Common Configuration Elements

• Base Image

  • Defines OS and preinstalled software

• Features

  • Prebuilt modular tooling (e.g., Node.js, Python, Docker)

• Extensions

  • VS Code extensions auto-installed

• Settings

  • Editor settings scoped to the environment

• Post-create Commands

  • Scripts that run after the container is built

• Forwarded Ports

  • Expose services (web apps, APIs)

Purpose

• Ensures environmental consistency

• Eliminates “works on my machine” issues



• Enables team-wide reproducible development

GitHub Codespaces Features

Cloud-Based Development

• Runs entirely on GitHub infrastructure

• No dependency on local machine resources

• Ideal for low-powered devices or locked-down corporate laptops

Fully Integrated IDE

• VS Code Web:

  • Editor

  • Terminal

  • Debugger

  • Git integration

• VS Code Desktop:

  • Same experience using Remote Development

Machine Types

Machine types of impact:

• Performance

• Cost

• Build times

Port Forwarding

• Automatically detects listening ports

• Allows:

  • Private ports (default)

  • Publicly accessible preview URLs

• Used for:

  • Web apps

  • APIs

  • Microservices

Prebuilds

Prebuilds proactively create codespaces environments:

• The environment is built before a developer opens it

• Reduces startup time dramatically

• Especially useful for large repositories

GitHub Integration

• Native Git support

• Authentication via GitHub identity

• Pull requests, issues, and branches are fully supported

Secrets Management

Codespaces supports secrets at multiple levels:

Secrets are:

• Injected securely

• Never committed to source control

Collaboration

• Live Share support

• Share running applications via forwarded ports

• Multiple codespaces can exist per user

GitHub Codespaces Lifecycle

Security Model

• Each codespace runs in:

  • A dedicated VM

  • Isolated network namespace

• Authentication uses GitHub identity

• Repository permissions apply

• No inbound access unless ports are forwarded

Cost & Billing Model

Billing is based on:

• Compute Time

  • While codespace is running

• Storage

  • Persisted disk usage

Cost depends on:

• Machine size

• Duration

• Number of active codespaces