> For the complete documentation index, see [llms.txt](https://docs.datasentinel.io/manual/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.datasentinel.io/manual/features/tips-and-hints/read-replicas.md).

# Read Replicas

Datasentinel offers efficient monitoring of PostgreSQL Read Replicas through read-only access. It supports both local agent-based and agentless setups, ensuring flexible and seamless integration.

This capability becomes particularly crucial when dealing with replication setups.

In such scenarios, Datasentinel displays distinct icons to easily distinguish between different components of the replication architecture: a <mark style="color:blue;">**P**</mark> icon for the primary instance and an <mark style="color:blue;">**R**</mark> icon for read replicas. This intuitive visual representation aids in quickly identifying and understanding the layout of your replication architecture.

<figure><img src="https://1072624949-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FlcWi6G1jtNuyGT9C0pkc%2Fuploads%2FESgGgYfpaZhw8VCA6wZl%2FArchitectureWithReplication.png?alt=media&amp;token=439de479-5492-4062-868f-138f708f436e" alt=""><figcaption><p>Architecture example with a Primary and 2 Read Replicas</p></figcaption></figure>

Furthermore, by [tagging your primary and read replica instances](/manual/features/tips-and-hints/tags.md) with a common identifier, users can benefit from the [Consolidated View Feature](/manual/features/tips-and-hints/consolidated-view.md). This allows the analysis of the entire database architecture through a single, unified dashboard.

It simplifies the process of monitoring and managing multiple instances, ensuring that the health and performance of both primary and replica databases are within easy reach.

{% hint style="info" %}
For a deeper dive into how Datasentinel enhances database monitoring, refer to our detailed blog post: [High-Availability Cluster Monitoring with Datasentinel](https://blog.datasentinel.io/post/ha_cluster/).

This post elaborates on the practical applications of Datasentinel in real-world scenarios, demonstrating its effectiveness in analyzing complex database environments.
{% endhint %}


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