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Glossary

CD Overview

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Última atualização: 2026-10-09 16:13:38

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What Is CI/CD
CI/CD (Continuous Integration, Continuous Delivery) is a development practice that delivers software in short cycles and at high frequency through automated pipelines. In DataBuddy, CI/CD enables data engineers to manage data workflows like software code: through Bundle, workflow configurations are file-based and versioned, and combined with Git to achieve automated deployment across multiple environments.
Features
Capability
Description
Bundle package management
Define resources such as workflows, tasks, and parameters as YAML configuration files to implement Infrastructure as Code.
Multi-environment deployment
Achieve multi-environment deployment with a single configuration through Targets configurations (dev / staging / prod), where each environment can use an independent Workspace and variables.
CLI command-driven
Provides a series of databuddy bundle commands that support complete lifecycle operations such as initialization, validation, deployment, running, and termination.
Variable override
Supports dynamically overriding variable values in the command line through the --var parameter without modifying configuration files.
Git integration
Supports hosting Bundle projects in Git repositories and implementing automated deployment through CI/CD pipelines (GitHub Actions / GitLab CI).
Version traceability
Each deployment automatically records the deployment status and Git metadata, supporting traceability and auditing.
Key Concepts
To understand the CI/CD module, you need to be familiar with the following core concepts:
Bundle: an asset package in DataBuddy that contains workflow configurations (YAML), code files (Notebook / SQL / Python), and deployment metadata. It is equivalent to Databricks Asset Bundles.
Target: the target environment for deployment, such as dev (development), staging (pre-release), and prod (production). Each Target can be independently configured with Workspace, variables, and permissions.
Resource: a resource entity defined in a Bundle. It currently supports the Workflow type, and a workflow can contain multiple task types such as Notebook, SQL, Python, nested workflows, and data quality.
Profile: a local identity authentication configuration stored in ~/.databuddycfg, containing the Workspace address and authentication credentials.
databuddy CLI: a command-line tool provided by DataBuddy for full lifecycle management of Bundles.
Applicable Scenarios
Scenario
Applicable Method
Recommended Feature
Multi-person collaborative development
Each person uses an independent dev Target, and after code is merged, it is uniformly deployed to production.
Develop with Bundle
Isolated multi-environment deployment
Switch between development / testing / production environments through Target variables.
Bundle package definition
Automated release with Git
Pushing to a specific branch automatically triggers deployment, and the code automatically goes live after passing review.
Git-integrated development
Workflow configuration versioning
Incorporate workflow configurations into Git version control for traceability and rollback.
Bundle commands
Architecture Overview
The overall workflow of DataBuddy CI/CD is as follows:
Phase
Operation
Description
1. Install CLI.
curl ... | sudo sh
Install the databuddy command-line client.
2. Log In and Authenticate.
databuddy auth login
Redirect to the DataBuddy login page to complete identity authentication.
3. Initialize Bundle.
databuddy bundle init
Select a template (SQL / Notebook / Minimal) to create a Bundle project.
4. Define Resources.
Edit YAML + code.
Define workflows in resources/workflow/ and write code in src/.
5. Validate Configuration.
databuddy bundle validate
Validate YAML syntax and resource references.
6. Deploy.
databuddy bundle deploy -t dev
Deploy the Bundle content to the target environment.
7. Run.
databuddy bundle run workflow <key>
Run the workflow in the target environment.
Sub-Feature Navigation
Sub-feature
Description
Documentation
Use Cases
Demonstrate the complete end-to-end workflow of Bundle development and Git integration.
-
Bundle Package Definition
Detailed explanation of YAML configuration file structure, fields, and multi-environment configuration
Bundle package definition
Bundle Commands
Complete CLI command reference, including installation, authentication, deployment, and running
Bundle commands
Recommended Learning Path
If you are using the CI/CD feature for the first time, read the following sections in order:
1. Learn Core Concepts: this section
2. Hands-On Practice: Develop with Bundle (complete an end-to-end deployment)
3. Master Configuration Syntax: Bundle Definition
4. Command Reference: Bundle Commands
5. Integrate Git Pipelines: Git-Integrated Development
References
Bundle Definition
Bundle Commands
Workflow Overview

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CD Overview

What Is CI/CD

Features

Key Concepts

Applicable Scenarios

Architecture Overview

Sub-Feature Navigation

Recommended Learning Path

References

Ajuda e Suporte

Capability	Description
Bundle package management	Define resources such as workflows, tasks, and parameters as YAML configuration files to implement Infrastructure as Code.
Multi-environment deployment	Achieve multi-environment deployment with a single configuration through Targets configurations (dev / staging / prod), where each environment can use an independent Workspace and variables.
CLI command-driven	Provides a series of `databuddy bundle` commands that support complete lifecycle operations such as initialization, validation, deployment, running, and termination.
Variable override	Supports dynamically overriding variable values in the command line through the `--var` parameter without modifying configuration files.
Git integration	Supports hosting Bundle projects in Git repositories and implementing automated deployment through CI/CD pipelines (GitHub Actions / GitLab CI).
Version traceability	Each deployment automatically records the deployment status and Git metadata, supporting traceability and auditing.

Scenario	Applicable Method	Recommended Feature
Multi-person collaborative development	Each person uses an independent dev Target, and after code is merged, it is uniformly deployed to production.	Develop with Bundle
Isolated multi-environment deployment	Switch between development / testing / production environments through Target variables.	Bundle package definition
Automated release with Git	Pushing to a specific branch automatically triggers deployment, and the code automatically goes live after passing review.	Git-integrated development
Workflow configuration versioning	Incorporate workflow configurations into Git version control for traceability and rollback.	Bundle commands

Phase	Operation	Description
1. Install CLI.	`curl ... \| sudo sh`	Install the databuddy command-line client.
2. Log In and Authenticate.	`databuddy auth login`	Redirect to the DataBuddy login page to complete identity authentication.
3. Initialize Bundle.	`databuddy bundle init`	Select a template (SQL / Notebook / Minimal) to create a Bundle project.
4. Define Resources.	Edit YAML + code.	Define workflows in `resources/workflow/` and write code in `src/`.
5. Validate Configuration.	`databuddy bundle validate`	Validate YAML syntax and resource references.
6. Deploy.	`databuddy bundle deploy -t dev`	Deploy the Bundle content to the target environment.
7. Run.	`databuddy bundle run workflow <key>`	Run the workflow in the target environment.

Sub-feature	Description	Documentation
Use Cases	Demonstrate the complete end-to-end workflow of Bundle development and Git integration.	-
Bundle Package Definition	Detailed explanation of YAML configuration file structure, fields, and multi-environment configuration	Bundle package definition
Bundle Commands	Complete CLI command reference, including installation, authentication, deployment, and running	Bundle commands