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Troubleshoot Replica Sets

On this page

  • Check Replica Set Status
  • Check the Replication Lag
  • Slow Application of Oplog Entries
  • Test Connections Between all Members
  • Socket Exceptions when Rebooting More than One Secondary
  • Check the Size of the Oplog

This section describes common strategies for troubleshooting replica set deployments.

To display the current state of the replica set and current state of each member, run the rs.status() method in a mongosh session that is connected to the replica set's primary. For descriptions of the information displayed by rs.status(), see replSetGetStatus.


The rs.status() method is a wrapper that runs the replSetGetStatus database command.

Replication lag is a delay between an operation on the primary and the application of that operation from the oplog to the secondary. Replication lag can be a significant issue and can seriously affect MongoDB replica set deployments. Excessive replication lag makes "lagged" members ineligible to quickly become primary and increases the possibility that distributed read operations will be inconsistent.

To check the current length of replication lag:

  • In a mongosh session that is connected to the primary, call the rs.printSecondaryReplicationInfo() method.

    Returns the syncedTo value for each member, which shows the time when the last oplog entry was written to the secondary, as shown in the following example:

    syncedTo: Thu Apr 10 2014 10:27:47 GMT-0400 (EDT)
    0 secs (0 hrs) behind the primary
    syncedTo: Thu Apr 10 2014 10:27:47 GMT-0400 (EDT)
    0 secs (0 hrs) behind the primary

    A delayed member may show as 0 seconds behind the primary when the inactivity period on the primary is greater than the members[n].secondaryDelaySecs value.


    The rs.status() method is a wrapper around the replSetGetStatus database command.

    Starting in MongoDB 7.0 (and 6.0.13, 5.0.24), the totalOplogSlotDurationMicros in the slow query log message shows the time between a write operation getting a commit timestamp to commit the storage engine writes and actually committing. mongod supports parallel writes. However, it commits write operations with commit timestamps in any order.


    Consider the following writes with commit timestamps:

    • writeA with Timestamp1

    • writeB with Timestamp2

    • writeC with Timestamp3

    Suppose writeB commits first at Timestamp2. Replication is paused until writeA commits because writeA's oplog entry with Timestamp1 is required for replication to copy the oplog to secondary replica set members.

  • Monitor the rate of replication by checking for non-zero or increasing oplog time values in the Replication Lag graph available in Cloud Manager and in Ops Manager.

Possible causes of replication lag include:

  • Network Latency

    Check the network routes between the members of your set to ensure that there is no packet loss or network routing issue.

    Use tools including ping to test latency between set members and traceroute to expose the routing of packets network endpoints.

  • Disk Throughput

    If the file system and disk device on the secondary is unable to flush data to disk as quickly as the primary, then the secondary will have difficulty keeping state. Disk-related issues are incredibly prevalent on multi-tenant systems, including virtualized instances, and can be transient if the system accesses disk devices over an IP network (as is the case with Amazon's EBS system.)

    Use system-level tools to assess disk status, including iostat or vmstat.

  • Concurrency

    In some cases, long-running operations on the primary can block replication on secondaries. For best results, configure write concern to require confirmation of replication to secondaries. This prevents write operations from returning if replication cannot keep up with the write load.

    You can also use the database profiler to see if there are slow queries or long-running operations that correspond to the incidences of lag.

  • Appropriate Write Concern

    If you are performing a large data ingestion or bulk load operation that requires a large number of writes to the primary, particularly with unacknowledged write concern, the secondaries will not be able to read the oplog fast enough to keep up with changes.

    To prevent this, request write acknowledgment write concern after every 100, 1,000, or another interval to provide an opportunity for secondaries to catch up with the primary.

    For more information see:

Administrators can limit the rate at which the primary applies its writes with the goal of keeping the majority committed lag under a configurable maximum value flowControlTargetLagSeconds.

By default, flow control is enabled.


For flow control to engage, the replica set/sharded cluster must have: featureCompatibilityVersion (fCV) of 4.2 and read concern majority enabled. That is, enabled flow control has no effect if fCV is not 4.2 or if read concern majority is disabled.

With flow control enabled, as the lag grows close to the flowControlTargetLagSeconds, writes on the primary must obtain tickets before taking locks to apply writes. By limiting the number of tickets issued per second, the flow control mechanism attempts to keep the lag under the target.

Replication lag can occur without the replica set receiving sufficient load to engage flow control, such as in the case of an unresponsive secondary.

To view the status of flow control, run the following commands on the primary:

  1. Run the rs.printSecondaryReplicationInfo() method to determine if any nodes are lagging:


    Example output:

    syncedTo: 'Mon Jan 31 2022 18:58:50 GMT+0000 (Coordinated Universal Time)',
    replLag: '0 secs (0 hrs) behind the primary '
    syncedTo: 'Mon Jan 31 2022 18:58:05 GMT+0000 (Coordinated Universal Time)',
    replLag: '45 secs (0 hrs) behind the primary '
  2. Run the serverStatus command and use the flowControl.isLagged value to determine whether the replica set has engaged flow control:

    db.runCommand( { serverStatus: 1 } ).flowControl.isLagged

    Example output:


    If flow control has not engaged, investigate the secondary to determine the cause of the replication lag, such as limitations in the hardware, network, or application.

