Cost Management- Cost Anomalies
The Cost Anomalies section helps users identify unexpected spikes in cloud costs and take necessary actions to mitigate them. It provides a breakdown of detected anomalies, their financial impact, and trends over time.
Cost Anomalies Detection
Overview
The Anomaly Detection feature in Thrusher is designed to help users identify, investigate, and address unexpected or unusual patterns in their AWS usage and spending. By leveraging this feature, users can proactively manage their cloud costs, avoid budget overruns, and ensure optimal resource utilization. This guide provides a comprehensive overview of the Anomaly Detection interface, its key components, and how to effectively use it to manage AWS anomalies.
Key Metrics & Insights
Total Anomalies – The total number of detected anomalies within the selected period, along with a comparison to the previous period.
High Severity Anomalies – Highlights anomalies that require immediate action due to significant cost deviations.
Total Cost Impact – Displays the extra amount spent due to cost anomalies.
Average Impact – Represents the average financial impact per anomaly.
Anomaly Trends
A line graph provides a visual representation of daily cloud costs versus expected costs. Key features include:
Daily Cost (Blue Line) – Represents actual cloud spend per day.
Average Cost (Red Line/Markers) – Identifies spikes where spending exceeded the expected baseline.
Selectable Time Period – Users can analyze trends over different time frames (e.g., last 7 days).
Recent Anomalies Table
The Recent Anomalies section provides details about detected anomalies, including:
Service Affected – Cloud service where the anomaly occurred.
Detection Time – When the anomaly was first identified.
Expected vs. Actual Cost – The baseline cost compared to the current actual cost.
Impact – The percentage increase over the baseline.
Severity Level – Indicates whether the anomaly is low, medium, or high severity.
Status – Tracks whether the anomaly is being investigated, resolved, or ignored.
Trend – Shows the percentage change over the past 24 hours.
Actions & Features
Configure Alerts – Users can set up alerts to receive notifications for future anomalies.
Filter & Sort – Anomalies can be filtered by severity and status, and sorted by date for easy tracking.
This section enables proactive monitoring of cloud expenses, helping users prevent unexpected overages and optimize spending efficiently.
The Anomaly Detection feature allows you to:
List Detected Anomalies : Provides a comprehensive list of anomaly detected in your AWS usage, including details such as anomaly type, severity, cost impact, and status.
Investigate Anomalies : Enables detailed investigation of each anomaly, helping you understand the underlying causes and take corrective actions.
Address Anomalies : Offers tools and recommendations to address and resolve anomalies, ensuring efficient resource usage and cost management.
Conclusion
The Anomaly Detection feature in Thrusher is a crucial tool for managing and optimizing your AWS costs. By providing detailed insights into anomalies and their underlying causes, it enables you to take proactive measures to address issues and ensure efficient resource usage. Regular use of this feature, along with best practices for anomaly management, will help you maintain control over your AWS spending and avoid unexpected cost increases.
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