About

Please review the Architecture Overview document for detailed information on selecting the appropriate deployment model. Each section below provides instructions on deploying using different models:

• Cloud Deployments
• Hybrid Deployments

If you're unsure about which deployment type you're currently using or wish to use, please refer to the definitions or contact your account representative for assistance.

Definitions and Terminology

To help with clarity, we have defined the following terms and phrases:

• Cloud Deployments: Refers to customers who connect to an integration without deploying any infrastructure. This term is synonymous with SaaS deployments.

• Hybrid Deployments: Refers to customers who connect to an integration using an Agent or have a Data Store. For more details, please see the definition here.

• Integrations: This term encompasses a variety of connections supported by the Monte Carlo Platform, independently of the developer toolkit.

Requirements

• Monte Carlo Role and Subscription: You must have the Account Owner role in Monte Carlo. Additionally, your account must be subscribed to either the Scale or Enterprise tier with an ESP (Enterprise Support Plan) for a hybrid deployment.
• Cloud Admin: For hybrid deployments, administrative access to either AWS, Azure, or GCP is necessary for the setup.
• Additional Admin Roles: Depending on the specific integration, you may also need administrative rights. Additionally, please note that certain integrations require specific subscription tiers and configurations with the respective vendors for certain functionalities. Refer to your vendor's documentation for more details.

Cloud Deployments

Simply add the integrations you want to connect.

For instructions on IP allowlisting and using services such as Private Link to establish connections to your integrations, please refer to our Network Connectivity docs. These steps might be necessary if your integration is closed from external connections.

Hybrid Deployments

Cloud with Customer-hosted Data Store Deployment

1. Select the guide relevant to the vendor you are using to create and register a data store:

   Cloud Vendor	Guide
   AWS	How to Create and Register an AWS Data Store
   Azure	How to Create and Register an Azure Data Store
   GCP	How to Create and Register a GCP Data Store

2. Add your integrations. For more information on connectivity, please refer to our Network Connectivity docs.

Customer-hosted Agent & Data Store Deployment

1. Select the guide relevant to the vendor you are using to create and register an agent and data store:

   Cloud Vendor	Guide
   AWS	How to Create and Register an AWS Agent and Data Store
   Azure	How to Create and Register an Azure Agent and Data Store
   GCP	How to Create and Register an GCP Agent and Data Store

2. Add your integrations (supported integrations: AWS, Azure, GCP). For more information on connectivity, please refer to our Network Connectivity docs.

FAQs

How Do I Check Which Version of the Platform or Deployments I Am Using?

👍

If your account was created after April 24th, 2024, it will automatically be using the V2 platform or newer.

To check the status of your deployment, follow these steps using our API or Command Line Interface (CLI).

API

1. Access the API Explorer:
   Visit the API Explorer in the Monte Carlo UI (learn more about the API Explorer here).
   
   Alternatively, you can generate an API key and use tools such as cURL or Postman to make API calls.

2. Trigger the API:
   Use this API to fetch deployment details. For instance:

   Example

   query getPlatformServices {
     getPlatformServices {
       uuid
       deployment {
         deploymentType
       }
     }
   }
   

CLI

1. Install and Configure the CLI:
   If you haven't done so already, follow the installation and configuration instructions. Ensure you have at least version v0.100.0 of the CLI.
2. Execute the Command:
   Open your terminal and run the following command (reference docs):
   Shell

   montecarlo platform list
   

Either way, you can use the following table to interpret the output and determine the status of your deployment:

Can I use more than one deployment (e.g., cloud, agent, etc.)?

Yes, please reach out to [email protected] or contact your account representative to learn more.

What types of integrations do I usually need to set up connectivity for?

Generally, you might need to enable connectivity between the Monte Carlo Platform and your integration (Cloud) or between the Monte Carlo Agent and your integration (Hybrid). This varies by vendor and depends on how you are managing your resource (e.g., whether it is publicly available).

For push-based developer tools or integrations that are automatically generated by query logs, usually, no action is required. This includes, but is not limited to, integrations like:

• Atlan
• Airflow
• dbt Core
• Sigma
• Mode

These integrations also might not use the collection platform, agents, and data stores.

For more information on connectivity, please refer to our Network Connectivity documentation.

How do I list which integrations are using a deployment if I have more than one?

If you have more than one deployment and/or want to see which connections are using a specific deployment, you can do so via the API.

1. Access the API Explorer:
   Visit the API Explorer in the Monte Carlo UI (learn more about the API Explorer here).
   
   Alternatively, you can generate an API key and use tools such as cURL or Postman to make API calls.

2. Trigger the API:
   Use the getPlatformServices API to fetch deployment details. For instance:

   Example: Listing connectionsExample: Filtering by connection typeExample: Filtering by deployment ID

   query getPlatformServices {
     getPlatformServices {
       uuid
       deployment {
         deploymentType
         platform {
           ipAddresses
         }
       }
       connections {
         uuid
         name
         connectionType
       }
     }
   }
   

   query getPlatformServices {
     getPlatformServices(connectionTypes: ["snowflake"]) {
       uuid
       deployment {
         deploymentType
         platform {
           ipAddresses
         }
       }
     }
   }
   

   query getPlatformServices {
     getPlatformServices(serviceUuid: "d8214cdf-00d2-4848-a8e3-947f0f6f7613") {
       uuid
       deployment {
         deploymentType
         platform {
           ipAddresses
         }
       }
       connections {
         uuid
         name
         connectionType
       }
     }
   }
   

How do I list all of my Data Stores or Remote Agents?

All registered data stores and agents are listed in the Monte Carlo UI here.

They can also be retrieved via the API or Command Line Interface (CLI). See below:

API

1. Access the API Explorer:
   Visit the API Explorer in the Monte Carlo UI (learn more about the API Explorer here).
   
   Alternatively, you can generate an API key and use tools such as cURL or Postman to make API calls.

2. Trigger the API:
   Use the getPlatformServices API to fetch deployment details. For instance:

   Example

   query getPlatformServices {
     getPlatformServices {
       uuid
       deployment {
         deploymentType
         agent {
           uuid
           endpoint
           agentType
         }
       }
     }
   }
   

CLI

1. Install and Configure the CLI:
   If you haven't done so already, follow the installation and configuration instructions.
2. Execute the Command:
   Open your terminal and run the following command (reference docs):
   Shell

   montecarlo agents list
   

How do I remove a Data Store or Remote Agent?

A data store or remote agent can be deregistered with the Command Line Interface (CLI). See details below:

1. Install and Configure the CLI:
   If you haven't done so already, follow the installation and configuration instructions.
2. Execute the Command:
   Open your terminal and run the following command (reference docs):
   Shell

   montecarlo agents deregister --agent-id <agent_id>
   

   If you have more than one agent, you can refer here for details on how to fetch the agent ID (UUID).

Note that deregistering either a data store or agent does not remove any resources you may have provisioned, and replacing either will mean previous data (history) will no longer be accessible unless migrated.

Importantly, jobs also might fail if you remove an agent or store without coordinating with our team. Please reach out to your Monte Carlo representative or support ([email protected]), and we'd be happy to help!