For information on flow control statistics, see:

Secondary members of a replica set now log oplog entries that take longer than the slow operation threshold to apply. These slow oplog messages:

  • Are logged for the secondaries in the diagnostic log.

  • Are logged under the REPL component with the text applied op: <oplog entry> took <num>ms.

  • Do not depend on the log levels (either at the system or component level)

  • Do not depend on the profiling level.

  • Are affected by slowOpSampleRate.

The profiler does not capture slow oplog entries.

All members of a replica set must be able to connect to every other member of the set to support replication. Always verify connections in both "directions." Networking topologies and firewall configurations can prevent normal and required connectivity, which can block replication.


Before you bind your instance to a publicly-accessible IP address, you must secure your cluster from unauthorized access. For a complete list of security recommendations, see Security Checklist. At minimum, consider enabling authentication and hardening network infrastructure.

MongoDB binaries, mongod and mongos, bind to localhost by default. If the net.ipv6 configuration file setting or the --ipv6 command line option is set for the binary, the binary additionally binds to the localhost IPv6 address.

By default mongod and mongos that are bound to localhost only accept connections from clients that are running on the same computer. This binding behavior includes mongosh and other members of your replica set or sharded cluster. Remote clients cannot connect to binaries that are bound only to localhost.

To override the default binding and bind to other IP addresses, use the net.bindIp configuration file setting or the --bind_ip command-line option to specify a list of hostnames or IP addresses.


Starting in MongDB 5.0, split horizon DNS nodes that are only configured with an IP address fail startup validation and report an error. See disableSplitHorizonIPCheck.

For example, the following mongod instance binds to both the localhost and the hostname My-Example-Associated-Hostname, which is associated with the IP address

mongod --bind_ip localhost,My-Example-Associated-Hostname

In order to connect to this instance, remote clients must specify the hostname or its associated IP address

mongosh --host My-Example-Associated-Hostname
mongosh --host

Consider the following example of a bidirectional test of networking:


Given a replica set with three members running on three separate hosts:




All three use the default port 27017.

  1. Test the connection from to the other hosts with the following operation set

    mongosh --host --port 27017
    mongosh --host --port 27017
  2. Test the connection from to the other two hosts with the following operation set from, as in:

    mongosh --host --port 27017
    mongosh --host --port 27017

    You have now tested the connection between and in both directions.

  3. Test the connection from to the other two hosts with the following operation set from the host, as in:

    mongosh --host --port 27017
    mongosh --host --port 27017

If any connection, in any direction fails, check your networking and firewall configuration and reconfigure your environment to allow these connections.

When you reboot members of a replica set, ensure that the set is able to elect a primary during the maintenance. This means ensuring that a majority of the set's members[n].votes are available.

When a set's active members can no longer form a majority, the set's primary steps down and becomes a secondary. The primary does not close client connections when it steps down.

Clients cannot write to the replica set until the members elect a new primary.


Given a three-member replica set where every member has one vote, the set can elect a primary if at least two members can connect to each other. If you reboot the two secondaries at once, the primary steps down and becomes a secondary. Until at least another secondary becomes available, i.e. at least one of the rebooted secondaries also becomes available, the set has no primary and cannot elect a new primary.

For more information on votes, see Replica Set Elections. For related information on connection errors, see Does TCP keepalive time affect MongoDB Deployments?.

A larger oplog can give a replica set a greater tolerance for lag, and make the set more resilient.

To check the size of the oplog for a given replica set member, connect to the member in mongosh and run the rs.printReplicationInfo() method.

The output displays the size of the oplog and the date ranges of the operations contained in the oplog. In the following example, the oplog is about 10 MB and is able to fit about 26 hours (94400 seconds) of operations:

configured oplog size: 10.10546875MB
log length start to end: 94400 (26.22hrs)
oplog first event time: Mon Mar 19 2012 13:50:38 GMT-0400 (EDT)
oplog last event time: Wed Oct 03 2012 14:59:10 GMT-0400 (EDT)
now: Wed Oct 03 2012 15:00:21 GMT-0400 (EDT)

The oplog should be long enough to hold all transactions for the longest downtime you expect on a secondary. [1] At a minimum, an oplog should be able to hold minimum 24 hours of operations; however, many users prefer to have 72 hours or even a week's work of operations.

For more information on how oplog size affects operations, see:


You normally want the oplog to be the same size on all members. If you resize the oplog, resize it on all members.

To change oplog size, see the Change the Size of the Oplog tutorial.

[1] The oplog can grow past its configured size limit to avoid deleting the majority commit point.


Replica Set Protocol Version