Cloud Cost Anomaly Detection: Catch Billing Surprises Early

The Problem with Cloud Billing Surprises

We've all been there: an unexpected cloud bill that's 2x, 5x, or even 10x higher than expected. Common causes include:

• Runaway auto-scaling
• Forgotten test resources
• Misconfigured services
• Data transfer spikes
• Cryptocurrency mining attacks

What is Cost Anomaly Detection?

Cost anomaly detection uses machine learning and statistical methods to identify unusual spending patterns. When costs deviate significantly from expected baselines, alerts are triggered.

Setting Up Anomaly Detection

AWS Cost Anomaly Detection

AWS offers native anomaly detection:

• Navigate to AWS Cost Management
• Select Cost Anomaly Detection
• Create a monitor (by service, account, or custom)
• Configure alert thresholds
• Set up SNS notifications

Limitations:

• AWS only
• Limited customization
• Basic alerting options

Azure Cost Management Alerts

Azure provides budget-based alerts:

• Go to Cost Management + Billing
• Create a budget
• Set threshold percentages
• Configure action groups

Limitations:

• Threshold-based, not ML-driven
• Requires manual threshold tuning
• Azure only

CloudSavvy Anomaly Detection

CloudSavvy provides advanced anomaly detection:

• ML-based detection across AWS and Azure
• Automatic baseline learning
• Instant email alerts
• Root cause suggestions
• Historical comparison

Best Practices for Anomaly Alerting

Configure appropriate thresholds:

• Too sensitive: Alert fatigue
• Too loose: Missed anomalies
• Start conservative, adjust over time

Set up multiple alert channels:

• Email for general awareness
• Slack/Teams for team visibility
• PagerDuty for critical issues

Establish response procedures:

• Who investigates alerts?
• What's the escalation path?
• How are issues documented?

Common Anomaly Patterns

Sudden spikes:

• Often caused by new deployments
• Check recent changes in AWS CloudTrail/Azure Activity Log

Gradual increases:

• Growing data volumes
• Accumulating snapshots/backups
• User/traffic growth

Periodic patterns:

• Month-end batch processing
• Marketing campaign traffic
• Seasonal business patterns

Responding to Anomalies

• Acknowledge: Don't ignore alerts
• Investigate: Check recent changes and metrics
• Contain: Stop bleeding if critical
• Fix: Address root cause
• Prevent: Add guardrails

Conclusion

Anomaly detection is your early warning system for cloud costs. Implement detection across all accounts and establish clear response procedures.

Try CloudSavvy's intelligent anomaly detection