Paradime Help Docs
Get Started
  • 🚀Introduction
  • 📃Guides
    • Paradime 101
      • Getting Started with your Paradime Workspace
        • Creating a Workspace
        • Setting Up Data Warehouse Connections
        • Managing workspace configurations
        • Managing Users in the Workspace
      • Getting Started with the Paradime IDE
        • Setting Up a dbt™ Project
        • Creating a dbt™ Model
        • Data Exploration in the Code IDE
        • DinoAI: Accelerating Your Analytics Engineering Workflow
          • DinoAI Agent
            • Creating dbt Sources from Data Warehouse
            • Generating Base Models
            • Building Intermediate/Marts Models
            • Documentation Generation
            • Data Pipeline Configuration
            • Using .dinorules to Tailor Your AI Experience
          • Accelerating GitOps
          • Accelerating Data Governance
          • Accelerating dbt™ Development
        • Utilizing Advanced Developer Features
          • Visualize Data Lineage
          • Auto-generated Data Documentation
          • Enforce SQL and YAML Best Practices
          • Working with CSV Files
      • Managing dbt™ Schedules with Bolt
        • Creating Bolt Schedules
        • Understanding schedule types and triggers
        • Viewing Run History and Analytics
        • Setting Up Notifications
        • Debugging Failed Runs
    • Migrating from dbt™ cloud to Paradime
  • 🔍Concepts
    • Working with Git
      • Git Lite
      • Git Advanced
      • Read Only Branches
      • Delete Branches
      • Merge Conflicts
      • Configuring Signed Commits on Paradime with SSH Keys
    • dbt™ fundamentals
      • Getting started with dbt™
        • Introduction
        • Project Strucuture
        • Working with Sources
        • Testing Data Quality
        • Models and Transformations
      • Configuring your dbt™ Project
        • Setting up your dbt_project.yml
        • Defining Your Sources in sources.yml
        • Testing Source Freshness
        • Unit Testing
        • Working with Tags
        • Managing Seeds
        • Environment Management
        • Variables and Parameters
        • Macros
        • Custom Tests
        • Hooks & Operational Tasks
        • Packages
      • Model Materializations
        • Table Materialization
        • View​ Materialization
        • Incremental Materialization
          • Using Merge for Incremental Models
          • Using Delete+Insert for Incremental Models
          • Using Append for Incremental Models
          • Using Microbatch for Incremental Models
        • Ephemeral Materialization
        • Snapshots
      • Running dbt™
        • Mastering the dbt™ CLI
          • Commands
          • Methods
          • Selector Methods
          • Graph Operators
    • Paradime fundamentals
      • Global Search
        • Paradime Apps Navigation
        • Invite users to your workspace
        • Search and preview Bolt schedules status
      • Using --defer in Paradime
      • Workspaces and data mesh
    • Data Warehouse essentials
      • BigQuery Multi-Project Service Account
  • 📖Documentation
    • DinoAI
      • Agent Mode
        • Use Cases
          • Creating Sources from your Warehouse
          • Generating dbt™ models
          • Fixing Errors with Jira
          • Researching with Perplexity
          • Providing Additional Context Using PDFs
      • Context
        • File Context
        • Directory Context
      • Tools and Features
        • Warehouse Tool
        • File System Tool
        • PDF Tool
        • Jira Tool
        • Perplexity Tool
        • Terminal Tool
        • Coming Soon Tools...
      • .dinorules
      • Ask Mode
      • Version Control
      • Production Pipelines
      • Data Documentation
    • Code IDE
      • User interface
        • Autocompletion
        • Context Menu
        • Flexible layout
        • "Peek" and "Go To" Definition
        • IDE preferences
        • Shortcuts
      • Left Panel
        • DinoAI Coplot
        • Search, Find, and Replace
        • Git Lite
        • Bookmarks
      • Command Panel
        • Data Explorer
        • Lineage
        • Catalog
        • Lint
      • Terminal
        • Running dbt™
        • Paradime CLI
      • Additional Features
        • Scratchpad
    • Bolt
      • Creating Schedules
        • 1. Schedule Settings
        • 2. Command Settings
          • dbt™ Commands
          • Python Scripts
          • Elementary Commands
          • Lightdash Commands
          • Tableau Workbook Refresh
          • Power BI Dataset Refresh
          • Paradime Bolt Schedule Toggle Commands
          • Monte Carlo Commands
        • 3. Trigger Types
        • 4. Notification Settings
        • Templates
          • Run and Test all your dbt™ Models
          • Snapshot Source Data Freshness
          • Build and Test Models with New Source Data
          • Test Code Changes On Pull Requests
          • Re-executes the last dbt™ command from the point of failure
          • Deploy Code Changes On Merge
          • Create Jira Tickets
          • Trigger Census Syncs
          • Trigger Hex Projects
          • Create Linear Issues
          • Create New Relic Incidents
          • Create Azure DevOps Items
        • Schedules as Code
      • Managing Schedules
        • Schedule Configurations
        • Viewing Run Log History
        • Analyzing Individual Run Details
          • Configuring Source Freshness
      • Bolt API
      • Special Environment Variables
        • Audit environment variables
        • Runtime environment variables
      • Integrations
        • Reverse ETL
          • Hightouch
        • Orchestration
          • Airflow
          • Azure Data Factory (ADF)
      • CI/CD
        • Turbo CI
          • Azure DevOps
          • BitBucket
          • GitHub
          • GitLab
          • Paradime Turbo CI Schema Cleanup
        • Continuous Deployment with Bolt
          • GitHub Native Continuous Deployment
          • Using Azure Pipelines
          • Using BitBucket Pipelines
          • Using GitLab Pipelines
        • Column-Level Lineage Diff
          • dbt™ mesh
          • Looker
          • Tableau
          • Thoughtspot
    • Radar
      • Get Started
      • Cost Management
