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[TMP] Armada Documentation - Table of Contents

Note

This page outlines a proposed structure for Armada's documentation website, designed to support three primary user journeys from initial discovery through advanced usage and contribution.

Purpose: Establish a coherent structure and content framework to guide documentation development and ensure comprehensive coverage of user needs across different experience levels.

Target Audiences:

  • Users: Data scientists, engineers, and analysts who submit and manage computational jobs
  • Operators: Infrastructure teams responsible for deploying, scaling, and maintaining Armada clusters
  • Developers: Developers building integrations, extending core functionality, or contributing to the open-source project

Next Steps: This structure will evolve based on community feedback and real-world usage patterns. Maintainers and contributors are encouraged to share insights on content gaps, user pain points, and structural improvements.

1. Overview

Introduction to Armada, its purpose, high-level architecture, and key components.

  • What is Armada?
  • Why Use Armada?
  • Key Features and Benefits
  • Use Cases and Success Stories
  • Comparison with Other Schedulers

2. Getting Started

Start here if you're new to Armada. Learn how to install it and run your first job.

2.1 Quickstart

  • Prerequisites and Requirements
  • Quickstart with Kind & Helm
  • Submitting Your First Job
  • Viewing Job Status and Logs

2.2 Tutorials

  • End-to-end ML Job Example
  • Batch Data Processing Pipeline
  • CI/CD Integration Walkthrough

3. Understanding Armada

3.1 Architecture

Understand how Armada works under the hood.

  • Armada system components
  • Scheduling pipeline and job lifecycle
  • Executors, queues, and priorities
  • Fault tolerance and scaling

3.2 Core Concepts

Deep dives into key ideas and mechanisms that power Armada.

  • Jobs & Queues
  • Prioritization and Fair-Use Scheduling
  • Scheduling Algorithms

4. Operator Guide

Complete guide for platform engineers and operators - from installation to production maintenance.

  • Local installation (Kind, Minikube)
  • Installation and Deployment
  • Cluster setup and configuration
  • Monitoring and observability
  • Scaling
  • Troubleshooting

5. User Guide

Practical guidance for job submission and management.

  • Submitting and cancelling jobs
  • Working with job specs
  • Using Integrations
  • Examples

5.1 CLI Reference

  • Installing armadactl
  • CLI commands and flags
  • Example usage patterns

5.2 API Reference

  • REST and gRPC APIs
  • OpenAPI Spec (auto-generated)

5.3 Clients

Client libraries and SDKs for different languages.

  • Python
  • Java/Scala

5.4 Integrations

Explore integrations.

  • Airflow Operator
  • MetaFlow Integration
  • Jenkins Integration
  • Spark Integration

6. Developer Guide

Resources for extending and contributing to Armada.

  • Running Armada from source locally
  • Code structure and modules
  • Profiling and debugging
  • Dev environment setup
  • Extending Armada

7. Contributing

Guidelines for contributing to the Armada project.

8. Community & Support

Ways to get involved and get help.

  • Slack and discussion forums
  • Reporting bugs and feature requests
  • Maintainers
  • Adopters

9. FAQ & Troubleshooting

Answers to common questions and known issues.

  • Common deployment issues
  • Job submission errors
  • Version compatibility
  • Debugging tips
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