![]() Surges in memory usage are usually related to database configuration specifications such as working memory (work_mem) or shared buffers, which define the memory limit to be used by a database. ![]() This makes memory usage a critical metric to monitor and observe for anomalies. Memory Usage - The system’s physical and swap memory (RAM) holds the data and instructions for low-latency processing. A common practice is to set up alerts when the CPU usage hits an alarming percentage (typically 85% of its allotted limit) to restrict an unresponsive database server. As the Postgres database relies on the server’s compute power (CPU) to run complex queries and perform batch updates, continuous monitoring of the CPU usage metric help detect exceeding/approaching CPU usage and detect processes causing the surge. Some of the host system resource metrics include:ĬPU Usage - Complex queries and large batch updates on Postgres often cause an outpour of the CPU usage. System Resource MetricsĪs the performance and health of any database typically rely on the underlying infrastructure of the host onto which it is deployed, system-level resource metrics help measure infrastructure resource usage that considerably impacts the performance of a database. PostgreSQL monitoring metrics are commonly categorized into host system metrics and database metrics that collectively help in efficiently identifying and mitigating potential concerns in real-time. Monitoring helps database administrators to detect changes in user access behavior, pinpoint the reasons and translate the findings into insights for business value. Monitoring is a crucial aspect for any highly available and performant database. In this article, we delve into key PostgreSQL metrics, recommended practices, and tools for PostgreSQL monitoring. Monitoring databases is also considered crucial for application performance as resource utilization and query optimization affect how well the server responds to queries. While the platform is known as one of the most advanced open-source databases, continuous performance optimization requires the comprehensive adoption of best practices and monitoring tools. PostgreSQL is widely adopted as an Object-Relational Database Management System (ORDBMS) since it offers a robust feature set to manage large, complex data sets, including structured (SQL) and unstructured (JSON) data.
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