serverless compute	https://learn.microsoft.com/en-us/azure/databricks/query-federation/http-migration
Integrate Databricks Git folders into CI/CD workflows	https://learn.microsoft.com/en-us/azure/databricks/repos/ci-cd
Check Azure Databricks feature availability by region	https://learn.microsoft.com/en-us/azure/databricks/resources/feature-region-support
Understand Azure Databricks platform release windows	https://learn.microsoft.com/en-us/azure/databricks/resources/platform-release
Migrate legacy line charts to new Databricks chart types	https://learn.microsoft.com/en-us/azure/databricks/visualizations/legacy-charts

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MicrosoftDocs/azure-databricks — deployment.md

Azure Databricks — Deployment

Deployment