🔍Anomaly Detection

Anomaly detection is a powerful feature of Economize that uses machine learning algorithms to detect anomalies in cost patterns. Anomaly detection is designed to help users identify and address unexpected spikes or unusual patterns in their cloud costs, which can be an indication of waste, misuse, or security issues.

Our anomaly detection feature uses machine learning algorithms to analyze historical cost data and identify patterns. The platform then uses this information to establish a baseline for normal cost behavior. Any cost pattern that deviates significantly from the established baseline is flagged as an anomaly.

Users can also view the anomalies by time period, enabling them to identify trends and patterns over time.

The anomaly detection feature also provides customizable alerts and notifications to users when anomalies are detected. Users can set up customized alerts to be sent via email, or slack messages, ensuring that they are immediately informed of any anomalies in their cloud costs.

Additionally, the platform's machine learning algorithms are continuously updated to ensure that they adapt to changes in cost patterns over time. This ensures that the platform can identify new types of anomalies as they emerge, ensuring that users are always informed of any cost-related issues.