Monte Carlo

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What you can do

• Enhanced Observability: Overlay dbt™ context onto Monte Carlo’s lineage graph for easier troubleshooting.
• Incident Detection: Detect and centralize dbt™ model errors, test failures, and other data incidents in one place.
• Run Insights: Visualize dbt™ job execution times, success/error statuses, and run histories.
• Simplified Impact Analysis: Evaluate downstream and upstream impacts of dbt™ transformations on table updates.

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Setting Up the Integration

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Step 1: Generate API Key and API ID

1. Log in to your Monte Carlo account.
2. Follow the instructions in Monte Carlo Docs to generate:
   • API Key
   • API ID

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Step 2: Add API Credentials to Paradime

1. From the Paradime home page, click the Settings icon (⚙️) on the bottom right hand side of the screen
2. Navigate to Workspaces > Environment Variables
3. In the Bolt Schedules section, add the following variables and their respective values from Step 1:
   • MCD_DEFAULT_API_TOKEN
   • MCD_DEFAULT_API_ID
4. Click the Save icon (💾)

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Step 3: Set Your Project Name

• In the same Bolt Schedules section, add:
  • MONTECARLO_PROJECT_NAME
• Set a value for the project name

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Step 4: Obtain the Connection ID

query getConnections {
  getUser {
    email
    account {
      connections {
        uuid
        type
        warehouse {
          name
        }
      }
    }
  }
}

{
	"data": {
		"getUser": {
			"email": "example@montecarlodata.com",
			"account": {
				"connections": [{
					"uuid": "9b265c4d-931f-4584-99c6-42ea37155a99",
					"type": "SNOWFLAKE",
					"warehouse": {
						"name": "snowflake-artemis"
					}
				}]
			}
		}
	}
}

% montecarlo integrations list
╒════════════════════════╤══════════════════╤══════════════════════════════════════╤═════════════════════════════════════════════════════════╕
│ Integration            │ Name             │ ID                                   │ Connection           │ Created on (UTC)                 │
╞════════════════════════╪══════════════════╪══════════════════════════════════════╪══════════════════════╪══════════════════════════════════╡
│ Redshift               │ prod-redshift    │ 12345678-1234-1234-1234-123456789012 │ host: redacted       │ 2022-12-14T14:54:15.944774+00:00 │
├────────────────────────┼──────────────────┼──────────────────────────────────────┼──────────────────────┼──────────────────────────────────┤
│ BigQuery               │ prod-bigquery    │ 12345678-1234-1234-1234-123456789013 │ client_id: redacted  │ 2022-12-14T18:02:54.644654+00:00 │
╘════════════════════════╧══════════════════╧══════════════════════════════════════╧══════════════════════╧══════════════════════════════════╛

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Step 5: Add the Connection ID

1. Copy the Connection ID from the logs.
2. Go back to the Environment Variables section in Paradime.
3. Add the following variable:
   • MONTECARLO_CONNECTION_ID
4. Click Save to confirm.

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Step 6: Enable the Integration

1. In the same Environment Variables section, add the following variable:
   • RUN_MONTECARLO_UPLOAD
2. Set its value to TRUE.

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Connection parameters

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Testing the Integration

1. Trigger a Run for one of your Bolt schedule which contains either dbt build, dbt run or dbt test command.
2. Verify the results in Monte Carlo:
   • Check the lineage graph for updated dbt™ context.

• View job statuses, model run results, and test outcomes.