Deploy Project API

The Deploy Project API allows you to deploy projects with custom pipeline and project configurations to specific fabrics. This is useful when you want to:

• Automate project deployment using external CI/CD tools instead of Prophecy's web interface.
• Deploy the same project to different environments (dev, staging, prod) with different configuration values

The API returns request responses in JSON format.

Requirements

To use the Deploy Project API, the project you want to deploy must:

• Target a fabric that exists in your environment.
• Have at least one Git tag that defines the project version.

Important

Unlike in the Prophecy UI where Git tags are created automatically during publish, when using this API you must create the Git tag externally. The tag must follow the exact format {projectName}/{version}.

---

POST Deploy Project

Endpoint

https://app.prophecy.io/api/deploy/project

info

Replace the base URL with your environment URL for dedicated SaaS and self-hosted deployments.

Request Headers

The following headers are required for the request.

Key	Value	Description
X-AUTH-TOKEN	{{auth_token}}	Your Prophecy access token

Body Parameters

The following are valid parameters for the request body.

Field Name	Type	Required	Description	Example
projectName	String	Yes	Name of the project to be deployed.	CustomerAnalytics
fabricName	String	Yes	Name of the fabric where the project will be deployed.	production-databricks
gitTag	String	Yes	Git tag identifying the specific version of the project to deploy. Must follow the format {projectName}/{version}.	CustomerAnalytics/2.1
pipelineConfigurations	JSON	No	Override default values for specific pipeline parameters. Each pipeline can have multiple parameter overrides. The parameter must exist in the pipeline definition, or the override will be skipped.	{"sales_report": {"report_period": "monthly"}}
projectConfiguration	JSON	No	Override default values for project-level configuration parameters that apply to all pipelines in the project.	{"environment": "production"}

Pipeline Configurations Structure

The pipelineConfigurations parameter allows you to specify pipeline parameter values for individual pipelines within the project. The structure is:

{
  "pipelineName": {
    "parameterName": "parameterValue",
    "anotherParameter": "anotherValue"
  }
}

Where:

• pipelineName is the name of a pipeline within the project
• parameterName is the name of a pipeline parameter
• parameterValue is the value to assign to that parameter

info

You only need to specify the parameters you want to override. Any parameters not specified will use their default values from the pipeline definition. You can override just one parameter or multiple parameters as needed.

Project Configuration Structure

The projectConfiguration parameter allows you to specify configuration values that apply to the entire project. The structure is:

{
  "parameterName": "parameterValue",
  "anotherParameter": "anotherValue"
}

Where:

• parameterName is the name of the project configuration variable
• parameterValue is the value to assign to that variable

info

Project configuration parameters serve as global values for all pipelines in the project. Individual pipelines can override these values by defining parameters with the same name in their pipeline-specific configuration.

Configuration Parameter Precedence

Configuration parameters follow this precedence order:

1. Pipeline parameter overrides (highest priority)
2. Project configuration overrides
3. Default project configuration
4. Default pipeline parameters (lowest priority)

Example cURL

This example deploys a project called CustomerAnalytics to the production-databricks fabric with specific pipeline and project configurations.

curl --location 'https://app.prophecy.io/api/deploy/project' \
--header 'X-AUTH-TOKEN: <prophecy-pat>' \
--header 'Content-Type: application/json' \
--data '{
  "projectName": "CustomerAnalytics",
  "fabricName": "production-databricks",
  "gitTag": "CustomerAnalytics/2.1",
  "pipelineConfigurations": {
    "sales_report": {
      "report_period": "monthly",
      "include_forecasts": "true"
    },
    "customer_segmentation": {
      "segment_count": "5",
      "min_customers_per_segment": "100"
    },
    "revenue_analysis": {
      "currency": "USD",
      "include_tax": "false"
    }
  },
  "projectConfiguration": {
    "environment": "production",
    "data_refresh_frequency": "daily"
  }
}'

Response Body

The following fields may appear in the response body of your request.

Field	Description
success	Indicates whether the request to deploy the project was successful.
message	Message that explains the outcome of the request.
deploymentId	Unique identifier of the deployment generated by this request.
details	Object containing detailed information about the deployment.
error	Detailed error information provided when the request fails.

Deployment Details Structure

The details object contains the following fields:

Field	Description
projectId	Unique identifier of the deployed project.
fabricId	Unique identifier of the fabric where the project was deployed.
version	Version number of the deployed project.
pipelinesDeployed	Array of pipeline names that were successfully deployed.
configurationsApplied	Number of configuration parameters that were applied during deployment.

Example Response

This example shows the response to a successful deployment request.

{
  "success": true,
  "message": "Project scheduled successfully",
  "deploymentId": "212",
  "details": {
    "projectId": "67890",
    "fabricId": "09123",
    "version": "2.1",
    "pipelinesDeployed": [
      "sales_report",
      "customer_segmentation",
      "revenue_analysis"
    ],
    "configurationsApplied": 5
  }
}

Error Response Example

This example shows the response to a request with an invalid Git tag.

{
  "success": false,
  "message": "Deployment failed",
  "error": "Failed to fetch project files: Clone failed because revision Some(CustomerAnalytics/2.1) was not found"
}