Identifying and Managing Noisy Neighbors in Multi-Tenant PostgreSQL Deployments (On-Premise)

Abstract

In on-premise multi-tenant PostgreSQL deployments, multiple tenants share the same physical infrastructure to maximize resource utilization and reduce operational costs. However, this shared environment can give rise to significant resource contention, particularly when one tenant exhibits the “noisy neighbor” effect—where its workload consumes a disproportionate amount of CPU, memory, or disk I/O relative to others. This unbalanced resource consumption can lead to widespread performance degradation, manifesting as increased query latency, reduced throughput, and overall service instability. The present article investigates the challenges inherent in multi-tenant setups, focusing on the detection and management of noisy neighbors. It explores both native PostgreSQL monitoring techniques (such as system views and performance statistics) and external solutions including Linux control groups (cgroups) for isolating and limiting resource usage. Additionally, the article outlines best practices for proactive monitoring, query optimization, and resource allocation to ensure a balanced and efficient multi-tenant environment. By providing a comprehensive framework for understanding and mitigating the noisy neighbor phenomenon, this work aims to equip database administrators and system architects with effective strategies for maintaining robust performance, even under heavy and unevenly distributed workloads.