AWS Case Study

AWS Auto Scaling

Use this page as a service-specific case-study starter for architecture, simulation, and optimization scenarios in pinpole.cloud.

Why this service matters

AWS Auto Scaling monitors applications and automatically adjusts capacity to maintain performance at the lowest cost.

Power:
- Unified scaling for EC2, ECS, DynamoDB, Aurora, and more
- Predictive scaling using ML for proactive capacity
- Target tracking, step, and scheduled scaling policies
- Scaling plans for multi-resource optimization

Important workflows

  • Design - Configure service behavior for your workload.

Configuration sections

  • Why Auto Scaling (Power + Limits)
  • Auto Scaling Settings

Key configuration points

PointDefault / ValueCategory
EnabledtrueAuto Scaling Settings
Scaling Strategytarget-trackingAuto Scaling Settings
Target CPU %70Auto Scaling Settings
Min Capacity1Auto Scaling Settings
Max Capacity10Auto Scaling Settings
Cooldown (seconds)300Auto Scaling Settings
Predictive ScalingfalseAuto Scaling Settings
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