        • Snowflake Cost Optimization
        • Snowflake Cost Monitoring
        • BigQuery Cost Monitoring
      • dbt™ Monitoring
        • Schedules Dashboard
        • Models Dashboard
        • Sources Dashboard
        • Tests Dashboard
      • Team Efficiency Tracking
      • Real-time Alerting
      • Looker Monitoring
    • Data Catalog
      • Data Assets
        • Looker assets
        • Tableau assets
        • Power BI assets
        • Sigma assets
        • ThoughtSpot assets
        • Fivetran assets
        • dbt™️ assets
      • Lineage
        • Search and Discovery
        • Filters and Nodes interaction
        • Nodes navigation
        • Canvas interactions
        • Compare Lineage version
    • Integrations
      • Dashboards
        • Sigma
        • ThoughtSpot (Beta)
        • Lightdash
        • Tableau
        • Looker
        • Power BI
        • Streamlit
      • Code IDE
        • Cube CLI
        • dbt™️ generator
        • Prettier
        • Harlequin
        • SQLFluff
        • Rainbow CSV
        • Mermaid
          • Architecture Diagrams
          • Block Diagrams Documentation
          • Class Diagrams
          • Entity Relationship Diagrams
          • Gantt Diagrams
          • GitGraph Diagrams
          • Mindmaps
          • Pie Chart Diagrams
          • Quadrant Charts
          • Requirement Diagrams
          • Sankey Diagrams
          • Sequence Diagrams
          • State Diagrams
          • Timeline Diagrams
          • User Journey Diagrams
          • XY Chart
          • ZenUML
        • pre-commit
          • Paradime Setup and Configuration
          • dbt™️-checkpoint hooks
            • dbt™️ Model checks
            • dbt™️ Script checks
            • dbt™️ Source checks
            • dbt™️ Macro checks
            • dbt™️ Modifiers
            • dbt™️ commands
            • dbt™️ checks
          • SQLFluff hooks
          • Prettier hooks
      • Observability
        • Elementary Data
          • Anomaly Detection Tests
            • Anomaly tests parameters
            • Volume anomalies
            • Freshness anomalies
            • Event freshness anomalies
            • Dimension anomalies
            • All columns anomalies
            • Column anomalies
          • Schema Tests
            • Schema changes
            • Schema changes from baseline
          • Sending alerts
            • Slack alerts
            • Microsoft Teams alerts
            • Alerts Configuration and Customization
          • Generate observability report
          • CLI commands and usage
        • Monte Carlo
      • Storage
        • Amazon S3
        • Snowflake Storage
      • Reverse ETL
        • Hightouch
      • CI/CD
        • GitHub
        • Spectacles
      • Notifications
        • Microsoft Teams
        • Slack
      • ETL
        • Fivetran
    • Security
      • Single Sign On (SSO)
        • Okta SSO
        • Azure AD SSO
        • Google SAML SSO
        • Google Workspace SSO
        • JumpCloud SSO
      • Audit Logs
      • Security model
      • Privacy model
      • FAQs
      • Trust Center
      • Security
    • Settings
      • Workspaces
      • Git Repositories
        • Importing a repository
          • Azure DevOps
          • BitBucket
          • GitHub
          • GitLab
        • Update connected git repository
      • Connections
        • Code IDE environment
          • Amazon Athena
          • BigQuery
          • Clickhouse
          • Databricks
          • Dremio
          • DuckDB
          • Firebolt
          • Microsoft Fabric
          • Microsoft SQL Server
          • MotherDuck
          • PostgreSQL
          • Redshift
          • Snowflake
          • Starburst/Trino
        • Scheduler environment
          • Amazon Athena
          • BigQuery
          • Clickhouse
          • Databricks
          • Dremio
          • DuckDB
          • Firebolt
          • Microsoft Fabric
          • Microsoft SQL Server
          • MotherDuck
          • PostgreSQL
          • Redshift
          • Snowflake
          • Starburst/Trino
        • Manage connections
          • Set alternative default connection
          • Delete connections
        • Cost connection
          • BigQuery cost connection
          • Snowflake cost connection
        • Connection Security
          • AWS PrivateLink
            • Snowflake PrivateLink
            • Redshift PrivateLink
          • BigQuery OAuth
          • Snowflake OAuth
        • Optional connection attributes
      • Notifications
      • dbt™
        • Upgrade dbt Core™ version
      • Users
        • Invite users
        • Manage Users
        • Enable Auto-join
        • Users and licences
        • Default Roles and Permissions
        • Role-based access control
      • Environment Variables
        • Bolt Schedules Environment Variables
        • Code IDE Environment Variables
  • 💻Developers
    • GraphQL API
      • Authentication
      • Examples
        • Audit Logs API
        • Bolt API
        • User Management API
        • Workspace Management API
    • Python SDK
      • Getting Started
      • Modules
        • Audit Log
        • Bolt
        • Lineage Diff
        • Custom Integration
        • User Management
        • Workspace Management
    • Paradime CLI
      • Getting Started
      • Bolt CLI
    • Webhooks
      • Getting Started
      • Custom Webhook Guides
        • Create an Azure DevOps Work item when a Bolt run complete with errors
        • Create a Linear Issue when a Bolt run complete with errors
        • Create a Jira Issue when a Bolt run complete with errors
        • Trigger a Slack notification when a Bolt run is overrunning
    • Virtual Environments
      • Using Poetry
      • Troubleshooting
    • API Keys
    • IP Restrictions in Paradime
    • Company & Workspace token
  • 🙌Best Practices
    • Data Mesh Setup
      • Configure Project dependencies
      • Model access
      • Model groups
  • ‼️Troubleshooting
    • Errors
    • Error List
    • Restart Code IDE
  • 🔗Other Links
    • Terms of Service
    • Privacy Policy
    • Paradime Blog
Powered by GitBook
On this page
  • What is Monte Carlo?
  • Value of Monte Carlo with Paradime
  • Setting Up the Integration
  • Testing the Integration

