Setup

Prizm supports two integration modes for dbt. Choose based on your deployment:

Mode	Best For
dbt Cloud	Teams using dbt Cloud for orchestration. Prizm connects via the dbt Cloud API and receives metadata via webhook or scheduled pull.
dbt Core	Teams running dbt Core in CI/CD, Airflow, or shell scripts. Prizm receives metadata via the `prizm-dbt` CLI plugin pushed after each dbt command.

dbt Cloud
dbt Core

Prerequisites

Before connecting, you need:

A dbt Cloud account with access to the Admin API
A service token with permission to read jobs, runs, and artifacts
Your account ID and access URL (varies by region)

Service tokens are the recommended credential type. Personal access tokens can be used but are tied to an individual user account. Use service tokens for production integrations.

Step 1 — Generate a Service Token

In dbt Cloud, navigate to Account Settings → Service Tokens
Click New Token and give it a descriptive name (e.g., prizm-connector)
Assign the following permission sets:
- Metadata Only (to read job definitions, run history, and artifacts)
Click Save and copy the token — it is shown only once

Step 2 — Find Your Account ID and Access URL

Setting	Where to Find It
Account ID	Shown in dbt Cloud URL: `https://cloud.getdbt.com/accounts/<account_id>/`
Access URL	US: `https://cloud.getdbt.com` · EU: `https://eu.dbt.com` · AU: `https://au.dbt.com` · Single-tenant: provided by dbt Labs

Step 3 — Add dbt Cloud in Prizm

Navigate to Source → Add and select dbt from the source type grid.Fill in the Source Details form (Step 1 of 2):

Field	Required	Description
Connection Name	✅	A unique label for this connection (e.g., `dbt-cloud-prod`)
Description	Optional	Free-text description of this source
Platform Type	✅	Select Cloud for dbt Cloud
Use Vault	Optional	Enable to retrieve credentials from your configured secrets vault
Account ID	✅	Your dbt Cloud account ID (visible in the dbt Cloud URL)
Access URL	✅	Your dbt Cloud access URL (e.g., `https://oe527.us1.dbt.com`)
API Key	✅	Service token from dbt Cloud — stored encrypted, never shown after save
Project	Optional	Filter to a specific dbt project within the account
Environment	Optional	Filter to a specific environment (prod / staging / dev)
Enabled Webhook	Optional	Set to Yes to receive near-real-time run events from dbt Cloud

Set Enabled Webhook to Yes for near-real-time ingestion — Prizm processes artifacts within seconds of a dbt job completing. Leave it as No to use scheduled polling instead.

Click Next to proceed to the configuration step.

Step 4 — Source Configuration

The second step configures semantic mapping and job automation for this dbt source.Semantic Configuration:

Setting	Description
Auto Mapping of Tags	Automatically maps dbt tags to Prizm semantic tags (Domain, Product, Application)
Auto Semantic Mapping	Enables AI-assisted classification of dbt assets into Prizm’s semantic layer
Domain	Set a default domain for all assets from this source
Product	Set a default product classification
Application	Set a default application classification

Associated Assets Job:

Setting	Description
Automatic Job Trigger for Associated Assets	When enabled, Prizm automatically runs observability jobs on warehouse assets (Snowflake, Databricks) that are associated with dbt models from this source

Click Update to save the configuration.

Step 5 — Select Jobs to Monitor

After the connection is validated, Prizm presents a list of dbt Cloud jobs in the connected account. Select the jobs you want Prizm to monitor.

Column	Description
Job Name	dbt Cloud job name
Project	dbt project the job belongs to
Environment	prod / staging / dev
Schedule	Configured cron schedule or trigger type
Last Run	Timestamp of the most recent run

You can restrict ingestion to specific projects or environments using the scope filter in the connector settings. By default, all jobs in the account are eligible for selection.

Step 6 — Save and Verify

Click Save. Prizm immediately attempts to ingest the most recent completed run for each selected job. Navigate to Settings → Sources → Logs to monitor ingestion progress.If the initial ingestion completes successfully, dbt models begin appearing in the Prizm catalog within a few minutes.

Prerequisites

Before configuring the dbt Core integration, ensure:

You have a dbt Core project running via CI/CD, Airflow, or shell scripts
You can install Python packages in your pipeline environment
A Prizm API token is available (from Settings → API Tokens)

Install the prizm-dbt CLI Plugin

Install the prizm-dbt package in the same environment where dbt runs:

pip install prizm-dbt

Set your authentication token as an environment variable:

export PRIZM_API_TOKEN=<your-prizm-api-token>

Add dbt Core in Prizm

Navigate to Source → Add and select dbt from the source type grid.

Fill in the Source Details form (Step 1 of 2):

Field	Required	Description
Connection Name	✅	A unique label for this connection (e.g., `dbt-core-prod`)
Description	Optional	Free-text description
Platform Type	✅	Select Core for dbt Core
Ingestion Mode	✅	CLI — artifacts are pushed via the `prizm-dbt` CLI plugin after each dbt run. Storage — artifacts are pulled from a configured S3, GCS, or Azure Blob path on a schedule.

