Best Practices for Postgres Database Replication
Written by Carlo Mencarelli
Scaling your database can be daunting, but with Postgres replicas, it doesn't have to be. Database replication not only ensures high availability but also helps keep your applications running smoothly, even under the strain of unexpected traffic spikes or server failures.
While you can maintain your replica on-site in the same data center, ideally, the replica would be situated in a geographically distinct location in case of a critical outage or disaster.
A database replica is not only for disaster recovery, though. While it is the best way to ensure you can keep during a data center outage, replica nodes are also great for scaling and splitting workloads across multiple instances or bringing data closer to your users.
What Is a Database Replica?
We’ve written about database replicas before. At the core, a database replica is a copy of your database. It may be used as a read replica, a hot standby, or even as a testing and performance node. When configuring replication, you designate one node as the primary and the others as the replicas. The Write Ahead Logs (WAL) maintain synchronicity by maintaining a record of all changes (Inserts, Updates, and Deletes) made to the database.
Replicas can improve disaster resilience by keeping an entire copy of your database in a separate data center or availability zone. During an outage, the administrator can failover to the replica and continue operations. PostgreSQL doesn’t offer native automatic failover, so this is something the administrator needs to implement or be prepared for. Timescale can help offload this responsibility in a variety of ways depending on the failure scenario.
Another great use case for replicas is to split the workload on the database system. For example, using a replica for all read traffic reduces the potential impact on the application if there is a sudden influx of update operations like inserting or backfilling large amounts of data. Ultimately, this benefits end users by increasing reliability. There is no distance limitation for replicas, so you can offer users improved performance via a read replica no matter what continent they are on.
An often-forgotten use for database replicas is leveraging them for testing environments. Maintaining multiple different datasets depending on the environment can be challenging for organizations. It might be easier to use a replica of the production environment database to benchmark load and performance changes to the application. Replicas in non-production environments can also be great for tuning query performance in a safe environment before merging the changes to production.
Types of Postgres Database Replicas
There are two different types of replication in PostgreSQL: logical and physical. Both have pros and cons, as well as best practices. Logical replication copies the data in the database and the changes that happen and sends them to the replica to be applied. Physical replication operates by sending complete WAL files to the replica or streaming the changes directly to the replica using the changes recorded in the WAL as the source.
As mentioned earlier, there’s also the concept of a “hot standby” or read replica. The read replica is great for running read-only queries while maintaining a database that can be used as a failover node in an emergency.
Logical replicas copy the entire database structure and then make each change that happens on the source database to the replica. Logical replication is great for testing major version upgrades or limiting users’ access to specific subsets of data.
Physical replicas are precisely what they sound like a copy of the entire database on another physical machine. As noted, this is typically accomplished by sending WAL files or streaming changes to the destination database. These replicas are great choices for offsite backups and read replicas. Since the changes can be replicated at the disk level, you can be sure that the changes that happen to each database will be the same.
Whether you use physical or logical replication, you can choose between asynchronous, synchronous write, or synchronous apply replication. Depending on the risk level, you may choose a different replication mode. For example, you only need eventual read consistency but need to support a high number of writes. In that case, you may choose asynchronous replication but understand that mode carries a level of data loss due to the nature of how the replication is done. Check out our blog on streaming replication if you need help choosing between these different modes.
Do’s and Don’ts of Database Replication
Replication can be complex, but fortunately, we can share some best practices and pitfalls to avoid reducing the difficulty of managing the process.
Best practices for replication
When setting up replication for PostgreSQL, it's crucial to follow best practices to ensure high availability, data integrity, and optimal performance. One of the most important aspects is implementing an automatic failover system. Failover protocols are essential for maintaining uptime during emergencies, such as hardware failures or network outages.
By having a robust failover mechanism in place, you can minimize downtime and ensure that your application remains operational despite unexpected issues. Additionally, combining failover with regular backups provides a two-layer protection system, allowing you to recover from data loss or corruption. Failover allows for stability during planned downtime, such as software updates or maintenance tasks.
It's worth noting that PostgreSQL does not have a built-in failover tool. However, several third-party solutions are available that can help you set up and manage failover in your PostgreSQL environment. Timescale, for example, offers a replication and failover implementation built on top of PostgreSQL's native replication capabilities, providing a seamless and reliable solution for high availability.
Another key consideration when setting up replication is choosing the right replication mode for your specific use case. Different replication modes offer varying levels of efficiency and consistency, and selecting the appropriate mode can significantly impact your system's performance.
For example, if your primary focus is write efficiency, you may opt for an asynchronous replication mode. This allows the primary server to commit transactions without waiting for the replicas to acknowledge receipt, resulting in faster write performance. On the other hand, if you require a balance between write performance and data consistency, synchronous write mode may be more suitable. In this mode, the primary server waits for at least one replica to acknowledge receipt before committing the transaction, ensuring consistent data across nodes.
Synchronous apply mode is the best choice for applications that demand maximum read consistency. In this mode, the primary server waits for all replicas to apply the transaction before considering it committed, guaranteeing that all nodes have the same data state. It's important to note that you can change the replication mode on a per-transaction basis, allowing you to fine-tune your replication setup based on the specific requirements of each operation.
