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Disk I/O % Utilization

Description

Disk I/O % Utilization alerts indicate that the percentage of disk IOPS utilized reaches a specified threshold. This threshold is specified when the alert is created.

Note

The utilization measurements for the following alerts include requests from all processes, not just MongoDB processes.

Disk I/O % utilization on Data Partition occurs if the percentage of time during which requests are being issued to any partition that contains the MongoDB collection data meets or exceeds the threshold.

Disk I/O % utilization on Index Partition occurs if the percentage of time during which requests are being issued to any partition that contains the MongoDB index data meets or exceeds the threshold.

Disk I/O % utilization on Journal Partition occurs if the percentage of time during which requests are being issued to the partition that contains the MongoDB journal meets or exceeds the threshold.

Possible Observations

These are a few possible methods to observe high Disk I/O % Utilization:

  • The Disk IOPS graph in the cluster metrics shows higher IOPS than the provisioned IOPS for the cluster. The Disk IOPS graph is located under the Hardware Metrics section of the Metrics tab.
  • There is a high IOWait curve in the Normalized System CPU metric. IOWait measures the percentage of time the CPU is idle and waiting for an I/O operation to complete. The Normalized System CPU graph is located under the Hardware Metrics section of the Metrics tab.

Common Triggers

These are a few common events which may lead to high Disk I/O % Utilization and trigger these alerts:

Possible Solutions

These are a few possible actions to consider to help resolve Disk I/O % Utilization alerts:

  • Optimize your queries.

  • Use the MongoDB Atlas Performance Advisor to view slow queries and suggested indexes.

  • Review Indexing Strategies for possible further indexing improvements.

    Note

    Creating new indexes may result in a temporary spike in IOPS.

  • Analyze Query Performance to review how your queries are using your indexes.

  • Utilize a faster disk drive with higher IOPS.

  • Distribute operations from disks with exceedingly large workloads onto different disks.