Click Next to proceed. On the Source Configuration step, configure semantic mapping defaults and the Associated Assets Job trigger (same options as dbt Cloud — see Step 4 in the dbt Cloud tab above).After saving, Prizm generates a project-specific token and endpoint URL used by the CLI plugin.

CLI Commands

`prizm-dbt push-artifacts` — Primary Command

Run this command after each dbt run, dbt test, dbt build, or dbt docs generate:

prizm-dbt push-artifacts \
  --project-dir <path-to-dbt-project> \
  --target-path <path-to-dbt-target-dir>

Flag	Description
`--project-dir`	Root directory of your dbt project (where `dbt_project.yml` lives)
`--target-path`	Directory where dbt writes artifacts (default: `./target`)

What this command does:

Reads manifest.json (required), run_results.json, semantic_manifest.json, and catalog.json from the target path
Attaches execution context: environment, target, adapter type, dbt version, invocation timestamp
Pushes all available artifacts to Prizm via the push-based API
Does not execute dbt — safe to run in any CI/CD context

manifest.json is required. If it is missing, the command exits with an error and lists the paths checked. All other artifacts are optional — if not present, they are marked “not produced” without error.

Example — GitHub Actions:

- name: Run dbt
  run: dbt build --profiles-dir .

- name: Push artifacts to Prizm
  env:
    PRIZM_API_TOKEN: ${{ secrets.PRIZM_API_TOKEN }}
  run: |
    prizm-dbt push-artifacts \
      --project-dir . \
      --target-path ./target

Example — Airflow:

BashOperator(
    task_id="push_dbt_artifacts",
    bash_command=(
        "prizm-dbt push-artifacts "
        "--project-dir /opt/airflow/dbt "
        "--target-path /opt/airflow/dbt/target"
    ),
    env={"PRIZM_API_TOKEN": "{{ var.value.prizm_api_token }}"},
)

`prizm-dbt validate` — Preflight Check

Run before your first push to verify the environment is correctly configured:

prizm-dbt validate

Checks performed:

Authentication token is present and valid
Prizm endpoint is reachable
Project directory and target path can be resolved
Required file read permissions exist

`prizm-dbt doctor` — Diagnostics

Run to diagnose configuration issues or provide context to Prizm Support:

prizm-dbt doctor

Outputs:

Resolved project_dir and target_path
Detected artifacts and their sizes
Environment context (env, target, adapter)
Connectivity check to Prizm
Result of the most recent artifact push (if available)

Central Storage Ingestion (Optional)

For regulated environments or teams that persist dbt artifacts in centralized storage, Prizm supports scheduled ingestion from:

Storage	Supported
Amazon S3	✅
Google Cloud Storage	✅
Azure Blob / ADLS	✅

Configure a storage-based source from the connector settings. Prizm polls the configured bucket path on a schedule and ingests any new artifacts found.

Storage-based ingestion is designed for asynchronous or backfill use cases. For near-real-time observability, the CLI plugin push is recommended.

Get Started

Core Concepts

Platform

Architecture

Data Sources

Integrations

Security & Access Control

Deployment

Help

Settings

MCP

Release Notes

API Reference

Prerequisites

Step 1 — Generate a Service Token

Step 2 — Find Your Account ID and Access URL

Step 3 — Add dbt Cloud in Prizm

Step 4 — Source Configuration

Step 5 — Select Jobs to Monitor

Step 6 — Save and Verify

Prerequisites

Install the prizm-dbt CLI Plugin

Add dbt Core in Prizm

CLI Commands

`prizm-dbt push-artifacts` — Primary Command

`prizm-dbt validate` — Preflight Check

`prizm-dbt doctor` — Diagnostics

Central Storage Ingestion (Optional)

Next Steps

What We Collect

FAQ

​Prerequisites

​Step 1 — Generate a Service Token

​Step 2 — Find Your Account ID and Access URL

​Step 3 — Add dbt Cloud in Prizm

​Step 4 — Source Configuration

​Step 5 — Select Jobs to Monitor

​Step 6 — Save and Verify

​Prerequisites

​Install the prizm-dbt CLI Plugin

​Add dbt Core in Prizm

​CLI Commands

​prizm-dbt push-artifacts — Primary Command

​prizm-dbt validate — Preflight Check

​prizm-dbt doctor — Diagnostics

​Central Storage Ingestion (Optional)

​Next Steps

What We Collect

FAQ

Prerequisites

Step 1 — Generate a Service Token

Step 2 — Find Your Account ID and Access URL

Step 3 — Add dbt Cloud in Prizm

Step 4 — Source Configuration

Step 5 — Select Jobs to Monitor

Step 6 — Save and Verify

Prerequisites

Install the prizm-dbt CLI Plugin

Add dbt Core in Prizm

CLI Commands

`prizm-dbt push-artifacts` — Primary Command

`prizm-dbt validate` — Preflight Check

`prizm-dbt doctor` — Diagnostics

Central Storage Ingestion (Optional)

Next Steps