How to Deploy Mprove: Your Self-Service Business Intelligence Solution

May 27, 2024 | Data Science

Welcome to the ultimate guide on how to deploy Mprove, your self-service Business Intelligence (BI) tool inspired by Looker! In this article, we’ll walk you through the process of deploying Mprove either on a Kubernetes cluster using Helm Chart or locally using docker-compose. Let’s dive in!

Table of Contents

Deploy to a Kubernetes Cluster Using Helm Chart

For instructions on deploying Mprove to a Kubernetes cluster, check out the Mprove Helm Charts. This resource is essential for setting up Mprove via Kubernetes and allows for effective version control in your BI environment.

Local Deploy Using Docker-Compose

If you prefer a local setup, follow these step-by-step instructions:

  1. Clone the Mprove GitHub repository to your local machine:
    git clone https://github.com/mprove-io/mprove.git
  2. Create the data folders outside of your Mprove repo:
    mkdir -p ~/mprove_data/mysql ~/mprove_data/organizations ~/mprove_data/dwh-postgres ~/mprove_data/dwh-clickhouse ~/mprove_data/dwh-clickhouse-logs ~/mprove_data/blockml-logs
  3. Create a ‘secrets’ folder and add required files:
    mkdir secrets
    echo -n > secrets/first-project-bigquery-credentials.json
    echo -n > secrets/first-project-remote-private-key.pem
    echo -n > secrets/first-project-remote-public-key.pem
  4. Copy the example environment file:
    cp .env.example .env
  5. Modify the variables in the mprove.env file according to your environment.
  6. Pull the required Docker images:
    docker-compose pull db dwh-postgres dwh-clickhouse rabbit backend blockml-single disk front
  7. Run the Docker images using:
    docker-compose up db dwh-postgres dwh-clickhouse rabbit backend backend-scheduler blockml-single disk front
  8. Open a Chrome tab and log in using the first user credentials at http://localhost:3003.

Troubleshooting

As you embark on this deployment journey, you may encounter some bumps along the road. Here’s how to troubleshoot common issues:

  • **Docker Issues**: If Docker is not running, ensure that the Docker service is started on your machine.
  • **Environment Variables**: Make sure to double-check your mprove.env file for any missing or incorrect environment variable configurations.
  • **Access Denied Issues**: If you encounter “403 Forbidden” errors, ensure you have the proper permissions set for the ‘secrets’ folder.
  • **Port Conflicts**: Ensure that the port 3003 is available and not being used by another application.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

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