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After creating your application in Revolte, the configuration phase ensures your services are aligned with your team’s development workflows and infrastructure requirements. This guide provides a high-level overview of the two configuration modules you will use to govern how code moves from your repository to a running service.

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Prerequisites

Before configuring your services, ensure you have:
  1. Connected your repository.
  2. Completed the initial application setup. If you haven’t, start with the Quick Start Guide.

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The Configuration Lifecycle

Configuration in Revolte is split into two distinct areas. Understanding this distinction is key to a governed deployment workflow.
1

Repository Preferences (The 'How')

Defined once per application. This governs how Revolte interacts with your code—including branch mappings, AI agent workflows, and pre-build validation steps.
2

Environment Settings (The 'Where')

Defined per deployment target. This governs where and under what conditions code runs—including secrets, resource specifications, and scaling rules for Preview, Staging, or Production.

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1. Repository Preferences

The Repository Preference tab is the control center for your automation. These settings apply globally to the application across all environments.

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AI Agent Workflows

Enable autonomous developer workflows to accelerate delivery:
  • Developer Agent: Toggle on to allow the AI to proactively implement tickets and handle routine PR work.
  • Pre-build Workflow: Enable automated code summarization and fix suggestions. You can tune the Comment Style (Balanced, Concise, or Verbose) to match your team’s review culture.

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Pipeline Governance

Standardize your quality gates before any code reaches a build stage:
  • Code Quality: Link your application to a specific code style framework.
  • Test Suite: Define the exact execution command (e.g., npm test or pytest) that must pass before a deployment is triggered.

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2. Environment Settings

While Repository Preferences stay the same, Environment Settings adapt to the needs of each deployment stage.
  • Resource Scaling: Assign different CPU and Memory specifications for Preview environments vs. Production.
  • Secrets & Variables: Manage encrypted credentials that are injected only at runtime for specific environments.
  • Deployment Policy: Configure manual approval gates for sensitive environments to ensure human-in-the-loop governance.

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Why Configuration Matters

  • Standardization: Ensure every service follows the same validation and review lifecycle.
  • Security: Isolate sensitive credentials and control access through environment-specific target settings.
  • Velocity: Use AI agents and pre-build workflows to remove manual bottlenecks in the SDLC.

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Next Steps

Repository Preferences

Deep dive into branch mapping and agent workflows.

Environment Settings

Learn how to manage per-environment overrides and secrets.