Cost Anomaly Detection

Use machine learning to automatically detect unusual spending patterns before they become billing disasters.

Why it matters

Cost Anomaly Detection uses machine learning to learn your normal spending patterns and automatically alerts you when something looks unusual. Unlike budgets where you set fixed thresholds, this catches unexpected spikes you didn’t plan for.

Examples of anomalies it catches:

  • Lambda function stuck in infinite loop
  • Misconfigured auto-scaling group
  • Accidental data transfer to the internet
  • Dev environment left running over the weekend

Author’s note: This is highly recommended. It works as a charm and has saved me from countless billing surprises with zero maintenance effort.

How it works

  1. AWS analyzes your historical spending patterns
  2. Machine learning builds a model of “normal” for your account/services
  3. When actual spend deviates significantly, you get an alert
  4. No configuration needed - it learns automatically

Budgets vs. Anomaly Detection

Use both together:

  • Budgets - Alert when you hit expected spending limits (planned capacity)
  • Anomaly Detection - Alert when something unexpected happens (errors/misconfigurations)

Budgets protect against predictable overruns. Anomaly Detection catches surprises.

Resources