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Review Serverless Metrics

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  • Chart Controls
  • Chart Display
  • Chart Selection

To view the metrics for a specific Atlas serverless instance from the Database view of a project, click the View Monitoring button for that serverless instance. Alternatively, click on the name of the serverless instance to open the overview, then click Monitoring and the Metrics tab.

Monitor database deployment metrics to identify performance issues and determine whether your current database deployment meets your requirements. For more information on the metrics available to monitor your database deployments, see Review Available Metrics.

The Metrics view has three distinct sections:

Note
Monitoring Data Storage Granularity

Atlas stores metrics data at increasing granularity levels. For more information, see Monitoring Data Storage Granularity.

Atlas provides the following controls for the Metric view. Adjusting any of these options affects all charts displayed under the Metrics view:

Control
Function
Granularity

Modifies the granularity of metrics displayed for each chart. Select a granularity, usually between 1 minute and 1 day (24 hours). Select Auto to automatically adjust the granularity based on the selected Zoom or Current Display date controls. Auto granularity selects the highest fidelity granularity available for the time range.

Note

Atlas supports a 10 second granularity only on M40 and larger clusters. To learn more, see Premium Monitoring Granularity.

Zoom
Modifies the date range of metrics displayed for each chart. Select a zoom range between 1 hour and 5 years. Adjusting the Zoom automatically adjusts the Current Display date range.
Filter by time range
Modifies the start and end date-time range of metrics displayed for each chart. Modifying the start and end date sets the value of Zoom to custom and overrides the previously selected zoom level.
Add Chart
Select one or more charts to display or hide.
Group Opcounters metrics
Directs Atlas to group the individual components of the Opcounters chart.

When viewing charts, you can do the following:

Task
Action
View a detailed description of a chart.

Hover your mouse over the chart to display the context menu.

Click next to the chart name to open the Chart Info modal. This modal includes a breakdown of the chart's data series, the annotations available for that chart, and the operations the chart supports.

Zoom in on a period of time.

Click and drag the mouse pointer over a portion of the chart.

To reset to the originally selected range (zoom out), double-click the chart.

Note

When you zoom in on one period of time, the Current Display date range in the chart control section automatically updates to reflect the selected period.

View statistics at a particular time.
Hover the mouse pointer over a point on the chart.
Move a chart.
Click and hold the grabber in the upper left corner of the chart, and drag the chart to the new position.
View a chart in list or tile format.
Click the list and tile toggle to switch between the list and tile view.

Atlas displays the available metrics to chart for the selected serverless instance under the Toggle Charts header.

Note

Currently, serverless instance metrics don't support any third-party monitoring services (for example, Datadog).

Connections

Number that indicates the total active connections to the database deployment.

Monitor connections to determine whether the current connection limits are sufficient. If necessary, upgrade the cluster tier.

Data Size

Number the indicates the amount of storage space in bytes that your stored data uses.

Monitor storage space to determine whether to use disk auto-scaling or manually increase the disk size. You can also monitor this metric to verify backup billing.

Execution Time

Metrics that indicate the average time in seconds to execute operations.

Monitor execution time for an increase in read operations to optimize queries and indexes.

Network

Metrics that indicate network performance.

Monitor network metrics to track network performance.

Opcounters

Metrics that indicate the operations per second run on a MongoDB process since the process last started.

Monitor MongoDB operations to validate performance issues related to high workloads. Confirm the type of operations responsible for the load.

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