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Review Cluster Metrics

On this page

  • View Metrics
  • Important Metrics
  • Monitoring Data Storage Granularity
  • Burst Reporting
  • Free Cluster and Shared Cluster Monitoring Considerations
  • Serverless Instance Monitoring Considerations
  • Manage Tags

Atlas collects and displays metrics for your servers, databases, and MongoDB processes.

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

Note

The number of servers that Atlas displays on the Metrics page at any given time depends on the browser screen size. Use the Toggle Members section to control which servers Atlas displays. Hover over the S and P icons to find out which servers they represent.

View Project Overview
The Clusters view displays all the clusters in an Atlas project and features core metrics per cluster. You can also view core metrics for a specific cluster on the Overview tab.
View Atlas Serverless Instance Metrics
View the metrics for a specific serverless instance in an Atlas project.
View Atlas Replica Set Metrics
View the metrics for a specific replica set in an Atlas project.
View Atlas Sharded Cluster Metrics
View the metrics for a specific sharded cluster in an Atlas project.
View MongoDB Processes
View the metrics for a specific MongoDB process in an Atlas cluster.
View Real-Time Performance Metrics
View real-time performance metrics for a specific Atlas cluster in a project.
View Atlas Search Metrics
View Atlas Search metrics for Atlas clusters with at least one active Atlas Search index.

You can monitor the following metrics to quickly gauge the health of your cluster.

Chart
Description
Connections

Number that indicates the total active connections to the cluster.

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

To learn more, see Fix Connection Issues and Fix Lost Primary.

Disk IOPS

Number that indicates the input operations per second.

Monitor whether disk IOPS approaches the maximum provisioned IOPS. Determine whether the cluster can handle future workloads.

To learn more, see Fix IOPS Issues and Fix Lost Primary.

Disk Usage

Number that indicates the total bytes of used disk space for the cluster.

Monitor the combined size of your data and MongoDB operational data (buffer, journal, and log files) on the cluster.

To learn more, see Fix Storage Issues.

Query Targeting

Number that indicates the efficiency of read operations run on MongoDB.

Monitor query targeting metrics to identify inefficent queries.

Note

The change streams cursors that the Atlas Search process (mongot) uses to keep Atlas Search indexes updated can contribute to the query targeting ratio and trigger query targeting alerts if the ratio is high.

To learn more, see Fix Query Issues.

Normalized System CPU

Number that indicates CPU usage of all processes on the node, scaled to a range of 0-100% by dividing by the number of CPU cores.

Monitor CPU usage to determine whether data is retrieved from disk instead of memory.

If you are unable to see the usage that triggered the alert, zoom in on the Normalized System CPU chart by clicking and dragging your mouse over the period of interest. With a higher-resolution view you may be able to identify acute spikes in CPU usage that weren't visible in the overview.

To learn more, see Fix IOPS Issues, Fix Lost Primary, and Fix CPU Usage Issues.

Oplog GB/Hour

Number that indicates the average rate in gigabytes of oplog data that the primary generates per hour.

Monitor oplog data to determine whether you have to increase the oplog size.

To learn more, see Fix Oplog Issues.

Util %

Percentage of time that requests are issued to and serviced by disk. This metric includes requests from any process, not just MongoDB processes.

Monitor whether utilization is high. Determine whether to increase the provisioned IOPS or upgrade the cluster.

To learn more, see Fix IOPS Issues.

Atlas stores metrics data at various granularity levels. For each granularity level, Atlas computes metrics as averages of the reported metrics at the next finer granularity level.

Example

At the end of a 60-minute period, Atlas generates a 1-hour metrics report. Atlas computes the value of the Connections metric in the 1-hour report as the average of all values for the Connections metric across the 60 1-minute reports that it generates in that hour.

Atlas gathers metrics data at a 1-minute granularity unless you qualify for premium monitoring.

When metrics data reach the end of their retention period, Atlas compacts them into a single unit of the next broader granularity level.

Example

After 48 hours' worth of data is collected, Atlas compacts each group of 60 minutes into a single unit of an hour. After 63 days, Atlas compacts each group of 24 hours into a single unit of a day.

Many metrics have a burst reporting equivalent. The value of a burst reporting metric at a given granularity is the maximum reported value from all the reports Atlas generates at the next finer granularity level during that interval.

Example

The Disk IOPS metric has a Max Disk IOPS equivalent. Atlas reports the Max Disk IOPS for a 1-hour interval as the highest Max Disk IOPS value across the 60 1-minute reports Atlas generated in that hour. Atlas reports the Max Disk IOPS for a 1-day interval as the highest Max Disk IOPS value across the 24 1-hour reports Atlas generated in that hour.

If you have at least one cluster that's M40 or larger, Atlas automatically enables premium monitoring for all clusters in the project. With premium monitoring enabled, Atlas gathers metrics data at a 10-second granularity. Premium monitoring remains enabled for all clusters in the project until you downgrade or terminate your last M40 cluster.

Atlas retains metrics data for a period of time that depends on the granularity of the data:

Data Period
Duration of Retention
10 seconds
8 hours
1 minute
48 hours
5 minutes
48 hours
1 hour
63 days
1 day
Forever

Premium monitoring only.

Atlas retains all database-specific statistics. MongoDB log data is retained at a maximum rate of 2000 lines per 2 minutes.

  • M0 free clusters and M2/M5 shared clusters support a subset of the metrics and charts available. For complete documentation on the limitations of M0/M2/M5 clusters, see Atlas M0 (Free Cluster), M2, and M5 Limits.

  • Atlas pauses monitoring for M0 free clusters which have had no connection activity for 7 days. Monitoring resumes once a successful connection occurs through the Atlas Administration API, Driver, mongosh, or Data Explorer.

  • Serverless instances support a subset of the metrics and charts available. For complete documentation on the limitations of serverless instances, see Serverless Instance Limits.

You can add a tag, view existing tags, and manage tags from the Clusters page or the Overview page. To learn more, see Manage cluster Tags from the Clusters Page and Manage cluster Tags from the Overview Page.

Important

Don't include sensitive information such as Personally Identifiable Information (PII) or Protected Health Information (PHI) in your resource tags. Other MongoDB services, such as Billing, can access resource tags. Resource tags are not intended for private and sensitive data. To learn more, see Sensitive Information.

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