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Optimize your Hopx usage to reduce costs while maintaining performance. Follow these best practices to get the most value from your sandboxes.

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Cost Optimization Tips

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1. Use Smaller Resources

Start with minimal resources and scale up if needed:
  • Python
  • JavaScript/TypeScript
from hopx_ai import Sandbox

# ✅ Good: Start with minimal resources (from template)
# Choose a template with minimal resources
sandbox = Sandbox.create(template="code-interpreter")

# If you need more resources, choose a different template
# or create a custom template with your desired resources

sandbox.kill()  # Cleanup

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2. Delete When Done

Always delete sandboxes after use:
  • Python
  • JavaScript/TypeScript
from hopx_ai import Sandbox

sandbox = Sandbox.create(template="code-interpreter")

try:
    result = sandbox.run_code("print('Hello')")
    # Do your work
finally:
    sandbox.kill()  # Always cleanup

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3. Use Pause Instead of Keeping Running

Pause preserves state but costs less than keeping sandboxes running:
  • Python
  • JavaScript/TypeScript
from hopx_ai import Sandbox

sandbox = Sandbox.create(template="code-interpreter")
sandbox.run_code("setup_code()")

# Pause when not in use (cheaper than keeping running)
sandbox.pause()

# Resume later
sandbox.resume()
sandbox.run_code("continue_work()")

sandbox.kill()  # Cleanup

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4. Share Sandboxes

Reuse sandboxes for multiple operations instead of creating new ones:
  • Python
  • JavaScript/TypeScript
from hopx_ai import Sandbox

# ✅ Good: Reuse sandbox for multiple operations
sandbox = Sandbox.create(template="code-interpreter")
try:
    sandbox.run_code("task1()")
    sandbox.run_code("task2()")
    sandbox.run_code("task3()")
finally:
    sandbox.kill()  # Always cleanup
# Better than creating 3 separate sandboxes

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Resource Optimization

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Monitor Resource Usage

Use metrics to understand your actual resource needs:
  • Python
  • JavaScript/TypeScript
from hopx_ai import Sandbox

sandbox = Sandbox.create(template="code-interpreter")

# Run your workload
sandbox.run_code("your_workload()")

# Check actual usage
metrics = sandbox.get_metrics_snapshot()
system = metrics.get('system', {})
cpu = system.get('cpu', {})
memory = system.get('memory', {})

print(f"CPU: {cpu.get('usage_percent', 0)}%")
print(f"Memory: {memory.get('used', 0) / 1024 / 1024:.2f}/{memory.get('total', 0) / 1024 / 1024:.2f} MB")

# Choose templates with appropriate resources based on actual usage
sandbox.kill()  # Cleanup

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Right-Size Resources

Match resources to your workload:
For simple scripts and basic operations:
  • Python
  • JavaScript/TypeScript
# Choose a template with minimal resources
sandbox = Sandbox.create(template="code-interpreter")

sandbox.kill()  # Cleanup
For data analysis with Pandas:
  • Python
  • JavaScript/TypeScript
# Choose a template with appropriate resources for data analysis
sandbox = Sandbox.create(template="code-interpreter")

sandbox.kill()  # Cleanup
For machine learning training:
  • Python
  • JavaScript/TypeScript
# Choose a template with high resources for ML training
# or create a custom template with your desired resources
sandbox = Sandbox.create(template="code-interpreter")

sandbox.kill()  # Cleanup

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Lifecycle Management

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Use Timeout for Automatic Cleanup

Automatically clean up sandboxes using timeout_seconds:
  • Python
  • JavaScript/TypeScript
from hopx_ai import Sandbox

# Automatically kills sandbox after timeout
sandbox = Sandbox.create(template="code-interpreter", timeout_seconds=600)
result = sandbox.run_code("print('Hello')")
# Sandbox is automatically killed after 600 seconds
# (No need to manually kill if timeout is set)

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Batch Operations

Group operations together to minimize sandbox creation:
  • Python
  • JavaScript/TypeScript
from hopx_ai import Sandbox

# ✅ Good: Batch operations in one sandbox
sandbox = Sandbox.create(template="code-interpreter")
try:
    # Process multiple files
    for file in files:
        sandbox.files.write(f"/workspace/{file.name}", file.content)
        sandbox.run_code(f"process_file('{file.name}')")
finally:
    sandbox.kill()  # Always cleanup

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Cost Comparison

StrategyCost ImpactUse Case
Minimal resourcesLowSimple scripts, testing
Right-sized resourcesMediumProduction workloads
Over-provisionedHigh❌ Avoid unless necessary
Reuse sandboxesLowMultiple operations
Create per operationHigh❌ Avoid
Pause when idleLowIntermittent workloads
Keep runningHigh❌ Avoid for idle sandboxes

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Next Steps

Core Concepts

Back to Core Concepts overview

Resources

Configure resources efficiently

Observability

Monitor resource usage

Sandbox Lifecycle

Manage lifecycle efficiently