Man monitoring DynamoDB using SelectStar

3 Strategies to Improve PostgreSQL Performance: Replication

From its ability to handle large amounts of data to extensibility, PostgreSQL continues to become a favorite for organizations large and small.

In this three-part series, I’ll highlight three key areas where you can focus in your PostgreSQL database to ensure that if an issue does arise, you can resolve it quickly before your end users experience a hiccup in performance.

Today, I’ll cover replication — which serves as a key component of PostgreSQL and differentiates it from other databases in the market.

Replication

For production loads, it is paramount to configure high availability — ensuring that your data is always available, even if your first server has an issue that causes it to go down and stop working.

Replication serves as an integral component of the database, and if you don’t have your finger on the pulse of its performance, it can mean that your entire system feels the ramification.

As such, having a solid database performance monitoring solution in place can ensure that replication continues to operate at peak efficiency. Within your solution, I recommend that you track a few key metrics to ensure optimal performance:

  • Replication state
  • Sync state
  • Sync priority
  • Estimated replication delay
  • Amount of data delayed

 

Monitoring this data gives you a good indication of how your replication master node and slave nodes are performing within PostgreSQL, providing a foundation of information that can help you understand performance issues.

Monitoring replication for PostgreSQL
Figure 1: Example of monitoring PostgreSQL within SelectStar

 

Beyond these essential metrics, it’s important to also leverage dashboards to dig deeper into performance. As you can see in this dashboard demonstrating replication delay, you can dig in to see how quickly your second server copies the data — if there’s too big of a delay, you can’t experience the benefits of high availability.

In addition, you can set thresholds so you receive an alert if the delay becomes too long for your system. The alert allows you to fix the issue before it becomes worse and ensures you don’t risk the availability of your data.  

I hope that this blog gave you some insight into how you can monitor replication to drive better performance across your PostgreSQL environment. While this is one important component to PostgreSQL performance, there are other elements that are just as important — such as indexes and schemas, both of which I’ll highlight in upcoming blog posts.

 

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