Production Best Practices

Predictive Auto-Scaling

Implement auto-scaling based on predictions rather than just current metrics:

def predictive_scaling(historical_data, forecast_horizon=24):
    """Generate scaling schedule based on predictions."""
    # Train forecasting model
    model = train_forecasting_model(historical_data)
    
    # Generate hourly predictions
    predictions = model.predict(horizon=forecast_horizon)
    
    # Convert predictions to scaling schedule
    scaling_schedule = []
    for hour, prediction in enumerate(predictions):
        required_instances = calculate_required_instances(prediction)
        scaling_schedule.append({
            'hour': hour,
            'instances': required_instances
        })
    
    return scaling_schedule

Capacity Risk Management

Manage capacity risks through systematic analysis:

1. Risk Identification: Identify potential capacity risks

   • Unexpected traffic spikes
   • Resource exhaustion
   • Dependency failures
   • Infrastructure outages

2. Risk Assessment: Evaluate likelihood and impact

   • Probability of occurrence
   • Potential service impact
   • Detection capability
   • Recovery time

3. Risk Mitigation: Implement strategies to reduce risk

   • Overprovisioning critical components
   • Implementing circuit breakers
   • Designing graceful degradation
   • Creating contingency plans

Example Risk Assessment Matrix:

Continuous Capacity Optimization

Implement a continuous optimization process:

1. Regular Capacity Reviews: Schedule periodic reviews

   • Weekly for short-term adjustments
   • Monthly for medium-term planning
   • Quarterly for long-term strategy

2. Automated Efficiency Analysis: Identify optimization opportunities

   • Underutilized resources
   • Over-provisioned services
   • Cost anomalies
   • Performance bottlenecks

3. Feedback Loops: Improve forecasting and planning

   • Track forecast accuracy
   • Document capacity decisions
   • Analyze incident capacity factors
   • Update models with new data

Capacity Planning Challenges and Solutions

Let’s address common challenges in capacity planning:

Challenge 1: Unpredictable Growth

Problem: Business growth doesn’t follow historical patterns.

Solutions:

• Implement scenario-based planning
• Maintain flexible infrastructure (cloud, containers)
• Create contingency plans for rapid scaling
• Establish early warning indicators

Challenge 2: Complex Dependencies

Problem: Service dependencies create cascading capacity requirements.

Solutions:

• Map service dependencies comprehensively
• Model capacity needs across the entire system
• Implement circuit breakers and fallbacks
• Test dependency failure scenarios

Challenge 3: Cost Constraints

Problem: Balancing reliability with cost efficiency.

Solutions:

• Implement tiered capacity strategies
• Use spot/preemptible instances for non-critical workloads
• Optimize resource utilization through better scheduling
• Implement cost allocation and chargeback

Challenge 4: Legacy Systems

Problem: Older systems with limited scalability.

Solutions:

• Identify and address bottlenecks
• Implement caching and offloading strategies
• Plan gradual modernization
• Create isolation boundaries around legacy components

Conclusion: Building a Capacity Planning Practice

Effective capacity planning is essential for SRE teams to maintain reliable, performant systems while optimizing costs. By implementing a structured approach to forecasting demand, modeling resource requirements, and planning capacity, you can ensure your infrastructure scales appropriately with your business needs.

Remember that capacity planning is not a one-time activity but a continuous process that improves over time. Start with the basics—collecting good data, establishing clear metrics, and creating simple models—then gradually incorporate more sophisticated techniques as your practice matures.

The most successful capacity planning practices combine quantitative analysis with engineering judgment, business context, and continuous learning. By following the methodologies and strategies outlined in this guide, you can build a capacity planning practice that supports your reliability goals while making efficient use of your infrastructure resources.