Overview
A Datazone project is a Git repository containing your data pipelines, actions, apps, knowledge objects, flows, and endpoints. All project components are defined in a centralconfig.yml file.
Project Structure
my-project
config.yml
pipelines
hello_world.py
data_processing.py
actions
apps
objects
flows
studio
utils.py
- Each project must have a
config.ymlfile - Each pipeline should have a unique alias and be defined in separate files
- Aliases must be unique within
pipelinesand withinstudio_apps - Unknown keys are rejected on deploy rather than ignored, so a typo fails loudly
- You can organize your code with utility files for shared logic
Configuration File
Theconfig.yml file defines all project resources:
config.yml
Configuration Reference
Project Fields
string
required
Name of your project. Used for display and identification.
string
required
Unique identifier for your project. Generated when you create a project.
array
List of data pipeline definitions. Each pipeline processes and transforms data.
array
List of serverless action functions. Actions can be triggered by endpoints or used by AI agents.Learn more in the Actions documentation.
array
List of intelligent AI applications.
array
List of Knowledge Object definitions — versioned business entities with a CRUD API.Removing an entry deletes the object and schedules cleanup of its data. Learn more in the Knowledge Objects documentation.
array
array
List of Studio Apps — React applications built and served by Datazone.Learn more in the Studio Apps documentation.
array
Pipeline Configuration
string
required
Short, unique identifier for the pipeline. Used in CLI commands and UI.
string
required
Relative path to the pipeline Python file from project root.
string
default:"SMALL"
Compute instance size for pipeline execution.Available sizes:
XSMALL- 2 vCPU, 8 GB RAMSMALL- 4 vCPU, 16 GB RAMMEDIUM- 8 vCPU, 32 GB RAMLARGE- 16 vCPU, 64 GB RAMXLARGE- 32 vCPU, 128 GB RAM (Enterprise only)
string
default:"local"
Spark deployment mode for distributed processing.Options:
local- Runs on a single machine (default)client- Driver runs in the same process, executors run separatelycluster- Both driver and executors run in separate processes (Enterprise only)
integer
Number of Spark executors for parallel processing. Only applies when
deploy_mode is client or cluster.object
Additional Spark configuration properties. Pass any custom Spark configuration key-value pairs.
array
Python packages required by the pipeline. Installed before execution.
Python Dependency Fields
string
required
Python package name from PyPI or custom index.
string
Specific package version. If omitted, installs the latest version.
string
Custom Python package index URL. Useful for private packages or mirrors.
array
Additional arguments passed directly to the package installer for this dependency.
Action Configuration
string
required
Relative path to the action Python file containing an Each file should contain one action function. Learn more in the Actions documentation.
@action decorated function.App Configuration
string
required
Relative path to the intelligent app Python file.
Studio App Configuration
string
required
Short, unique identifier for the app. Used in its served URL.
string
Display name shown in Datazone. Defaults to the alias.
string
required
Relative path to the app directory — the folder holding The entry is created for you when you add a Studio App, and removing it deletes the app and its directory. Each app is built per branch; see the Studio Apps documentation.
package.json.Knowledge Object Configuration
string
required
Relative path to the object definition YAML file. One file may hold several objects, separated by Learn more in the Knowledge Objects documentation.
---.Flow Configuration
string
required
Endpoint Configuration
string
required