> ## Documentation Index
> Fetch the complete documentation index at: https://docs.heygarth.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Overview & Integration Prerequisites

> Overview of G360 and required prerequisites for integrations.

## Overview

Before creating projects in the Engineering Metrics platform, users must first configure one or more integrations. Integrations act as the primary data sources used to collect engineering, CI/CD, repository, deployment, and AI usage metrics.

Projects depend on configured integrations to synchronize and process analytics data. Without a valid integration connection, project synchronization and dashboard reporting will not function correctly.

This section explains the recommended setup workflow and prerequisites required before project creation.

## Recommended Setup Workflow

The Engineering Metrics platform follows the workflow below:

### 1. Configure Integration Connection

Create and authenticate a connection to an external provider such as GitHub, GitLab, Bitbucket, Jenkins, CircleCI, OpenAI, Anthropic, Cursor, or other supported platforms.

### 2. Add Data Scope

Select repositories, pipelines, projects, or data entities that should be synchronized into Engineering Metrics.

### 3. Configure Scope Settings

Define synchronization behavior, deployment stage mappings, DORA metrics configuration, and other analytics settings.

### 4. Create a Project

Create a project within the Engineering Metrics platform to organize analytics and reporting.

### 5. Map Integrations to the Project

Associate configured integrations and selected scopes with the project.

### 6. Configure Synchronization

Set synchronization frequency, historical data range, scheduling behavior, and execution policies.

### 7. Run Synchronization

Execute the initial synchronization process to begin collecting and processing data.

### 8. View Dashboards and Analytics

Once synchronization completes successfully, engineering metrics, DORA metrics, PR analytics, CI/CD insights, and AI usage metrics become available within the dashboards.

## General Prerequisites

Before configuring integrations, ensure the following requirements are met:

* Access to the Engineering Metrics platform
* Permissions to configure integrations and projects
* Valid credentials or API tokens for the external provider
* Required repository, pipeline, or API access permissions
* Network connectivity between Engineering Metrics and the external platform
* Proxy configuration details if operating within a restricted enterprise environment

## Authentication and API Tokens

Most integrations require API-based authentication using one of the following:

* Personal Access Tokens (PATs)
* API Keys
* OAuth Tokens
* Admin Keys
* Service Account Credentials

For each integration provider, users should:

* Generate the required token or API key
* Ensure the token has the necessary access scopes and permissions
* Store credentials securely
* Avoid using personal user credentials where possible
* Prefer dedicated service or organization-managed accounts for production environments

Detailed token generation steps and required scopes are documented within each integration section of this guide.

## Important Notes

* A project cannot synchronize data until at least one valid integration connection is configured
* Insufficient permissions or incorrect token scopes may result in missing repositories, failed synchronization, or incomplete analytics
* Some integrations may support only one active connection per organization depending on provider limitations
* Synchronization schedules and historical data ranges directly impact dashboard visibility and reporting accuracy