Replica Set Deployment Architectures
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The architecture of a replica set affects the set's capacity and capability. This document provides strategies for replica set deployments and describes common architectures.
The standard replica set deployment for a production system is a three-member replica set. These sets provide redundancy and fault tolerance. Avoid complexity when possible, but let your application requirements dictate the architecture.
Note
Outside of a rolling upgrade, all mongod members of
a replica set should use the same major version of
MongoDB.
Strategies
Determine the Number of Members
Add members in a replica set according to these strategies.
Maximum Number of Voting Members
A replica set can have up to 50 members, but only 7 voting members. If the replica set already has 7 voting members, additional members must be non-voting members.
Deploy an Odd Number of Members
Ensure that the replica set has an odd number of voting members. A replica set can have up to 7 voting members. If you have an even number of voting members, deploy another data bearing voting member or, if constraints prohibit against another data bearing voting member, an arbiter.
An arbiter does not store a copy of the data and requires fewer resources. As a result, you may run an arbiter on an application server or other shared resource. With no copy of the data, it may be possible to place an arbiter into environments that you would not place other members of the replica set. Consult your security policies.
Warning
Avoid deploying more than one arbiter in a replica set. See Concerns with Multiple Arbiters.
To add an arbiter to an existing replica set:
Typically, if there are two or fewer data-bearing members in the replica set, you might need to first set the cluster wide write concern for the replica set.
See cluster wide write concern for more information on why you might need to set the cluster wide write concern.
You do not need to change the cluster wide write concern before starting a new replica set with an arbiter.
Consider Fault Tolerance
Fault tolerance for a replica set is the number of members that can
become unavailable and still leave enough members in the set to elect a
primary. In other words, it is the difference between the number of
members in the set and the majority of voting members needed to
elect a primary. Without a primary, a replica set cannot accept write
operations. Fault tolerance is an effect of replica set size, but the
relationship is not direct. See the following table:
Number of Members | Majority Required to Elect a New Primary | Fault Tolerance |
|---|---|---|
3 | 2 | 1 |
4 | 3 | 1 |
5 | 3 | 2 |
6 | 4 | 2 |
Adding a member to the replica set does not always increase the fault tolerance. However, in these cases, additional members can provide support for dedicated functions, such as backups or reporting.
rs.status() returns majorityVoteCount
for the replica set.
Use Hidden and Delayed Members for Dedicated Functions
Add hidden or delayed members to support dedicated functions, such as backup or reporting.
Read-Heavy Applications
A replica set is designed for high availability and redundancy. In most cases secondary members operate under similar loads as the primary. You should not direct reads to secondaries.
If you have a read-heavy application, consider using Cluster-to-Cluster Sync to replicate data to another cluster for reading.
For more information on secondary read modes, see: secondary
and secondaryPreferred.
Add Capacity Ahead of Demand
The existing members of a replica set must have spare capacity to support adding a new member. Always add new members before the current demand saturates the capacity of the set.
Distribute Members Geographically
To protect your data in case of a data center failure, keep at least one member in an alternate data center. If possible, use an odd number of data centers, and choose a distribution of members that maximizes the likelihood that even with a loss of a data center, the remaining replica set members can form a majority or at minimum, provide a copy of your data.
Note
Distributing replica set members across two data centers provides benefit over a single data center. In a two data center distribution,
If one of the data centers goes down, the data is still available for reads unlike a single data center distribution.
If the data center with a minority of the members goes down, the replica set can still serve write operations as well as read operations.
However, if the data center with the majority of the members goes down, the replica set becomes read-only.
If possible, distribute members across at least three data centers. For config server replica sets (CSRS), the best practice is to distribute across three (or more depending on the number of members) centers. If the cost of the third data center is prohibitive, one distribution possibility is to evenly distribute the data bearing members across the two data centers and store the remaining member in the cloud if your company policy allows.
To ensure that the members in your main data center be elected primary
before the members in the alternate data center, set the
members[n].priority of the members in the alternate data
center to be lower than that of the members in the primary data center.
For more information, see Replica Sets Distributed Across Two or More Data Centers
Target Operations with Tag Sets
Use replica set tag sets to target read operations to specific members or to customize write concern to request acknowledgment from specific members.
Use Journaling to Protect Against Power Failures
MongoDB enables journaling by default. Journaling protects against data loss in the event of service interruptions, such as power failures and unexpected reboots.
Hostnames
Important
To avoid configuration updates due to IP address changes, use DNS hostnames instead of IP addresses. It is particularly important to use a DNS hostname instead of an IP address when configuring replica set members or sharded cluster members.
Use hostnames instead of IP addresses to configure clusters across a split network horizon. Starting in MongoDB 5.0, nodes that are only configured with an IP address fail startup validation and do not start.
Replica Set Naming
If your application connects to more than one replica set, each set must have a distinct name. Some drivers group replica set connections by replica set name.
Deployment Patterns
The following documents describe common replica set deployment patterns. Other patterns are possible and effective depending on the application's requirements. If needed, combine features of each architecture in your own deployment:
- Three Member Replica Sets
- Three-member replica sets provide the minimum recommended architecture for a replica set.
- Replica Sets Distributed Across Two or More Data Centers
- Geographically distributed sets include members in multiple locations to protect against facility-specific failures, such as power outages.