Cost Anomaly Detection

Pattern-based anomaly detection identifies unexpected cost changes across your Azure environment—then correlates them with infrastructure modifications to explain why costs changed.

The Problem

Unexpected cost changes are difficult to understand and act on:

Delayed Discovery: Cost spikes often aren't noticed until the monthly bill arrives—weeks after the cause
Missing Context: Billing data shows what changed, but not why it changed
Manual Correlation: Connecting cost changes to infrastructure modifications requires tedious cross-referencing
Missed Savings: Cost drops from deprovisioned resources can go unnoticed, hiding optimization opportunities

The Solution

StratoLens detects cost anomalies and explains what caused them:

Early Detection: Identify cost spikes within days, not at month-end
Automatic Correlation: See which infrastructure changes caused the cost impact
Directional Awareness: Distinguish increases (potential problems) from decreases (potential savings)

See It In Action

Key Benefits

Detect cost spikes within days, not at month-end bill shock

Correlate cost changes with infrastructure modifications

Classify severity by percentage change and dollar impact

Analyze 60+ days of historical cost data for comprehensive trend detection

Common Use Cases

Investigate unexpected cost spikes by viewing correlated infrastructure changes

Detect accidental resource provisioning or configuration changes that increased spending

Identify cost savings opportunities from resources with sudden cost drops

Ready to Learn More?

Explore our documentation to see how Cost Anomaly Detection works in detail.

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