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Review Available Metrics

You can review the following metrics to monitor your deployments. All hardware metrics include metrics or individual charts for maximum values.

Note

Cloud Manager can only collect hardware metrics if you have enabled an automation agent. A monitoring agent can only collect database metrics.

Important

The metrics available depend on your user role and deployment type.

Metric
Description
Asserts

Displays the following information:

  • regular displays the average rate of regular asserts raised per second over the selected sample period.

  • warning displays the average rate of warnings per second over the selected sample period.

  • msg displays the average rate of message asserts per second over the selected sample period. These internal server errors have a well-defined text string. MongoDB Atlas logs stack traces for these.

  • user displays the average rate of user asserts per second over the selected sample period. This metric includes asserts that a user generates, such as out of disk space or duplicate key errors.

Monitor asserts to track how many errors occur while trying to read or write data. Check the server logs to identify the source of any errors.

Avg Object Size

Displays the average object size across all collections in the database.

Monitor object size to track the size of your objects and better understand your database space.

Background Flush Avg

Displays the average time of background flushes in seconds. mongod writes to and flushes (fsyncs) journal files immediately. By default, all other data files are flushed every 60 seconds in the background.

Monitor the background flush average to determine whether this statistic is a significant percentage of 60 seconds. If so, this statistic could indicate that the server is bottlenecked on these writes. You might have a large number of random writes occurring. The operating system might flush data faster than every 60 seconds. In that case, this statistic will be a very small value even if the writing is a bottleneck.

Catalog

Displays the following information:

  • total databases displays the total number of non-system databases.

  • total collections displays the total number of collections across all non-system databases.

  • total views displays the total number of views across all non-system databases.

  • total indexes displays the total number of indexes across all non-system collections.

Monitor catalog counts to prevent an excessive number of databases, collections, views, or indexes from causing startup failures.

Collections

Displays the number of collections in the database.

Monitor collections to determine restart times, continuous backup performance, and stability.

Connections

Displays the total number of active connections to the deployment.

Monitor connections to determine whether the current connection limits are sufficient.

Cursors

Displays the following information:

  • totalOpen displays the number of cursors that the server is maintaining for clients. Since MongoDB exhausts unused cursors, this value is usually small or zero. However, if there is a queue, stale tailable cursors, or a large number of operations, this value might rise.

  • timedOut displays the average rate of cursors that have timed out per second over the selected sample period.

Monitor cursors to close unnecessary cursors and reduce the timeout configuration in the application.

Data Size

Displays the actual size of the data files in the database.

Monitor data size to ensure that database is not using too much memory or CPU.

DB Storage

Displays the following information:

  • storageSize displays the sum total amount of on-disk storage space allocated for document storage across all databases.

  • dataSize displays the amount of storage space in bytes that your stored data uses.

  • indexSize displays the sum total size in bytes of the index data across all databases.

Monitor storage space to determine whether to manually increase the disk size.

Disk IOPS

Displays input operations per second.

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

Disk Latency

Displays the following information:

  • read latency displays the average amount of time to read from disk.

  • write latency displays the average amount of time to write to disk.

Monitor disk latency to track the efficiency of reading from and writing to disk.

Disk Queue Depth

Displays the average length of the queue of requests issued to the disk partition that stores MongoDB data.

Monitor disk queue depth to identify potential issues and bottlenecks.

Disk Space Free

Displays the total amount of free space remaining on disk.

Monitor free disk space to determine whether to use disk auto-scaling or manually increase the disk size.

Disk Space Percent Free

Displays the total amount of free space remaining on disk as a percentage of the total disk space.

Monitor the percentage of free disk space to determine whether to use disk auto-scaling or manually increase the disk size.

Disk Space Used

Displays the total bytes of used disk space on the partition that runs MongoDB.

Monitor the used disk space to determine whether to manually increase the disk size.

Document Metrics

Displays the following information:

  • returned displays the documents per second returned.

  • inserted displays the documents per second inserted.

  • updated displays the documents per second updated.

  • deleted displays the documents per second deleted.

Monitor document metrics to measure the work MongoDB completes.

File Size

Displays the total size of all the data files in the database.

Monitor file size to deternine whether files are consuming excessive disk space.

Index Size

Displays the total size of all indexes in the database. This metric includes the overhead incurred by indexes on top of the actual document data on which the indexes are based.

Monitor the index size to manage your indexes. To learn more, see Indexing Strategies.

Indexes

Displays the total number of indexes in the database.

Monitor indexes to manage them. To learn more, see Indexing Strategies.

Max Disk IOPS

Displays the following maximum disk IOPS values over the time period specified by the metric granularity:

  • max read iops maximum disk read input operations per second.

  • max write iops maximum disk write input operations per second.

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

Max Disk Queue Depth

Displays the maximum disk queue depth values over the time period specified by the metric granularity. Disk queue depth is the average length of the queue of requests issued to the disk partition that stores MongoDB data.

Monitor disk queue depth to identify potential issues and bottlenecks.

