LogoLogo
  • Introduction
    • Overview
    • Why Alvin?
    • Connect your systems
      • Data Warehouse
        • BigQuery
          • Provision source system credentials
          • Provision with GCloud CLI
        • Snowflake
        • Databricks
      • Business Intelligence
        • Looker
      • Orchestration
        • dbt
      • SSO (Single Sign-On)
    • Security & compliance
    • Types of metadata
    • FAQ
  • Cost Monitoring
    • Introduction to Cost Monitoring
    • Compute
    • Storage
  • BI Query Optimizer
    • Introduction to Query Optimizer
    • How does it work?
    • Getting started
  • Workflow automation
    • Introduction to Workflow Automation
    • Events definitions
    • Configuring Workflows
  • Anomaly Detection
    • Anomaly Detection
  • Exploring Metadata
    • Lineage
      • Depth of lineage
    • Impact Analysis
    • Entities
    • Entity View
    • Metadata Warehouse
Powered by GitBook
On this page
  • Setup Alvin DBT integration
  • 1. Setup the Alvin API Key
  • 2. Install PyPI package
  • 3. Setup the Alvin CLI
  • 4. Execute alvin dbt process-artifacts command
  1. Introduction
  2. Connect your systems
  3. Orchestration

dbt

The Alvin DBT integration allows Alvin to extract runtime metadata about DBT Models, Runs and Jobs connected to each run.

Last updated 6 months ago

Setup Alvin DBT integration

1. Setup the Alvin API Key

To get hold of a valid API key, contact a member of our team who will share it with you securely.

2. Install PyPI package

The Alvin CLI allows users to extract runtime metadata about DBT Models, Runs and Jobs connected to each run, to install it in your environment all you need is to run the following command: pip install alvin-simple-cli

The latest version of the alvin-simple-cli package can be found .

3. Setup the Alvin CLI

If using an Orchestration Environment such as GitHub

If you are running the Alvin CLI in an orchestration environment such as GitHub, you may skip the setup command and just set the API_KEY through an environment variable named ALVIN_API_TOKEN.


  • Run alvin setup command to set your environment.

This will create a alvin.cfg file in your user directory under .alvin.

Edit the file and add the following:

  • alvin_api_token(Generated from the UI at step number 1)

The value {REPLACE_WITH_GENERATED_API_KEY} should be replaced with the API KEY created at step number 1.

4. Execute alvin dbt process-artifacts command

After you run a DBT command such as:

  • run

  • test

  • seed

  • build

You may send the dbt artifacts to Alvin by running:

alvin dbt process-artifacts --dw-platform-id {alvin_dw_platform_id} \
--platform-id {alvin_dbt_platform_id} \
--artifacts-path /dbt/demo/target \
--project-name {your_dbt_project_name} \
--user-email {any_arbitrary_email_string}

List of parameters:

  • dw-platform-id value of your data warehouse platform set in Alvin that can be fetched from this Alvin UI.

  • platform-id value used to store the dbt platform metadata, can be a string that matches the following regex pattern: ^[a-z][a-z0-9_]*.

  • artifacts-path relative or absolute directory where the dbt target is created.

  • project-name any arbitrary string that you can use to group your dbt results.

  • user-email email that you want to associate this dbt execution with.

here