Cost Atlas
You can use Cost Atlas to view and break down your cloud spend across accounts, services, regions, resources, and usage types. It supports grouping, filtering, and cost-type selection to help you analyze spend patterns.
Cost Atlas provides unified cost analysis across all connected cloud providers - AWS, Azure, GCP, and OCI.
How to View the Cost Atlas
Log into OneLens.
Navigate to the Cost Atlas from the main dashboard.
Here is how the dashboard will look like:
Saved View
Start with the default view or predefined view for a quick overview, or switch to a saved view to tailor the dashboard layout and focus.
Default View
By default, the Cost Atlas opens with the following configuration:
Date Range: Last 2 weeks
Cost Type: Unblended cost
Granularity: Daily
Group By: Resource
If you mark a custom view as favourites, that view will replace the above system default as your new default view. The next time you open the page, your starred view (with its filters, grouping, and settings) will load automatically.
Learn how to save custom views.
Configure a Cost Report
To learn how to apply time filters, groupings, cost types, and filters, see Configuring a Cost Report.
Analyzing Cost Data
Once your report is configured, you can analyze cost data using key metrics and visual trends.
a. Key Metrics
Total Cost: Shows your overall cloud expenditure for the selected period.
Total Cost Delta: Highlights variations in costs compared to the corresponding previous period, helping you track increases or reductions.
You can set the timeframe of the previous period for comparison, allowing for flexible and context-specific analysis.
Cost MTD (Month-to-Date): Displays the total accumulated cost from the start of the current month to the present date.
b. Table
The table view includes the following key columns:
Displays overall spending for the selected period.
Refers to the cloud costs from the time period directly before the one you are currently viewing. For example:
If you are looking at costs for the month of March, the Previous Cost will show the expenses from February (the month immediately before March).
If you're looking at costs for a specific week, the Previous Cost will display the costs from the week before the one you selected.
Highlights the difference between the selected and previous periods.
You can view this cost either in:
Dollar Value
Percentage
Daily, weekly, or monthly breakdowns based on the selected granularity.
Each row in the table contains a Display option. This option allows users to highlight data in the chart, focusing on specific cost patterns visually.
Heatmap Mode
Heatmap mode is built into the cost table and always stays active. It automatically shades each cell based on its relative value to others in the same column. Higher costs appear with darker intensity, making it easy to spot spikes, dips, and outliers at a glance—no extra configuration needed.
Focus Mode
Focus Mode helps you isolate rows that show significant cost deviations. Enable it using the toggle available in the table section.
Configuration Steps When enabling Focus Mode, you can apply the following conditions to refine the table:
Set a threshold for average period – Display only rows where the average cost for the selected period is higher than your defined threshold.
Cost is lower than – Hide rows with costs falling below the specified value.
Rows do not match deviation parameters – Exclude rows that do not meet the configured deviation thresholds (useful for anomaly-focused analysis).
Use Cases
Day-wise cost tracking – Quickly detect daily anomalies or unusual spikes.
Month-to-month cost tracking – Identify significant changes between months to spot trends or possible inefficiencies.
Export Cost Report
You can also export cost reports for offline analysis and sharing with stakeholders:
Click on the Export button in the Cost Atlas section.
Select the preferred format for your report:
CSV: Ideal for detailed data analysis and manipulation.
Excel: Provides a spreadsheet version of the cost report.
Sample Export Preview
Below is a sample of how the exported file might look:
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