Max Normalized System CPU

Displays the maximum CPU usage values 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.

Max Process CPU

Displays the following maximum process CPU values over the time period specified by the metric granularity:

  • max user displays the maximum percentage of time that the CPU spent servicing the MongoDB process.

  • max kernel displays the maximum percentage of time the CPU spent servicing operating system calls for the MongoDB process.

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

Max System CPU

Displays the maximum CPU usage values of all processes on the node.

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

Max System Memory

Displays the maximum system memory values in bytes.

Monitor memory to determine whether your currrent deployment meets your memory needs.

Memory

Displays the total consumption of memory in megabytes at a particular point in time:

  • resident displays the memory that the MongoDB process running on a node consumes. This metric excludes the consumption of other processes and does not represent the total memory that the node consumes.

  • virtual displays the memory reserved in disk to act as swap space.

  • mapped displays the number of MMAPv1 memory maps of all the data files. This number is likely similar to your total database(s) size. WiredTiger does not use memory mapped files, so this should be 0.

Monitor memory to determine whether your currrent deployment meets your memory needs.

Network

Displays the following information:

  • bytesIn displays the average rate of physical bytes (after any wire compression) sent to this database server per second over the selected sample period.

  • bytesOut displays the average rate of physical bytes (after any wire compression) sent from this database server per second over the selected sample period.

  • numRequests displays the average rate of requests sent to this database server per second over the selected sample period.

Monitor network metrics to track network performance.

Non-Mapped Virtual Memory

Displays the amount of virtual memory that the memory mapping of data files doesn't take into account.

Monitor non-mapped virtual memory to determine whether aspects other than memory mapping files use excessive memory. For example, this could indicate too many connections to the database. Each connection has a thread stack and the memory for those stacks can add up to a considerable amount. Keep this statistic reasonably low because the memory used here is unavailable for caching.

Normalized Process CPU

Displays the following information:

  • user displays the percentage of time that the CPU spent servicing the MongoDB process, scaled to a range of 0-100% by dividing by the number of CPU cores.

  • kernel displays the percentage of time the CPU spent servicing operating system calls for the MongoDB process, 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.

Normalized System CPU

Displays the 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.

Num Extents

Displays the total number of contiguously allocated chunks of data file space for the database.

Monitor this metric to better understand your database space.

Objects

Displays the number of objects in the database.

Monitor this metric to better understand your database space.

OpCounters

Displays the number of the following operations per second run on a MongoDB process since the process last started:

  • command (replica set) or cmd (sharded cluster)

  • query

  • insert

  • delete

  • update

  • getmore

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

Page Faults

Displays the average rate of page faults on this process per second over the selected sample period. In non-Windows environments this applies to hard page faults only.

Monitor page faults to determine whether to increase your memory.

Process CPU

Displays the following information:

  • user displays the percentage of time that the CPU spent servicing the MongoDB process.

  • kernel displays the percentage of time the CPU spent servicing operating system calls for the MongoDB process.

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

Queues

Displays the following information:

  • total displays the number of operations queued and waiting for any lock.

  • readers displays the number of operations queued and waiting for a read lock.

  • writers displays the number of operation queued and waiting for a write lock.

Monitor queues to identify potential issues and bottlenecks.

Query Targeting

Displays the following information:

  • scanned displays the number of index items scanned per second.

  • scanned objects displays the number of documents scanned per second.

Monitor query targeting to determine whether you have any inefficient queries.

Query Targeting

Displays the efficiency of read operations run on MongoDB:

  • scanned / returned displays the number of documents scanned to return one document.

  • scanned objects / returned the ratio of the number of documents scanned to the number of documents returned by queries, since the previous data point for the selected sample period.

Monitor query targeting to determine read efficiency and optimize queries and indexes.

Scan and Order

Displays the number of operations per second returning results that required a sort in-memory.

Monitor this metric to identify whether your queries need indexes.

Shard Data Size

Displays the amount of storage space in bytes that your stored data uses on each shard. You can access this chart only for sharded clusters with MongoDB 6.0+.

Monitor this metric to verify whether you have balanced shards.

Shard Document Count

Displays the number of documents on each shard. You can access this chart only for sharded clusters with MongoDB 6.0+.

Monitor this metric to verify whether you have balanced shards.

Storage Size

Displays the storage size of the database.

Monitor storage size to determine whether to manually increase the disk size.

System CPU

Displays the CPU usage of all processes on the node.

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

System Network

Displays the following information:

  • network bytes in displays the average rate of physical bytes that the network interface receives per second.

  • network bytes out displays the average rate of physical bytes that the network interface transmits per second.

    The Cloud Manager release on February 14, 2024 fixes an issue where Cloud Manager inaccurately reported this metric. This release resets this metric and the previous values no longer appear.

  • max network bytes in displays the maximum network bytes in values over the time period that the metric granularity specifies.

  • max network bytes out displays the maximum network bytes out values over the time period that the metric granularity specifies.

Monitor network metrics to track network performance.

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