Usage & Credits

Understand how Ona credits work, what OCUs are, and how your environment and AI usage consumes credits.

What is an OCU?

An OCU (Ona Compute Unit) is Ona’s standard unit of measurement for resource consumption. OCUs represent the computational resources used by your environments and AI features. Key points about OCUs:
  • Standardized measurement: OCUs provide a consistent way to measure resource usage across different features
  • Time-based consumption: OCUs are consumed over time while resources are active
  • Credit conversion: Your subscription credits are converted to OCUs for actual usage tracking
  • Resource scaling: Different environment sizes and AI operations consume OCUs at different rates

Environment Usage

Running environments consume OCUs based on their computational requirements and duration.

How Environment OCUs Work

Resource-based consumption:
  • Environment size: Larger environments (more CPU/memory) consume more OCUs per hour
  • Active time: OCUs are consumed only while environments are running
  • Automatic stopping: Environments automatically stop after inactivity to conserve OCUs
Environment lifecycle:
  1. Starting: OCU consumption begins when environment starts
  2. Running: Continuous OCU consumption while active
  3. Idle timeout: Environment stops automatically after 30 minutes of inactivity
  4. Stopped: No OCU consumption when environment is stopped

Environment Size and OCU Rates

Different environment classes consume OCUs at different rates:
  • Standard environments: Base OCU consumption rate
  • Large environments: Higher OCU consumption for increased resources
  • Custom configurations: OCU rates vary based on CPU and memory allocation
Billing configuration interface showing environment and usage settings

Configure billing settings and environment limits

AI Usage

AI features in Ona also consume OCUs when you use AI-powered functionality.

AI OCU Consumption

AI features that consume OCUs:
  • Code generation: AI-powered code suggestions and completions
  • Code explanation: AI analysis and explanation of code
  • Chat interactions: Conversations with AI assistants
  • Code refactoring: AI-assisted code improvements
OCU consumption patterns:
  • Per-request basis: Each AI interaction consumes a specific amount of OCUs
  • Variable consumption: Complex requests may consume more OCUs than simple ones
  • Real-time deduction: OCUs are deducted immediately when AI features are used

Managing AI Usage

Optimization strategies:
  • Selective usage: Use AI features when most beneficial
  • Batch requests: Combine multiple questions into single interactions when possible
  • Monitor consumption: Track AI OCU usage through billing dashboard
Usage limit configuration interface for managing OCU consumption

Update usage limits for environments and AI features

Credit to OCU Conversion

Your subscription credits are converted to OCUs for actual usage tracking. Learn more about subscription plans and credit allocation.

How Conversion Works

Credit system:
  • Monthly allocation: Subscription plans include a specific number of credits
  • OCU conversion: Credits are converted to OCUs at a fixed rate
  • Usage tracking: OCU consumption is tracked in real-time
  • Credit depletion: When OCUs are consumed, equivalent credits are deducted

Optimizing OCU Usage

Maximize your credit efficiency with these optimization strategies.

Environment Optimization

Best practices:
  • Delete unused environments: Remove environments when not needed
  • Right-size environments: Choose appropriate environment size for your tasks

AI Usage Optimization

Efficient AI usage:
  • Targeted requests: Ask specific, focused questions
  • Context awareness: Provide relevant context to get better responses
  • Review before requesting: Check if information is available in documentation first
  • Batch similar requests: Combine related questions when possible

Troubleshooting Usage Issues

Common usage-related issues and solutions.

High OCU Consumption

Potential causes:
  • Long-running environments: Environments left running unnecessarily
  • Oversized environments: Using larger environments than needed
  • Frequent AI usage: Heavy reliance on AI features
  • Multiple concurrent environments: Running several environments simultaneously
Solutions:
  • Review active environments: Check and stop unused environments
  • Optimize environment size: Use smallest suitable environment configuration
  • Use environment sharing: Share environments within teams when appropriate

Credit Depletion

When credits run low:

Next Steps