Deployment Overview
Deployment creates the structural foundation of your data pipeline. When you deploy, Coalesce analyzes the differences between your current Environment and your desired configuration, then executes the necessary changes.
Once you've completed Setting Up Your Project and Building Your Pipeline, you're ready to deploy your Pipeline to your data warehouse.
Deployment Methods
You can deploy your pipeline using:
Before You Deploy
This assumes you've created your data pipeline. If you don't have one, check out the Quick Start Guide.
- Configure your Environment
- Configure your Git Integration
- Exclude Nodes from Deployment (optional)
- Set your Parameters (optional)
- You can set them on the environment level or during the deploy processes.
- Deploy your pipeline. You can use the following:
📄️ Deploy Using the CLI
Deploy Coalesce data transformation environments using the command-line interface (CLI) tool. Comprehensive guide covering CLI setup, deployment plan creation, environment configuration, and automated deployment workflows for enterprise data warehouse management and DevOps integration.
📄️ Deploy Using the Coalesce App
Deploy data transformation pipelines to environments using the Coalesce application interface. Step-by-step guide covering deployment wizard navigation, package selection, parameter configuration, and deployment plan review for successful enterprise data warehouse deployments and environment management.
📄️ Excluding Nodes From Deployment
Configure selective node deployment in Coalesce data transformation pipelines by excluding specific nodes from deployment operations. Learn to manage deployment scope, control pipeline deployment granularity, and implement selective deployment strategies for enterprise data warehouse management.
📄️ Rollback a Deployment
Execute deployment rollbacks in Coalesce data transformation platform to restore previous environment states. Learn rollback procedures, data structure restoration, and deployment recovery strategies for maintaining enterprise data warehouse stability and managing deployment failures.