Was this helpful?

  1. Documentation
  2. Integrations
  3. Observability

Monte Carlo

PreviousCLI commands and usageNextStorage

Last updated 3 months ago

Was this helpful?

What is Monte Carlo?

is a leading data observability platform that helps data teams monitor, resolve, and prevent data quality issues. It provides insights into the health, freshness, and lineage of your data assets across your entire data stack.

Value of Monte Carlo with Paradime

Integrating Monte Carlo with Paradime enables teams to centralize data observability and enhance the monitoring of production jobs (Bolt schedules) and dbt™ models. Key benefits include:

  • 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.

With this integration, data teams can proactively address failures, optimize dbt™ models, and ensure reliable data pipelines.


Setting Up the Integration

Follow these steps to configure the Monte Carlo integration within Paradime.

Step 1: Generate API Key and API ID

  1. Log in to your Monte Carlo account.

  2. Follow the instructions in to generate:

    • API Key

    • API ID

The key is required to be generated with the "Editor" or "Owner" roles, for example if you create a Service Account Key you need to select "Editors" or "Account Owners" under "Authorization Groups".

If you're using a personal key, the user that generated it needs to be an "Editor" or "Owner".


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. In the Bolt Schedules section, add the following variables and their respective values from Step 1:

    • MCD_DEFAULT_API_TOKEN

    • MCD_DEFAULT_API_ID

  3. Click the Save icon (💾)

Step 3: Set Your Project Name


Step 3: Set Your Project Name

  • In the same Bolt Schedules section, add:

    • MONTECARLO_PROJECT_NAME

  • Set a value for the project name


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 │
╘════════════════════════╧══════════════════╧══════════════════════════════════════╧══════════════════════╧══════════════════════════════════╛

Step 5: Add the Connection ID

  1. Copy the Connection ID from the logs.

  2. Add the following variable:

    • MONTECARLO_CONNECTION_ID

  3. Click Save to confirm.


Step 6: Enable the Integration

This Flag will enable uploading automatically all schedules dbt run artifacts to Montecarlo.

    • RUN_MONTECARLO_UPLOAD

  1. Set its value to TRUE.

By the end of this step, your Monte Carlo environment variables should include:


Testing the Integration

To verify the integration, run the following steps in Paradime's Bolt:

  1. Trigger a Run for one of you Bolt schedule which 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.

Navigate to Workspaces >

You can reuse or create any name that aligns with your dbt models.

The Connection ID identifies the warehouse or lake connection in Monte Carlo. You can do this by retrieving the connection UUID via the API through the by running the below query.

If you prefer you can also use the command in the Monte Carlo CLI to retrieve your connection ID (UUID).

Go back to the section in Paradime.

In the same section, add the following variable:

For more details on the logs that Montecarlo will ingest check the .

📖
Monte Carlo
Monte Carlo Docs
Environment Variables
getUser
API Explorer
list
Environment Variables
Environment Variables
Montecarlo dbt integration documentation
your existing dbt project name