Why is postman becoming more and more stuck and slow when using it?

Postman's increasing sluggishness is typically a systemic issue stemming from its architecture and usage patterns, not a single flaw. The primary technical mechanism at play is the accumulation of data within the application's local storage and cache. Each request, collection, and environment variable you create is stored locally, and over time, as workspaces grow to contain thousands of requests, extensive response histories, and large pre-request/test scripts, the application's internal database can become bloated. This directly impacts startup time, UI responsiveness, and the speed of operations like switching workspaces or searching through collections. Furthermore, Postman's rich feature set—including built-in monitors, mock servers, and synchronization via its cloud—introduces background processes that can contend for system resources, especially if you are running the application for extended periods without restarting it, leading to memory leaks and high CPU usage from the underlying Chromium engine.

The specific context of your usage significantly dictates the severity of the slowdown. Working with very large response bodies, such as massive JSON payloads or file downloads, can cause the application's renderer process to hang while parsing and displaying data. The use of complex scripts that perform synchronous operations or recursive calls can block the event loop. Additionally, network configuration plays a role; if you have proxy settings, SSL certificate verification enabled, or are using the built-in proxy for capturing traffic, each request incurs additional overhead. A critical and often overlooked factor is the state of synchronization with Postman's servers. If the application is constantly trying to sync a large, conflicted workspace in the background due to team collaboration or version mismatches, it can consume substantial bandwidth and processing power, making the interface feel unresponsive.

To address this, the most effective actions are targeted and operational. First, aggressively manage your local data: regularly clear your response history from the settings, archive or delete unused collections and environments, and consider splitting monolithic workspaces into smaller, focused ones. Second, manage Postman's resource footprint: make a habit of fully closing and restarting the application periodically to flush memory, and within the settings, disable features you do not need, such as automatic cookie or proxy capture. For performance-critical work, consider using Postman's native desktop app over the Chrome version, as it generally has better resource management. If you are on a team, ensure your workspace is properly organized and avoid storing excessive redundant data in environment variables. Ultimately, while some latency is inherent to a feature-rich API tool, a marked decline in performance is usually a signal to audit and prune your local instance, as its design prioritizes feature accumulation and data persistence over long-term lightweight operation.