To optimize your replication setup, it's essential to understand and adjust key replication parameters. These parameters can significantly impact the performance and behavior of your replicas, so in-depth testing should be conducted before deploying any of them to production. Some crucial parameters to consider include max_wal_size, hot_standby, max_wal_senders, wal_keep_size, and hot_standby_feedback.
The max_wal_size parameter determines the maximum size of the WAL files before automatic WAL file recycling occurs. Adjusting this value can affect the amount of storage space required and the time needed for crash recovery.
The hot_standby parameter enables read-only queries on replica servers, allowing you to offload read workloads from the primary server. max_wal_senders sets the maximum number of concurrent connections from replicas, while wal_keep_size specifies the minimum size of WAL files to retain for replica servers. Increasing these values can support more replicas but may consume more resources on the primary server. Finally, hot_standby_feedback allows replicas to send feedback to the primary server about their current state, helping to avoid query cancellations due to conflicts.
Monitoring your replicas is crucial to ensure they perform optimally and that emergency protocols are in place. Effective monitoring helps you identify and resolve issues before they impact your application's availability or performance. PostgreSQL provides various built-in monitoring tools and commands.
For example, the EXPLAIN command can help you analyze query performance by providing insights into the query execution plan. The pg_stat_activity view offers information about the current activity in the database, including running queries and their associated resources.
In addition to built-in tools, several third-party monitoring solutions are available. These tools often provide more advanced features and visualizations, making monitoring and troubleshooting your replication setup easier. Timescale offers monitoring dashboards that comprehensively overview your database's health, performance, and replication status. These dashboards can help you quickly identify bottlenecks, detect anomalies, and make informed decisions about scaling and optimization.
Replication pitfalls
When implementing replication, there are several pitfalls to be aware of that can impact the performance and consistency of your replicas. One common issue is the impact of heavy write loads on the replication process. When the primary server experiences a high concentration of write queries, it can slow down the replicas as they struggle to keep up with the incoming changes.
In such cases, the replicas may either become desynchronized, leading to inconsistent data, or they may wait for the WAL replication to catch up, resulting in increased latency. To mitigate this issue, breaking up large write queries into smaller batches is the way to go, allowing the replicas to process the changes more efficiently and maintain better synchronization with the primary server.
Another potential pitfall is the use of exclusive locks on source tables. When a query acquires a ACCESS EXCLUSIVE lock on a table in the primary server, the replicas must wait until the lock is released before they can replay the changes. This can lead to significant delays in the replication process, especially if the lock is held for an extended period.
To identify and address such delays, you can use the pg_locks view to monitor lock activity and adjust your queries accordingly. You can prevent replication delays and maintain a more responsive replica environment by minimizing exclusive locks and making sure that they are released promptly.
Read replication desynchronization is another common pitfall, mainly when using read replicas when data consistency is critical. If a read replica is not configured correctly or experiences frequent delays, it may provide stale or inconsistent data to the application. This can lead to incorrect query results and a poor user experience.
To avoid this issue, it's crucial to ensure that your read replicas are configured correctly and are suitable for your specific use case. If your application requires near-real-time data consistency, a read replica with significant delays may not be the right choice. In such cases, exploring alternative replication strategies or adjusting your application’s tolerance for slightly stale data may be necessary.
How Timescale Uses Database Replication
Timescale offers a range of tools and features that simplify database replication and enhance the overall experience. With Timescale, creating replicas is a straightforward process, thanks to intuitive tools and documentation. We have a comprehensive guide on PostgreSQL database replication which walks users through the steps involved in setting up and managing replicas. As mentioned earlier, Timescale offers native failover capabilities, ensuring high availability and minimizing downtime in the event of a primary server failure.
Monitoring replicas is crucial for maintaining a healthy and performant replication setup. Timescale provides a user-friendly replica monitoring interface that allows users to track their replicas’ status and performance easily. Metrics on the replica, such as CPU, memory utilization, replication lag, and more, are easily accessible.
Timescale also leverages logical replication to facilitate seamless platform transitions and migrations. Using logical replication allows users to replicate data between different database versions, making it an ideal tool for migrating databases with minimal downtime. This blog post on migrating a terabyte-scale PostgreSQL database to Timescale demonstrates how easy it is to migrate without downtime.
Next Steps
In this guide, we learned about the importance of database replication and best practices for maximizing its value. Replicas ensure high availability, smooth performance, and the ability to split workloads across multiple instances. We briefly explored the different types of replication, such as logical and physical, and the various modes like asynchronous, synchronous write, and synchronous apply. Then we dove into best practices and common problems that are found when using replication.
Best practices include implementing automatic failover, choosing the right replication mode, adjusting key parameters, and monitoring replicas effectively. We also discussed common pitfalls, such as heavy write loads, exclusive locks, and read replica desynchronization, along with strategies to mitigate them.
Lastly, we discovered how Timescale simplifies replication with intuitive tools, native failover capabilities, and a user-friendly monitoring interface. By leveraging these features and following best practices, users can create a robust and efficient replication setup that enhances their database's performance, reliability, and scalability.
Try it for free today to see how easy replication is with Timescale.